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Speaker 1: Mother Knows Dad starring Nicole and Jemmy and Maria qk.

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Speaker 2: Hi.

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Speaker 3: Everyone welcome The Mother Knows Death. We have a lot

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Speaker 3: of great stories for you this week. Today we are

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Speaker 3: going to get started talking about Taylan All you storing

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Speaker 3: pregnancy and its potential link to autism, the dead teenager

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Speaker 3: who was found in singer David's tesla, a man who

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Speaker 3: died on a ride at Universal, a surrogate who was

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Speaker 3: put on leave because she was carrying someone else's baby,

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Speaker 3: a mom and a daughter who are both pregnant by

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Speaker 3: the same man. And newborn babies that were switched and

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Speaker 3: given to different mothers in the hospital. All that and

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Speaker 3: more on today's episode. Let's get started with the big

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Speaker 3: news this week that there is some kind of a

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Speaker 3: link between Thailand all and autism.

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Speaker 1: I mean, this was pretty controversial yesterday on the internet,

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Speaker 1: with like, you know, one side having opinions, another side

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Speaker 1: having completely different opinions. So the news came out that

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Speaker 1: there's this potential link between tail and ill used during

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Speaker 1: pregnancy and autism, and the President is saying that FDA

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Speaker 1: will notify doctors of a very increased risk of autism

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Speaker 1: from using it, even though so many people are debating

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Speaker 1: that there are decades of research saying that this is

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Speaker 1: not the case and that it is very safe to use.

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Speaker 1: So how do you feel about this?

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Speaker 3: Well, first, I'm always skeptical of anything that the government

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Speaker 3: tells us at this point, so I always want to

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Speaker 3: do my own research on things, and even then you

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Speaker 3: can go to all different sources and you never really

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Speaker 3: know if you're getting the full story. But this isn't

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Speaker 3: really news to me. I feel like I've been hearing

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Speaker 3: this for a very very long time that there's some

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Speaker 3: kind of link with thailand all, and that's kind of

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Speaker 3: exactly where it stands. So they're saying that, and this

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Speaker 3: is a terminology thing. They're saying that thailand All in

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Speaker 3: pregnancy causes autism, and there's never really been a study

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Speaker 3: done that that says that there are studies done that

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Speaker 3: show that there is an association with it, which is

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Speaker 3: just a difference, which means that they've seen an increased

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Speaker 3: risk in autism in children that have been born to

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Speaker 3: mothers that took thailan al during pregnancy. However, they don't

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Speaker 3: know if it's thailand all mixed with the genetic component,

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Speaker 3: if it's Thailand all mixed with something else. They don't

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Speaker 3: know what the relationship is. They just know there's a relationship.

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Speaker 3: Does that make sense, Yes, it does.

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Speaker 1: So like with that in mind, I think it's it

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Speaker 1: seems irresponsible to have said that in the way they

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Speaker 1: did without having the data to back it up.

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Speaker 3: Yes, I mean they they the terminology is not correct

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Speaker 3: and people are jumping on that. So if they wanted

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Speaker 3: to say, we want to like this is what I

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Speaker 3: would have done. I would have said, you know, we

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Speaker 3: want to put a warning label on Thailan all because

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Speaker 3: there's some kind of association with it. We don't know

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Speaker 3: what it is yet, but we know that Thailand all,

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Speaker 3: either by itself or with something, is increasing the risk

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Speaker 3: of autism. And they, of course the way that they

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Speaker 3: say it just this is this is why there's a

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Speaker 3: lot of trust lost in just all of these different things.

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Speaker 3: And I feel kind of I don't know the word

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Speaker 3: I'm looking for is, but I just feel kind of

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Speaker 3: hopeless or something that now from now on, it's just

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Speaker 3: going to be like every other administration that's in the

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Speaker 3: White House, It's going to be like half of the

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Speaker 3: country doesn't listen to what they say because they hate

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Speaker 3: that person, then the other person comes in, and then

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Speaker 3: they like that person. You know, it's just going to

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Speaker 3: be this pingponging back and forth. So whoever hates this

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Speaker 3: dude is just going to disagree with it anyway regard

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Speaker 3: it doesn't It literally doesn't matter what he says. And

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Speaker 3: it's the same with the other side too. It doesn't

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Speaker 3: matter what anybody says. You're just going to find something

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Speaker 3: to nitpick and say that it's wrong. So, I mean,

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Speaker 3: the reason that it's irresponsible to say it in the

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Speaker 3: way that they did is because especially like I was

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Speaker 3: never a crazy pregnant person. Like I don't know, I've

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Speaker 3: work in the hospital. I say this all the time,

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Speaker 3: like all of the placentas that I would see with

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Speaker 3: like mothers on heroin and methadone and all of this,

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Speaker 3: you know, smoked crack, baby's born healthy, all this stuff, Right,

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Speaker 3: I just was kind of like, I mean and cheese

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Speaker 3: during pregnancy, Like I don't care, like you know, but

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Speaker 3: some people are extra extra extreme, like Andrea if you're listening,

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Speaker 3: but I mean, she had a hard time getting pregnant

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Speaker 3: and everything, and she was just very very like I

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Speaker 3: don't want to use this face, wash, I don't want

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Speaker 3: to dye my hair like you know, So when you

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Speaker 3: say that to to a pregnant person that tail and

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Speaker 3: all use causes autism, that's going to make a certain

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Speaker 3: amount of women never want to use it. Now, that's

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Speaker 3: fine if you want to. If you your knee hurts

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Speaker 3: or whatever, you have a headache and you just want

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Speaker 3: to like ride it out, that's totally that's fine, and

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Speaker 3: and really you should try to do that anyway, just

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Speaker 3: to minimize whatever you take during pregnant. But the problem

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Speaker 3: comes in when a woman gets sick when she's pregnant,

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Speaker 3: which happens like in fact, it happens more often because

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Speaker 3: pregnancy is you're considered im you know, compromised. Right, So

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Speaker 3: if you get an illness where you get a fever,

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Speaker 3: Thailand all brings the fever down. Having a fever during

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Speaker 3: pregnancy is not a good thing because it could it

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Speaker 3: could lead to miscarriage, honestly, like it could really make

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Speaker 3: you sick and the and risk the fetus his life

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Speaker 3: as well. So if you have people now that are

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Speaker 3: getting fevers that are now scared to death to take

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Speaker 3: tailand off to make it go away, that is going

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Speaker 3: to potentially be a problem. Right, So whereas if they said,

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Speaker 3: we think there's an association, but we're not sure what.

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Speaker 3: It just seems a little bit more like palatable that

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Speaker 3: people would be willing to take it if if they

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Speaker 3: were pregnant. You know.

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Speaker 1: Well, I also think an important detail, which of course

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Speaker 1: they don't have the data on, is are we talking

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Speaker 1: about this as pregnant women that took a handful of

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Speaker 1: them throughout their whole pregnancy or women that are popping

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Speaker 1: one every single day?

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Speaker 3: So yeah, I check this out, and according to Yaale

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Speaker 3: Public Health, it is frequent and prolonged aceto metafine use.

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Speaker 3: So it's not just like, oh, I took for during pregnancy. Now,

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Speaker 3: what you need to remember.

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Speaker 1: Is that.

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Speaker 3: Thailanol is basically the only kind of pain relieving, fever

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Speaker 3: reducing drug a woman could take during pregnancy.

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Speaker 1: Yeah, because they can't take insund so.

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Speaker 3: No, So now you have a situation where I mean

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Speaker 3: there's people who have rheumatar arthritis and lupus and just

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Speaker 3: headaches whatever whatever like sometimes people take thailanol every day

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Speaker 3: of their life for things like that. So I'm thinking

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Speaker 3: that it's more of those types of patients and like

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Speaker 3: I said, there's not. We don't know what the link

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Speaker 3: is because their study is done that have Thailand all

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Speaker 3: and autism, and they're just like, we can't make the connection.

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Speaker 3: So so it's it's definitely an association, but why kind

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Speaker 3: of we don't know why, right. Another thing though, from

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Speaker 3: the other side, is that we can't you know, I've

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Speaker 3: seen a bunch of doctors posting like Childer knows it's

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Speaker 3: been the safest drug in the world since not do

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Speaker 3: blah blah blah, and like that's to say that that

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Speaker 3: it's benign. It's the same with the vaccine talk and

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Speaker 3: all that shit, Like it's just like any single time

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Speaker 3: you're putting a drug in your body, even something like

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Speaker 3: Thailand all there there is a risk with with it.

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Speaker 3: It's a it's a safer drug for sure, but it's

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Speaker 3: definitely not one hundred percent benign. People have had issues

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Speaker 3: with it, including it's very easy to damage your liver

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Speaker 3: with it, really and especially if you already have liver damage,

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Speaker 3: like if you're a drinker, you could have serious problems

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Speaker 3: with not that much til at all. So but I

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Speaker 3: don't know, I just I just think that it's it's

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Speaker 3: just kind of like, I know that we've been talking

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Speaker 3: about this forever there's this potential link, but like, why

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Speaker 3: did it have to be announced in that way yesterday?

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Speaker 3: Just with like I feel like it wasn't very thought

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Speaker 3: out and tiptoed around because of how sensitive it is.

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Speaker 1: That's kind of what I'm getting at. Like, if they

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Speaker 1: went up there and did that press conference and we're like,

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Speaker 1: we've thought this for a while, we conducted these studies,

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Speaker 1: and this is what the studies have shown us, I

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Speaker 1: think a lot more people will be taking it seriously.

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Speaker 1: But you're like, you literally just went up there and

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Speaker 1: said something like you have you have like this basically

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Speaker 1: this conspiracy that there's a link between the two, but

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Speaker 1: you have nothing factually backing that up. And that's why

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Speaker 1: I think it was so controversial.

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Speaker 3: I mean, I guess this is the thing though. Obviously

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Speaker 3: because of COVID, there's been like a huge distrust in

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Speaker 3: public health, right and then this time around, they wanted

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Speaker 3: Robert Kennedy to be like, we're going to be more

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Speaker 3: transparent about what's going on. And this seems to have

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Speaker 3: come out of left field for many people because they've

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Speaker 3: I don't think they've really ever outwardly said that this

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Speaker 3: was and there was an association. So most people don't

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Speaker 3: check scientific papers and have no idea that this is

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Speaker 3: even a thing. Did you know this was a thing?

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Speaker 1: Well, I like not to the extent you did. I

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Speaker 1: I didn't know why everybody was freaking out about it

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Speaker 1: yesterday because I started seeing this popping up in the

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Speaker 1: news two to three weeks ago. So I was like,

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Speaker 1: why all of a sudden yesterday, is this like the

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Speaker 1: big deal? But I understand they did that big conference

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Speaker 1: about it.

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Speaker 3: Yeah, and like that's the thing. So the average the

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Speaker 3: average person that's your age, right, that's getting pregnant and

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Speaker 3: stuff like that, is like not aware of this association.

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Speaker 3: And I think that that's really all they should have

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Speaker 3: done was been like, hey, just the heads up, there's

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Speaker 3: some kind of association. You do what you want with

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Speaker 3: the information kind of thing. I don't know. I don't know,

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Speaker 3: Like I just don't. I don't really know if there's

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Speaker 3: something that they know that they're not telling us, or.

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Speaker 1: Well they didn't, they just didn't worry. It was messy.

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Speaker 1: It just was messy.

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Speaker 3: It was messy, and really like he like he shouldn't

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Speaker 3: have been talking about it. Really because he just is

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Speaker 3: He's not I don't think you have to be a

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Speaker 3: doctor to talk about it, but he's not a medical

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Speaker 3: person and it should have been explained a little bit better.

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Speaker 3: And I feel like from a medical person perspective, if

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Speaker 3: I was standing behind him, I would have been like,

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Speaker 3: oh God, just please stop. You're making it worse, like

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Speaker 3: and it kind of discredits something that might be very real.

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Speaker 1: Well yeah, and like also I wanted to note that

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Speaker 1: this article we're referencing, said tayl Nhill's maker, keV Kenvu

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Speaker 1: said Monday that it strongly disagrees that a state of

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Speaker 1: minifit causes autism, is deeply concerned about the healthas blah

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Speaker 1: blah blah blah. We also need to take in perspective.

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Speaker 1: Of course, the drug company is not going to come

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Speaker 1: out and agree with this finding that it's potentially gonna

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Speaker 1: make their stock flomit and their money go down. So like,

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Speaker 1: I think the important thing to realize here is everybody

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Speaker 1: needs to hear this and kind of do their independent

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Speaker 1: research and see if there have been proper studies conducted.

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Speaker 1: And it was like what we're saying all the time,

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Speaker 1: if a study is done and it does prove this,

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Speaker 1: let's make sure it's by an independent source, not like

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Speaker 1: ibuprofen running this study for real. Right, So I don't know,

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Speaker 1: I agree with you. It was just completely messy. And

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Speaker 1: if there is an association, like you're saying, they should

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Speaker 1: have said that in the way everybody's taking it, it's

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Speaker 1: just like, this is it, this is what's happening, and

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Speaker 1: this is what we believe, not like there is speculation

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Speaker 1: that there is a link between the two, pending further investigation.

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Speaker 3: So one of the you know, there's been lots of

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Speaker 3: statements issued by all of these health agencies and things,

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Speaker 3: and one of them said, quote, it is highly unsettling

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Speaker 3: that our federal health agencies are willing to make an

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Speaker 3: announcement that will affect the health and wellbeing of millions

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Speaker 3: of people without the backing of reliable data. Right, And

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Speaker 3: I agree with that statement. But like COVID, like hello,

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Speaker 3: COVID medicase, what about that whole thing that we had

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Speaker 3: to be six feet away from each other and they

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Speaker 3: ruined and closed restaurants because of it in businesses that

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Speaker 3: were in close quarters. And now they're just like, yeah,

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Speaker 3: we just kind of like arbitrarily made that up. You know,

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Speaker 3: so this is why, this is why we don't trust

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Speaker 3: it ever and and like will we ever again? I don't.

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Speaker 3: I don't really know, but you know, it's it's not

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Speaker 3: like this is unprecedent. This has happened. It happened with

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Speaker 3: COVID for sure, and yes with oxycotton. We could go

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Speaker 3: through the list of like all different things that they

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Speaker 3: told us were safe and weren't safe, and the implications

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Speaker 3: of something like Thailand all being considered not safe in

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Speaker 3: pregnancy is it's just so huge just because it so

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Speaker 3: many people get pregnant, and so many people are afraid

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Speaker 3: of autism, and so you know, so well, can you.

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Speaker 1: Imagine if a mother lost her life or a child

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Speaker 1: died prematurely or something because they had a fever that

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Speaker 1: could have been taken care of with taking a dose

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Speaker 1: and it was and they didn't do it because they

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Speaker 1: were scared.

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Speaker 3: The other thing is to is that for parents that

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Speaker 3: have autistic children. I don't know because I don't have

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Speaker 3: an autistic child, right, but I would think on one hand,

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Speaker 3: I would just want to know anything possible to help.

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Speaker 3: I mean, but at this point you already have the

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Speaker 3: autistic child. There's nothing that you could do to reverse

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Speaker 3: that kind of at this point. Except they did say

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Speaker 3: yesterday too that the FDA is now approving luc of

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Speaker 3: warren a medication for autism because they found.

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Speaker 1: That cancer medication.

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Speaker 3: Well, Lucia used to take it, okay, so it's it

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Speaker 3: is usually given to patients that have cancer. But since

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Speaker 3: she's got an autoimmune disease and the specific when she

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Speaker 3: was on the methotrexx eight they gave her, she had

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Speaker 3: to take that pill too. And they're finding that because

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Speaker 3: there is a like a full l eate deficiency and they

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Speaker 3: think there might be patients that have autism that they

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Speaker 3: have seen a little bit of an increase in their

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Speaker 3: verbal communication in some patients. So if I was a

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Speaker 3: mom that had a child that was having verbal communication issues,

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Speaker 3: I would be open to hearing about other things and

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Speaker 3: also just willing to listen to possible reasons why my

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Speaker 3: child did get autism, because like if you think about

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Speaker 3: it too, like let's say I had an autistic child, Well,

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Speaker 3: now you're of child bearing age, Like, wouldn't you want

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Speaker 3: to know what caused that? Because it could be something

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Speaker 3: genetically or something could be tilent. I'll mixed with the

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Speaker 3: genetics or whatever it is. And you know, I'm just

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Speaker 3: sure any active pregnant woman right now is probably just

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Speaker 3: freaking out over this because it's like you already stressed

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Speaker 3: out over every single detail and then this comes out

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Speaker 3: and you're like, well, what if I do have to

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Speaker 3: take it when I get sick and then that does

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Speaker 3: end up happening, But then what if it ends up

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Speaker 3: being something totally unrelated they do you need to be

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Speaker 3: more specific about about what they have studied as far

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Speaker 3: as the dosage that they think, because that could that

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Speaker 3: could be huge too. It also could be huge in

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Speaker 3: what trimester is it used in. There's all different things

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Speaker 3: that they need to really which they should have just

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Speaker 3: like slowed their role a little bit and like said, oh,

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Speaker 3: like say, for example, okay, thailanol, if you're taking more

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Speaker 3: than three or four thaileanol a week in the second trimester,

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Speaker 3: you're at an increased risk. Like be more specific instead

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Speaker 3: of just being like, yeah, that stuff's terrible. Like there's

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Speaker 3: like factories and and like people. I mean, I don't

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Speaker 3: care about pharmaceutical companies, but there's a lot of people

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Speaker 3: that rely on thailanol. I mean, could you imagine it's

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Speaker 3: it's probably the most common drug that's sold in in

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Speaker 3: the world. Really, I don't you know, Like seriously, if

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Speaker 3: you really think about it, it probably is.

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Speaker 1: I mean to me, this was just up there with

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Speaker 1: outrageous claims, as well as another thing that came out

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Speaker 1: yesterday that a raptures apparently happening today. So like, what

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Speaker 1: is going on today too? Sorry if you guys hear

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Speaker 1: this episode, I think we've survived.

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Speaker 3: But for now, all right, so let's let's talk about

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Speaker 3: we did. So we talked about this in the Grocerroom

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Speaker 3: Live YouTube, right, we haven't talked about this on this show, right, No, So.

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Speaker 1: This broke after we wrapped recording our episodes last week,

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Speaker 1: so we covered it on YouTube live and it was

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Speaker 1: initially when you know, just the bare amount of information

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Speaker 1: was coming out about it, and then we did a

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Speaker 1: really deep dive on it in the Grocery Room yesterday.

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Speaker 1: So a couple of weeks ago, police got a call

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Speaker 1: about this foul oder coming from a Tesla at an

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Speaker 1: impound lot. The car had only been there for two

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Speaker 1: days since it had been reported abandoned in a local neighborhood,

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Speaker 1: and when police got there, they found the badly decomposing

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Speaker 1: body of this missing teenager, Celeste Revas, and the car

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Speaker 1: has been is that has been is registered to the

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Speaker 1: singer David, who's been actively on tour for the last

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Speaker 1: couple of weeks.

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Speaker 3: So they so there's been a lot of different information

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Speaker 3: that's come out as far as what her body looked like,

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Speaker 3: and so they said that she was these are specific

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Speaker 3: words they use, severely decomposed. Her body was not intact,

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Speaker 3: and it was wrapped in plastic in the trunk of

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Speaker 3: the car. They also have said that it appears that

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Speaker 3: she was in the car for five days before it

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Speaker 3: got to the impound before it got to the impound lot,

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Speaker 3: so that and how long was it in the impound

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Speaker 3: lot Only two days, so a total of a week, right,

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Speaker 3: So if you date back and say, okay, what was

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Speaker 3: seven days before her body she was found on September eighth, correct, Yeah,

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Speaker 3: so September first ish around there he was on tour, yes,

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Speaker 3: So so okay, so that's the question, like, well, if

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Speaker 3: he's on tour and he has an alibi and he

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Speaker 3: wasn't there, then then who did this? Right?

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Speaker 1: Yes?

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Speaker 3: My other question though, is is it just possible that

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Speaker 3: because we don't have the autopsy report yet. We tried

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Speaker 3: to get it and it says we have we have

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Speaker 3: to wait for it to come in the mail, so

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Speaker 3: we'll get back to you in you know, two months.

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Speaker 3: But it says that the cause of death, the cause

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Speaker 3: of death is, and the manner of death are pending.

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Speaker 3: Like they are not putting an answer on the website

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Speaker 3: for the medical Examiner's office, so we only know these

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Speaker 3: little blips that they've given out to the media, and

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Speaker 3: we're not really sure if because sometimes if a non

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Speaker 3: medical person is writing an article, they might not be

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Speaker 3: explaining it correctly. And again we were just talking about

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Speaker 3: with the terminology with the tile and all thing like

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Speaker 3: when when the medical examiner says the body is not

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Speaker 3: intact to me, that means that they're there, the aren't

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Speaker 3: maybe the hand isn't attached, or their limbs aren't attached

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Speaker 3: or something like that. But you can't just jump to

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Speaker 3: the word dismemberment because when a person is severely decomposed,

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Speaker 3: like they said, you have to remember that all the

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Speaker 3: bones are stuck together with soft tissue, So if that decomposes,

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Speaker 3: then you could have like a natural dismemberment that wasn't

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Speaker 3: necessarily done by the person who killed her, So we

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Speaker 3: don't know any of that. But like I just I

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Speaker 3: just want to be careful of saying those words because

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Speaker 3: that's a whole different scene in a way.

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Speaker 1: Well yeah, and like we I think we talk. I

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Speaker 1: believe we talked about on the YouTube, but maybe you

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Speaker 1: and I talk but in a private conversation. But we

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Speaker 1: don't know for a fact that she was murdered at

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Speaker 1: this time. But the crime committed here was she was

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Speaker 1: put in a bag and put in a car, So

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Speaker 1: like somebody committed some form of a crime by putting

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Speaker 1: her in there. It's not like she got lot we

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Speaker 1: had done that dissection about the boys in Camden before

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Speaker 1: that got stuck in the trunk and died in the

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Speaker 1: car accidentally, that was not what happened. I guess it's

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Speaker 1: possible she crawled in the trash bag and closed the trunk.

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Speaker 3: But like listen, we just don't know. In the world

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Speaker 3: of forensics, like weirder things have happened, right, Do you

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Speaker 3: remember that one case, that Eliza Lamb case at that

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Speaker 3: Cecil hotel. Yeah, that she that was like so weird

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Speaker 3: that she ended up in the water supply tank of

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Speaker 3: the hotel. Like weird stuff happened sometimes, especially when people

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Speaker 3: are doing drugs or something or they're having some kind of,

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Speaker 3: uh A psychological issue. But I don't, I don't know,

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Speaker 3: Like I have a lot of questions about it, because

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Speaker 3: to me, the words severely decomposed means that this person

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Speaker 3: is like still as soft tissue attached, clearly because they

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Speaker 3: were able to identify this tattoo that she had matching

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Speaker 3: with him, right, so she has to have some kind

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Speaker 3: of soft tissue attached still. But a severely decomposed person

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Speaker 3: to me is like has a lot of soft tissue

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Speaker 3: missing and has some bones sticking out, and that even

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Speaker 3: though she was inside of a dark color car in

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Speaker 3: an area that was nineteen to ninety five degrees, that

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Speaker 3: level of decomposition, I just feel like, I don't know,

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Speaker 3: it's just it might. I don't want one hundred percent

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Speaker 3: say this because I didn't get to examine the body

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Speaker 3: and stuff. But when you if she was murdered and

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Speaker 3: she was put in the trunk right away, then she's

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Speaker 3: in an environment that has low oxygen, low air flow,

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Speaker 3: and more importantly, there's no access for insects or animals.

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Speaker 3: To get to her body. Right, So when you start decomposing,

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Speaker 3: the bacteria puts off these gases that attract like flies,

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Speaker 3: and then the flies lay eggs, and then they have maggots,

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Speaker 3: and the maggots eat the tissue and kind of help

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Speaker 3: break down the body. Well, when you don't have that

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Speaker 3: assistance in theory, it takes long. Even though it's so hot,

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Speaker 3: it takes longer to decompose to that level. So was

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Speaker 3: she there five d I don't know, Like, it's totally

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Speaker 3: possible she was killed and kept in a house for

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Speaker 3: a while and then moved to the car, Like I

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Speaker 3: just don't know.

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Speaker 1: Well that's what I was thinking. I mean, there's a

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Speaker 1: million scenarios that could have gone down, and nobody's been

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Speaker 1: arrested or charged. Right now, I think the most important

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Speaker 1: part of this case is that she was missing for

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Speaker 1: a year and a half. She was a minor. She

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Speaker 1: was found the day after what would have been her

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Speaker 1: fifteenth birthday, so we know she died at fourteen years old.

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Speaker 1: And you know, all these online salutes have been pulling

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Speaker 1: up all this data basically from discord and social media,

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Speaker 1: and of course this is not one hundred percent confirmed

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Speaker 1: by police. It that they possibly meaning Celeste and David,

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Speaker 1: had a relationship going back to possibly when she was

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Speaker 1: eleven years old.

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Speaker 3: Yeah, it's it's super bizarre because there's picture there's definitely

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Speaker 3: pictures of them together that multiple people have found through

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Speaker 3: different live streams that he's done. I mean, this guy's

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Speaker 3: got millions of followers. You have to think about that. So,

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Speaker 3: which is odd because this child, she's a child, was

433
00:25:45,359 --> 00:25:49,280
Speaker 3: reported missing and there is a poster floating around with

434
00:25:49,320 --> 00:25:51,720
Speaker 3: her picture on it and her name and her age,

435
00:25:52,359 --> 00:25:55,200
Speaker 3: and not one of the millions of people that saw

436
00:25:55,240 --> 00:25:59,199
Speaker 3: her and knew that her name was Celeste. Because he

437
00:25:59,480 --> 00:26:02,879
Speaker 3: was really not hiding it, right, he wrote a song

438
00:26:03,320 --> 00:26:05,280
Speaker 3: about a person named the Last He.

439
00:26:05,280 --> 00:26:07,760
Speaker 1: Wasn't hiding it. And then this video came out over

440
00:26:07,800 --> 00:26:12,520
Speaker 1: the weekend that her former teacher was using the case

441
00:26:12,560 --> 00:26:15,000
Speaker 1: as an example of how dangerous social media could be,

442
00:26:15,080 --> 00:26:18,000
Speaker 1: and a student filmed him talking about it. But he

443
00:26:18,160 --> 00:26:20,480
Speaker 1: was talking about her and how she met this guy

444
00:26:20,520 --> 00:26:23,520
Speaker 1: on social media and how he had picked her up

445
00:26:23,520 --> 00:26:25,600
Speaker 1: and brought her back. So she lived about ninety minutes

446
00:26:25,600 --> 00:26:29,400
Speaker 1: outside of La So, according to the teacher, David had

447
00:26:29,440 --> 00:26:32,199
Speaker 1: picked Celeste up, brought her back to La and the

448
00:26:32,200 --> 00:26:34,320
Speaker 1: police got her and brought her back home, and then

449
00:26:34,359 --> 00:26:36,880
Speaker 1: a couple months later is when she was declared missing

450
00:26:36,960 --> 00:26:40,479
Speaker 1: in April of twenty twenty four. So I'm just saying, like,

451
00:26:40,520 --> 00:26:44,720
Speaker 1: if they know he's involved, why did nobody know she

452
00:26:44,800 --> 00:26:49,119
Speaker 1: was there, especially because he wasn't seemingly hiding it. I

453
00:26:49,200 --> 00:26:51,960
Speaker 1: just think there are so many bizarre details of this case.

454
00:26:52,280 --> 00:26:54,800
Speaker 1: According to her brother, they had reported it to police

455
00:26:54,840 --> 00:26:57,000
Speaker 1: and thought that she was there, but nobody did anything

456
00:26:57,040 --> 00:26:57,560
Speaker 1: about it.

457
00:26:58,119 --> 00:27:02,119
Speaker 3: See, I was thinking from what I read that because

458
00:27:02,119 --> 00:27:05,080
Speaker 3: the mother said this too, Like the teacher said it,

459
00:27:05,480 --> 00:27:09,080
Speaker 3: everyone knew she had a rapper boyfriend named David, but

460
00:27:09,160 --> 00:27:12,560
Speaker 3: I don't think they knew it was him, you know

461
00:27:12,560 --> 00:27:15,040
Speaker 3: what I mean. That's the that's the problem. Like if

462
00:27:15,080 --> 00:27:16,560
Speaker 3: the brother goes to the cops.

463
00:27:17,000 --> 00:27:19,400
Speaker 1: If she ran away with him months before and they

464
00:27:19,480 --> 00:27:21,520
Speaker 1: retrieved her from his house.

465
00:27:21,880 --> 00:27:24,280
Speaker 3: I don't know if she was retrieved from his house

466
00:27:24,320 --> 00:27:29,200
Speaker 3: and if he was because obviously, like well it not obviously,

467
00:27:29,280 --> 00:27:32,600
Speaker 3: especially in California. But assuming the police show up and

468
00:27:32,640 --> 00:27:35,200
Speaker 3: there's a miner at a grown man's house, they would

469
00:27:35,680 --> 00:27:39,000
Speaker 3: do something about it. They probably got her, but she

470
00:27:39,280 --> 00:27:43,240
Speaker 3: was not associated with him at all. And that's why

471
00:27:43,320 --> 00:27:46,280
Speaker 3: they don't know who he is. So the brother goes

472
00:27:46,320 --> 00:27:48,440
Speaker 3: to the police and says, she has this rapper boyfriend

473
00:27:48,480 --> 00:27:50,040
Speaker 3: named David, Like, what the hell are they going to

474
00:27:50,119 --> 00:27:53,159
Speaker 3: do with that? Everybody's named David, Like that's not helpful

475
00:27:53,200 --> 00:27:55,080
Speaker 3: at all because they didn't know it was like that

476
00:27:55,280 --> 00:27:57,760
Speaker 3: stupid way he spells his name with the letter four

477
00:27:57,800 --> 00:28:00,879
Speaker 3: in it, that's impossible to That was real fun writing

478
00:28:00,960 --> 00:28:05,920
Speaker 3: about him yesterday with that stupid name. Anyway. So another

479
00:28:06,040 --> 00:28:08,639
Speaker 3: weird thing too, is that so this child went missing

480
00:28:08,640 --> 00:28:12,640
Speaker 3: at thirteen years old, and her mother had told police

481
00:28:12,680 --> 00:28:15,680
Speaker 3: that she had a tattoo on her finger that said

482
00:28:16,880 --> 00:28:20,199
Speaker 3: and I'm just like, how is this kid? So this

483
00:28:20,359 --> 00:28:22,800
Speaker 3: kid's on social media? This is how she meets this

484
00:28:22,840 --> 00:28:26,000
Speaker 3: guy David, Right, what was she on discord or something? Yeah,

485
00:28:26,040 --> 00:28:29,399
Speaker 3: which is just an absolute extra terrible one for a

486
00:28:29,480 --> 00:28:32,240
Speaker 3: kid to be on. And she's got a tattoo already.

487
00:28:32,240 --> 00:28:33,919
Speaker 3: She's thirteen, She's a little kid.

488
00:28:34,080 --> 00:28:37,000
Speaker 1: So all right, So I think the information about the

489
00:28:37,040 --> 00:28:41,440
Speaker 1: tattoo is a little confusing because I think what happened

490
00:28:42,560 --> 00:28:46,320
Speaker 1: was they looked at her remains, they narrowed her age

491
00:28:46,360 --> 00:28:49,959
Speaker 1: down to like eleven to sixteen, or something, and then

492
00:28:50,000 --> 00:28:53,400
Speaker 1: they cross examined that with missing persons and came across her,

493
00:28:53,960 --> 00:28:57,320
Speaker 1: and then when they notified the family, that's when they

494
00:28:57,320 --> 00:28:58,760
Speaker 1: found out about the tattoo.

495
00:28:59,280 --> 00:29:02,320
Speaker 3: No, no, the mother said that she had a tattoo.

496
00:29:03,400 --> 00:29:06,360
Speaker 1: Okay, so I guess I was reading it, which, like

497
00:29:06,440 --> 00:29:08,320
Speaker 1: they found out about it when they went.

498
00:29:08,280 --> 00:29:12,320
Speaker 3: Out the mother. That's part of the identification was that

499
00:29:12,400 --> 00:29:15,640
Speaker 3: the mother said she had this tattoo on her finger. Okay,

500
00:29:16,000 --> 00:29:18,680
Speaker 3: so the mom. So if the mom knew about it,

501
00:29:18,800 --> 00:29:21,400
Speaker 3: she was thirteen years old when she or earlier when

502
00:29:21,440 --> 00:29:24,080
Speaker 3: she got it, because that's the last time the mom

503
00:29:24,120 --> 00:29:24,800
Speaker 3: has seen her.

504
00:29:25,040 --> 00:29:27,480
Speaker 1: Well, I've been seeing a lot of criticisms towards the

505
00:29:27,560 --> 00:29:31,240
Speaker 1: mother too, about like how was you you know, why

506
00:29:31,360 --> 00:29:32,640
Speaker 1: was your kid on these platforms?

507
00:29:33,520 --> 00:29:37,080
Speaker 3: You think about the test and like I agree with

508
00:29:37,160 --> 00:29:40,480
Speaker 3: that completely, like that that could be a whole other episode.

509
00:29:40,520 --> 00:29:42,800
Speaker 3: But like, I'm not I'm not going to sit here

510
00:29:42,840 --> 00:29:48,480
Speaker 3: and like like her kid is dead in the back

511
00:29:48,520 --> 00:29:51,280
Speaker 3: of a car, like I toast, Like I'm not, I'm

512
00:29:51,320 --> 00:29:52,440
Speaker 3: not going there right now.

513
00:29:52,480 --> 00:29:56,720
Speaker 1: But like unless there's like confirmed information from the investigation

514
00:29:56,880 --> 00:30:00,400
Speaker 1: that shows her involvement in it, people should really leave

515
00:30:00,440 --> 00:30:00,800
Speaker 1: her alone.

516
00:30:00,800 --> 00:30:03,360
Speaker 3: Oh yeah, I mean and listen like it's it's it's

517
00:30:03,480 --> 00:30:05,880
Speaker 3: nice to talk about because it's a good lesson that

518
00:30:06,680 --> 00:30:09,520
Speaker 3: you can't you have to watch children on the internet

519
00:30:09,600 --> 00:30:11,720
Speaker 3: and every I mean, like we talk about this every

520
00:30:11,800 --> 00:30:16,040
Speaker 3: single week about some different story. But yeah, so when

521
00:30:16,040 --> 00:30:19,640
Speaker 3: they when they find remains like that, that's exactly what's

522
00:30:19,680 --> 00:30:21,680
Speaker 3: going to happen that first, they're just going to be, like,

523
00:30:21,800 --> 00:30:23,880
Speaker 3: you know, try to figure out who is this person,

524
00:30:24,520 --> 00:30:30,800
Speaker 3: And especially with with a teenage child, it's pretty easy

525
00:30:30,840 --> 00:30:35,800
Speaker 3: to pinpoint a narrow down range because of their teeth.

526
00:30:36,800 --> 00:30:42,680
Speaker 3: So there certain teeth come out at different ages. We

527
00:30:42,760 --> 00:30:46,400
Speaker 3: have the teeth, we have certain bones. Growth plates they

528
00:30:46,440 --> 00:30:49,040
Speaker 3: fuse at different ages, so you'll be able to see

529
00:30:49,080 --> 00:30:52,640
Speaker 3: when a child's still growing. So usually around twenty years old,

530
00:30:52,760 --> 00:30:55,840
Speaker 3: the growth plates are closed, so you could be like, okay,

531
00:30:55,880 --> 00:30:58,640
Speaker 3: well this child is under twenty years old. But then

532
00:30:58,680 --> 00:31:01,560
Speaker 3: you could say, okay, these more are grown in, so

533
00:31:01,720 --> 00:31:04,400
Speaker 3: they have to be somewhere in between eleven and twenty

534
00:31:04,400 --> 00:31:06,400
Speaker 3: and they could really just narrow it down based upon

535
00:31:06,440 --> 00:31:09,560
Speaker 3: what they see doing an X ray post mortem, So

536
00:31:10,040 --> 00:31:12,400
Speaker 3: door are gonna sit there and figure out, Okay, this

537
00:31:12,520 --> 00:31:18,240
Speaker 3: is definitely like either a tween or a teenager, and

538
00:31:17,680 --> 00:31:20,760
Speaker 3: it's not even the same as an adult because a

539
00:31:20,880 --> 00:31:22,960
Speaker 3: child there should always be a report out for a

540
00:31:23,000 --> 00:31:26,600
Speaker 3: missing child because it's a child, right, So then they

541
00:31:26,600 --> 00:31:29,400
Speaker 3: go through their database and then they find, oh that

542
00:31:29,440 --> 00:31:33,880
Speaker 3: there's this girl that's been missing thirteen years old and

543
00:31:33,960 --> 00:31:36,320
Speaker 3: she also has brown hairn she also has brown eyes.

544
00:31:36,760 --> 00:31:38,880
Speaker 3: And I don't know if the mother gave the tattoo

545
00:31:38,960 --> 00:31:43,760
Speaker 3: information or not to when the missing person report was filed.

546
00:31:44,160 --> 00:31:48,160
Speaker 3: But and then they can confirm obviously with DNA and

547
00:31:48,240 --> 00:31:50,840
Speaker 3: if the mother had dental records on her and stuff.

548
00:31:50,880 --> 00:31:54,440
Speaker 3: But I mean, it's it's really it's just terrible too

549
00:31:54,480 --> 00:31:58,280
Speaker 3: because even think about this, like if he had nothing

550
00:31:58,320 --> 00:32:02,479
Speaker 3: to do with her death, it's it's like he he

551
00:32:02,600 --> 00:32:06,680
Speaker 3: left for tour on July thirtieth and just like left

552
00:32:06,840 --> 00:32:08,720
Speaker 3: a child by yourself.

553
00:32:08,960 --> 00:32:13,240
Speaker 1: Well it's it's that detail that has me, you know, suspicious.

554
00:32:13,320 --> 00:32:16,240
Speaker 1: And also the fact that they found her body on

555
00:32:16,280 --> 00:32:19,280
Speaker 1: September eighth in his car. I'm assuming they alerted him

556
00:32:19,400 --> 00:32:22,520
Speaker 1: that day about it. Yeah, and he didn't stop touring

557
00:32:22,600 --> 00:32:26,040
Speaker 1: until his shows got canceled last week like ten days later.

558
00:32:26,720 --> 00:32:27,840
Speaker 3: Yeah, it's so weird.

559
00:32:27,920 --> 00:32:30,080
Speaker 1: So you can go on Okay, Like, I understand you

560
00:32:30,080 --> 00:32:32,320
Speaker 1: have obligations, but you're in the middle of a criminal

561
00:32:32,320 --> 00:32:33,440
Speaker 1: investigation right now.

562
00:32:33,520 --> 00:32:37,800
Speaker 3: So let's say this in theory. Let's say his best

563
00:32:37,840 --> 00:32:40,800
Speaker 3: friend was using his car while he was away, and

564
00:32:41,640 --> 00:32:43,760
Speaker 3: they called him and said, sir, there's a dead body

565
00:32:43,840 --> 00:32:47,239
Speaker 3: in your car. Like he didn't know it was her

566
00:32:47,400 --> 00:32:51,800
Speaker 3: right away? Right, So I mean listen, like any normal

567
00:32:51,840 --> 00:32:54,080
Speaker 3: person would be like, oh my god, I'm coming home,

568
00:32:54,160 --> 00:32:57,720
Speaker 3: like what is happening right now? But he didn't, which

569
00:32:57,760 --> 00:33:02,960
Speaker 3: is really, really really bizarre, is there. I'm just putting

570
00:33:02,960 --> 00:33:07,360
Speaker 3: this out there because we actually know someone that's something

571
00:33:07,400 --> 00:33:11,680
Speaker 3: similar like this has happened to. Is it possible that

572
00:33:12,520 --> 00:33:18,720
Speaker 3: he did not know that she was that age?

573
00:33:19,200 --> 00:33:24,760
Speaker 1: Like okay, like, because we know somebody had happened to possibly,

574
00:33:25,080 --> 00:33:29,000
Speaker 1: but she I'm thinking she's she's I'm thinking about Lillian,

575
00:33:29,120 --> 00:33:30,960
Speaker 1: right She's around the same age as Lilian and the

576
00:33:30,960 --> 00:33:34,560
Speaker 1: missing posters A she's declared a missing person and it

577
00:33:34,600 --> 00:33:38,280
Speaker 1: says her age on there. B. She looks like a

578
00:33:38,400 --> 00:33:41,080
Speaker 1: thirteen year old. She does not look like a twenty

579
00:33:41,120 --> 00:33:42,400
Speaker 1: year old.

580
00:33:42,120 --> 00:33:45,240
Speaker 3: But she in the one In the one picture she's

581
00:33:45,320 --> 00:33:49,360
Speaker 3: wearing like a tank top that's pretty low cut and

582
00:33:49,400 --> 00:33:53,320
Speaker 3: she has a little bit of cleavage there. I'm just saying, listen,

583
00:33:53,440 --> 00:33:59,200
Speaker 3: they're like Lillian, Lillian is is still she's not through

584
00:33:59,240 --> 00:34:02,760
Speaker 3: it yet, so she still has childlike appearances. But there

585
00:34:02,840 --> 00:34:07,400
Speaker 3: are children that some kids get, like my friend growing up,

586
00:34:07,400 --> 00:34:09,879
Speaker 3: get their period when they're in third grade and when

587
00:34:09,880 --> 00:34:12,000
Speaker 3: I'm very like mature looking.

588
00:34:12,200 --> 00:34:13,799
Speaker 1: But what I'm getting at is when I look at

589
00:34:13,840 --> 00:34:16,879
Speaker 1: photos of her, she's not very mature looking. She might

590
00:34:17,080 --> 00:34:19,960
Speaker 1: pass as a fifteen year old, but she's still a kid,

591
00:34:20,000 --> 00:34:22,120
Speaker 1: and she's still way too young to be with him.

592
00:34:22,280 --> 00:34:25,160
Speaker 1: So I think, even if they prove he had nothing

593
00:34:25,200 --> 00:34:28,319
Speaker 1: to do with her death, he's still a pedophile.

594
00:34:28,880 --> 00:34:31,680
Speaker 3: Like no, he is a relief just saying that, Like

595
00:34:32,080 --> 00:34:34,920
Speaker 3: if he's from another part of California and meets this

596
00:34:35,000 --> 00:34:38,759
Speaker 3: girl and they start dating and he just like never

597
00:34:38,800 --> 00:34:44,080
Speaker 3: met her family. She says she's seventeen or eighteen or whatever,

598
00:34:44,960 --> 00:34:48,440
Speaker 3: and then she left, Like if the police weren't involved

599
00:34:48,600 --> 00:34:52,600
Speaker 3: with him specifically, she could have just like broke up

600
00:34:52,600 --> 00:34:54,640
Speaker 3: with them and left and then came back. And like

601
00:34:55,000 --> 00:34:59,360
Speaker 3: he like, how would how would he know? This is

602
00:34:59,400 --> 00:35:03,040
Speaker 3: just a converse I want to have just because and

603
00:35:03,080 --> 00:35:04,600
Speaker 3: thank god I don't have a son that I don't

604
00:35:04,600 --> 00:35:06,959
Speaker 3: have to deal with this, but like there are situations

605
00:35:07,000 --> 00:35:10,920
Speaker 3: where where a teenage girl would lie and say that

606
00:35:10,960 --> 00:35:14,239
Speaker 3: she was older than she actually was. No sure that

607
00:35:14,320 --> 00:35:17,080
Speaker 3: could be like in the differential here too. Of just

608
00:35:17,120 --> 00:35:19,319
Speaker 3: trying to put that out there. I would just love

609
00:35:20,239 --> 00:35:22,880
Speaker 3: the data. I would love to see what he says

610
00:35:22,960 --> 00:35:26,200
Speaker 3: about it, because they're obviously interrogating.

611
00:35:26,280 --> 00:35:26,880
Speaker 1: We're going to have this.

612
00:35:26,960 --> 00:35:29,800
Speaker 3: Entire thing, and we're going to learn more about this obviously,

613
00:35:29,880 --> 00:35:31,600
Speaker 3: Like we'll talk about it more on this show once

614
00:35:31,640 --> 00:35:34,600
Speaker 3: we get the Autops Superport, if we and by the

615
00:35:34,640 --> 00:35:37,479
Speaker 3: time we get it, it's going to beyond well yeah,

616
00:35:37,560 --> 00:35:40,640
Speaker 3: cause like we ordered it, what two days after we

617
00:35:40,680 --> 00:35:42,680
Speaker 3: could have ordered it, so it'll all be online by

618
00:35:42,719 --> 00:35:46,560
Speaker 3: the time whoever ordered it first, you know. But I

619
00:35:46,600 --> 00:35:49,800
Speaker 3: mean obviously, so listen, I know that earlier you said

620
00:35:50,640 --> 00:35:52,799
Speaker 3: that we don't know, we can't we don't know one

621
00:35:52,840 --> 00:35:54,799
Speaker 3: hundred percent that this is a homicide because they didn't

622
00:35:54,800 --> 00:35:59,280
Speaker 3: put it as the manner of death. However, and listen,

623
00:35:59,360 --> 00:36:03,719
Speaker 3: like every the time homicide detectives are called, it's not

624
00:36:03,920 --> 00:36:07,279
Speaker 3: always a homicide. It's just something is suspicious and it

625
00:36:07,360 --> 00:36:09,640
Speaker 3: might be a homicide, right Yeah.

626
00:36:09,360 --> 00:36:09,520
Speaker 1: But.

627
00:36:11,000 --> 00:36:13,439
Speaker 3: The fact that they went to the house and were

628
00:36:13,480 --> 00:36:17,760
Speaker 3: specifically looking for blood evidence and specifically looking in drains

629
00:36:17,800 --> 00:36:20,520
Speaker 3: and things like that leads me to believe that at

630
00:36:20,560 --> 00:36:24,680
Speaker 3: autopsy they saw something that said she would have bled

631
00:36:24,960 --> 00:36:29,600
Speaker 3: a lot, and we need to find where she was killed. Yea,

632
00:36:29,600 --> 00:36:31,520
Speaker 3: because I mean, why else would they be looking, Like

633
00:36:31,880 --> 00:36:36,440
Speaker 3: let's say she was manually strangled, Right, they wouldn't be

634
00:36:36,440 --> 00:36:39,440
Speaker 3: looking for blood because he squeezed her neck, And why

635
00:36:39,480 --> 00:36:40,720
Speaker 3: would they be looking for blood?

636
00:36:41,280 --> 00:36:41,440
Speaker 2: Right?

637
00:36:41,800 --> 00:36:45,479
Speaker 1: But who killed her? Like when did she die?

638
00:36:45,560 --> 00:36:47,840
Speaker 3: Did she You're sure that he never had a break

639
00:36:48,239 --> 00:36:49,319
Speaker 3: and went home for a day.

640
00:36:49,600 --> 00:36:53,000
Speaker 1: Listen. I looked at the tour dates. Anything's possible. There

641
00:36:53,080 --> 00:36:55,560
Speaker 1: was like days where he had a day off, Like

642
00:36:55,920 --> 00:36:58,120
Speaker 1: I actually think he had a day off the day

643
00:36:58,160 --> 00:37:01,440
Speaker 1: she was found. But at that time, I believe on

644
00:37:01,560 --> 00:37:05,120
Speaker 1: like the seventh, he was had a show in Minnesota,

645
00:37:05,280 --> 00:37:07,480
Speaker 1: and then on the ninth he had a show in Wisconsin.

646
00:37:08,120 --> 00:37:10,520
Speaker 1: So like it would be a lot to fly back

647
00:37:11,480 --> 00:37:14,160
Speaker 1: for one night and go back, right, But it's possible.

648
00:37:14,480 --> 00:37:17,160
Speaker 1: But the neighbors had said that that car hadn't moved

649
00:37:17,160 --> 00:37:19,360
Speaker 1: in over a month, and that's why it got reported

650
00:37:19,360 --> 00:37:21,799
Speaker 1: as abandoned. So I would think if it's on a

651
00:37:21,840 --> 00:37:24,879
Speaker 1: busy street in the Hollywood Hills, somebody would have seen

652
00:37:24,920 --> 00:37:28,880
Speaker 1: somebody put a big, large trash bag in the trunk.

653
00:37:30,560 --> 00:37:33,120
Speaker 1: So like, yeah, yeah, that's beforehand.

654
00:37:33,760 --> 00:37:35,719
Speaker 3: I that's what. I don't know what the five day

655
00:37:35,760 --> 00:37:39,719
Speaker 3: thing is, like, I just don't I don't know. I

656
00:37:39,800 --> 00:37:42,040
Speaker 3: just don't think. I don't think so, like I just

657
00:37:42,480 --> 00:37:45,520
Speaker 3: if it was if it was outside, I'd be like yes, like,

658
00:37:46,000 --> 00:37:48,680
Speaker 3: especially like in Florida, that could happen real fast.

659
00:37:48,960 --> 00:37:51,600
Speaker 1: Don't they always have like cameras all over them too.

660
00:37:52,320 --> 00:37:54,360
Speaker 1: Aren't they gonna be able to see something or at

661
00:37:54,400 --> 00:37:56,640
Speaker 1: least see the last time. Don't they have monitors in

662
00:37:56,680 --> 00:37:58,560
Speaker 1: every single part of the car so they could see

663
00:37:58,600 --> 00:38:00,000
Speaker 1: the last time the trunk was open.

664
00:38:00,520 --> 00:38:04,120
Speaker 3: Yeah, I I'm sure we just like they're not telling

665
00:38:04,239 --> 00:38:07,560
Speaker 3: us anything. So and as soon as we're done recording

666
00:38:07,560 --> 00:38:09,279
Speaker 3: this episode, like a whole bunch of shit will come

667
00:38:09,280 --> 00:38:10,719
Speaker 3: out as as usual.

668
00:38:10,440 --> 00:38:13,239
Speaker 1: All right, now, truly, we'll cover it on the YouTube live,

669
00:38:14,719 --> 00:38:17,120
Speaker 1: so I know, right, all right? Last week, this thirty

670
00:38:17,160 --> 00:38:19,760
Speaker 1: two year old man got on the Stardust Racers roller

671
00:38:19,760 --> 00:38:21,880
Speaker 1: coaster in Universal, and when the ride was over, he

672
00:38:21,960 --> 00:38:25,319
Speaker 1: was unresponsive and later pronounced dead at the hospital. So

673
00:38:25,640 --> 00:38:28,200
Speaker 1: my first thought was a medical episode, but I was

674
00:38:28,239 --> 00:38:30,160
Speaker 1: pretty shocked by what they're saying.

675
00:38:30,520 --> 00:38:34,480
Speaker 3: So this guy, I guess this may or may not

676
00:38:34,560 --> 00:38:36,680
Speaker 3: be relevant, But this guy had some kind of a

677
00:38:36,719 --> 00:38:41,560
Speaker 3: spinal cord injury and was in a wheelchair, so but

678
00:38:41,840 --> 00:38:44,480
Speaker 3: that was allowed on the ride. They assisted him to

679
00:38:44,520 --> 00:38:46,560
Speaker 3: get him off, So I don't know if he had

680
00:38:46,600 --> 00:38:49,520
Speaker 3: trouble using his legs or like he straight up was paralyzed.

681
00:38:49,560 --> 00:38:51,040
Speaker 3: I don't know. They just said he had a spinal

682
00:38:51,080 --> 00:38:56,880
Speaker 3: cord injury, so I'm pretty certain I would say that

683
00:38:56,920 --> 00:38:59,560
Speaker 3: would be relevant if he had a spinal cord injury

684
00:38:59,600 --> 00:39:04,560
Speaker 3: and had other problems associated with that without having his

685
00:39:04,760 --> 00:39:07,520
Speaker 3: legs move, for example, like you can get ulcers and

686
00:39:07,560 --> 00:39:11,640
Speaker 3: infections and just like different things could happen and then

687
00:39:11,680 --> 00:39:16,879
Speaker 3: you could have subsequent medical issues because of that. In

688
00:39:16,920 --> 00:39:20,000
Speaker 3: this case, because his so his manner of death was

689
00:39:20,080 --> 00:39:24,120
Speaker 3: ruled accidental, so it didn't have to do with a

690
00:39:24,160 --> 00:39:29,120
Speaker 3: medical issue. And the craziest part is that the cause

691
00:39:29,160 --> 00:39:33,799
Speaker 3: of death was listed as blunt force trauma. So to me,

692
00:39:34,280 --> 00:39:37,759
Speaker 3: his spinal cord injury means nothing to this case. He

693
00:39:37,880 --> 00:39:42,120
Speaker 3: was like whipped around and hurt by something to the

694
00:39:42,120 --> 00:39:46,560
Speaker 3: point that it killed him. Like his body hit against something,

695
00:39:47,440 --> 00:39:50,759
Speaker 3: whether it was a cell phone that fell out of

696
00:39:50,760 --> 00:39:55,960
Speaker 3: someone's pocket, or against a rod hanging or someone's shoe

697
00:39:56,080 --> 00:39:58,280
Speaker 3: or what at that force going through a roller coaster,

698
00:39:58,360 --> 00:40:01,799
Speaker 3: like something hurt his body so bad that it killed him.

699
00:40:02,320 --> 00:40:04,719
Speaker 1: Okay, So this is a point I wanted to say

700
00:40:04,719 --> 00:40:08,560
Speaker 1: that Louie brought up to me. So Louie saw something

701
00:40:08,600 --> 00:40:11,960
Speaker 1: on TikTok. And of course this is not confirmed or anything,

702
00:40:12,000 --> 00:40:15,800
Speaker 1: and there's investigations that the ride were operating properly and everything.

703
00:40:16,320 --> 00:40:19,160
Speaker 1: But this is a dual launch roller coaster, so they

704
00:40:19,200 --> 00:40:22,359
Speaker 1: have two tracks, and there's two roller coasters going at

705
00:40:22,360 --> 00:40:25,520
Speaker 1: the same time, and at certain points the tracks get

706
00:40:25,640 --> 00:40:27,839
Speaker 1: kind of close to each other where they like will

707
00:40:27,880 --> 00:40:31,000
Speaker 1: dip off, you know what I'm saying. So I watched

708
00:40:31,000 --> 00:40:34,040
Speaker 1: a point of view video of the roller coaster, and

709
00:40:34,080 --> 00:40:36,880
Speaker 1: there are points where the cars come pretty close to

710
00:40:36,880 --> 00:40:38,920
Speaker 1: one another. And Louie had said he saw something on

711
00:40:38,960 --> 00:40:42,200
Speaker 1: TikTok that possibly the guy could have gotten hit if

712
00:40:42,200 --> 00:40:46,680
Speaker 1: somebody's arms were up and the roller coasters went over,

713
00:40:46,800 --> 00:40:48,319
Speaker 1: depending on how tall he was.

714
00:40:48,840 --> 00:40:51,600
Speaker 3: Yeah, and they'll be able to figure that out because

715
00:40:51,600 --> 00:40:55,080
Speaker 3: there's going I mean, god, I just keep thinking, like

716
00:40:55,160 --> 00:40:58,560
Speaker 3: what because if does it have the over shoulder harness.

717
00:40:59,560 --> 00:41:03,080
Speaker 3: I'm not sure because it probably does. If it's like

718
00:41:03,440 --> 00:41:04,719
Speaker 3: a roller coaster like.

719
00:41:04,640 --> 00:41:08,680
Speaker 1: That, I would think it does because it turns a lot.

720
00:41:08,800 --> 00:41:11,120
Speaker 1: I could say what you're gonna say, and I'll look

721
00:41:11,120 --> 00:41:11,319
Speaker 1: it up.

722
00:41:11,520 --> 00:41:15,120
Speaker 3: Yeah, because I'm just curious because really, when you're talking

723
00:41:15,160 --> 00:41:19,440
Speaker 3: about dying from blunt force trauma, right, it's not because

724
00:41:19,480 --> 00:41:22,520
Speaker 3: you got hit in the leg unless it was to

725
00:41:22,560 --> 00:41:27,279
Speaker 3: the point that it amputated. You're like it like he

726
00:41:27,320 --> 00:41:29,080
Speaker 3: got hit in the head or he got hit in

727
00:41:29,120 --> 00:41:29,959
Speaker 3: the chest.

728
00:41:30,880 --> 00:41:32,160
Speaker 1: Yes to harness.

729
00:41:32,400 --> 00:41:36,319
Speaker 3: Okay, so there's a harness. Harness, there's not no just

730
00:41:36,400 --> 00:41:39,000
Speaker 3: a bar. But like, let me say, you can show

731
00:41:39,040 --> 00:41:39,839
Speaker 3: me a picture of it.

732
00:41:40,280 --> 00:41:40,799
Speaker 1: Hold on it.

733
00:41:40,719 --> 00:41:43,280
Speaker 3: It goes like it's like a lap bar. His chest

734
00:41:43,320 --> 00:41:48,080
Speaker 3: is exposed. Yes, Okay, so this sounds like the two

735
00:41:48,480 --> 00:41:53,839
Speaker 3: side by side. Yeah, Like I think it was either

736
00:41:53,840 --> 00:41:59,480
Speaker 3: an unsecure object or or just proximity somehow. I mean,

737
00:42:00,400 --> 00:42:02,320
Speaker 3: I can't imagine that that's the case because they'd be

738
00:42:02,400 --> 00:42:04,759
Speaker 3: having problems all over and unless there was like a

739
00:42:04,840 --> 00:42:09,359
Speaker 3: freakishly tall person on there that had legs that were like,

740
00:42:10,120 --> 00:42:12,319
Speaker 3: you know, like a seven foot tall person that had

741
00:42:12,360 --> 00:42:14,840
Speaker 3: extra long legs that didn't make the clearance or something.

742
00:42:15,160 --> 00:42:17,920
Speaker 1: I would think they would have cleared that in testing.

743
00:42:18,080 --> 00:42:20,520
Speaker 3: I'm like, so, I'm like so intrigued by this because

744
00:42:20,560 --> 00:42:24,200
Speaker 3: I just want to know, Like obviously, like everybody just

745
00:42:24,239 --> 00:42:26,800
Speaker 3: from the accounts I was reading online, like people knew

746
00:42:26,800 --> 00:42:29,359
Speaker 3: what was happening right away, and people were visibly like

747
00:42:29,400 --> 00:42:31,919
Speaker 3: freaking out about it. So I wonder if they take

748
00:42:32,000 --> 00:42:34,520
Speaker 3: every single person off the ride and like interview them

749
00:42:34,560 --> 00:42:37,080
Speaker 3: and try to figure out what happened. I mean, this

750
00:42:37,160 --> 00:42:40,239
Speaker 3: is This is the thing though with the with like

751
00:42:40,320 --> 00:42:43,239
Speaker 3: certain parks that I've been to recently have been very

752
00:42:43,320 --> 00:42:45,880
Speaker 3: much like you have to leave your phone here, you

753
00:42:45,960 --> 00:42:49,080
Speaker 3: have to leave your glasses here. You should, Yeah, And

754
00:42:49,120 --> 00:42:51,200
Speaker 3: it sucks for a person like me because I can't

755
00:42:51,200 --> 00:42:53,239
Speaker 3: see without my glasses. So when I go on a ride,

756
00:42:53,280 --> 00:42:55,680
Speaker 3: like I literally can't see what's happening. But also I

757
00:42:55,680 --> 00:42:57,440
Speaker 3: don't want them to fly off of my face and

758
00:42:57,760 --> 00:43:01,719
Speaker 3: hit somebody and hurt them because you know, I mean,

759
00:43:01,760 --> 00:43:04,200
Speaker 3: my phone's pretty heavy, Like if I drop it on

760
00:43:04,280 --> 00:43:06,960
Speaker 3: my foot, it hurts right. Well, imagine the force of

761
00:43:07,000 --> 00:43:10,120
Speaker 3: going seventy miles an hour on a roller coaster and

762
00:43:10,160 --> 00:43:14,480
Speaker 3: it flinging at someone like, oh, totally, so something if

763
00:43:14,480 --> 00:43:16,319
Speaker 3: he didn't have the harness over his chest, that was

764
00:43:16,400 --> 00:43:19,799
Speaker 3: unprotected too, so something had to hit his chest or

765
00:43:19,840 --> 00:43:22,759
Speaker 3: his head or like I said, like, if something was

766
00:43:22,760 --> 00:43:25,800
Speaker 3: that bad that he had an amputation, he could have

767
00:43:25,920 --> 00:43:28,440
Speaker 3: led out from that from a from a limit amputation

768
00:43:28,600 --> 00:43:30,239
Speaker 3: or something. But I don't. I don't know if there

769
00:43:30,280 --> 00:43:33,640
Speaker 3: was any accounts of it being a bloody scene or well.

770
00:43:33,200 --> 00:43:37,280
Speaker 1: People reported officials were told to respond to a patient

771
00:43:37,280 --> 00:43:40,239
Speaker 1: who had a laceration and when they got there, he

772
00:43:40,360 --> 00:43:43,239
Speaker 1: wasn't breathing and CPR was already in progress, and then

773
00:43:43,280 --> 00:43:44,960
Speaker 1: he was pronounced it at the hospital later.

774
00:43:48,360 --> 00:43:50,840
Speaker 3: You know, the word laceration is like what was it

775
00:43:50,880 --> 00:43:54,000
Speaker 3: like across this frickin' neck, Like I mean exactly. The

776
00:43:54,040 --> 00:43:57,680
Speaker 3: thing is is that it have been an animal, like

777
00:43:57,719 --> 00:43:59,760
Speaker 3: a could it could have been it could have been anything,

778
00:43:59,800 --> 00:44:04,360
Speaker 3: I guess, like a beak. I don't know. I'm sure

779
00:44:04,520 --> 00:44:09,279
Speaker 3: like we'll learn more because this is obviously this is

780
00:44:09,360 --> 00:44:13,040
Speaker 3: going to go to trial, I assume, or they'll they

781
00:44:13,080 --> 00:44:15,520
Speaker 3: might just try to like settle it, but you'll get

782
00:44:15,520 --> 00:44:20,080
Speaker 3: more information from it because you know what's crazy to me,

783
00:44:20,120 --> 00:44:22,480
Speaker 3: there's probably people that are on that ride as we speak,

784
00:44:22,680 --> 00:44:25,400
Speaker 3: like people are just like, yeah, whatever, it's a newer ride.

785
00:44:25,400 --> 00:44:28,000
Speaker 3: I think it just opened earlier this year. But like

786
00:44:28,000 --> 00:44:30,840
Speaker 3: what I was getting at, if Louis on it, I

787
00:44:30,840 --> 00:44:31,239
Speaker 3: don't think.

788
00:44:31,440 --> 00:44:33,399
Speaker 1: I feel like they went this year.

789
00:44:33,520 --> 00:44:34,759
Speaker 3: I feel like you did. I don't know.

790
00:44:35,000 --> 00:44:38,719
Speaker 1: I feel I understand the point Louis made about the arms, right,

791
00:44:39,080 --> 00:44:41,560
Speaker 1: but like I feel like in today's day and age,

792
00:44:41,600 --> 00:44:43,960
Speaker 1: we're not talking about like Action Park where somebody's drawing

793
00:44:44,000 --> 00:44:45,879
Speaker 1: a ride on a napkin and they're not doing any

794
00:44:45,880 --> 00:44:49,160
Speaker 1: engineering testing or anything like. I would assume that point

795
00:44:49,160 --> 00:44:51,840
Speaker 1: would have been brought up in the many tests before

796
00:44:51,880 --> 00:44:53,799
Speaker 1: the ride was developed, and they would have seen it

797
00:44:53,840 --> 00:44:54,400
Speaker 1: in testing.

798
00:44:55,480 --> 00:44:57,640
Speaker 3: Yeah, and there, I'm telling you there would have been

799
00:44:57,640 --> 00:45:03,360
Speaker 3: a problem already. It's just so he had a visible laceration.

800
00:45:03,480 --> 00:45:08,200
Speaker 3: That's interesting. Yeah, I just like I hate that. I

801
00:45:08,239 --> 00:45:17,799
Speaker 3: don't know, drives me nuts.

802
00:45:19,520 --> 00:45:22,360
Speaker 1: This episode is brought to you by the Gross Room guys.

803
00:45:22,440 --> 00:45:25,200
Speaker 3: Last week, Celebrity Death di Section was on Charlie Kirk

804
00:45:25,239 --> 00:45:28,240
Speaker 3: and we still haven't really added anything to that because

805
00:45:28,880 --> 00:45:31,160
Speaker 3: they just came out with a little bit of information,

806
00:45:31,400 --> 00:45:34,520
Speaker 3: but I want to make sure it's from a more

807
00:45:35,400 --> 00:45:38,960
Speaker 3: substantial source before we add to that post. But we also,

808
00:45:39,160 --> 00:45:42,120
Speaker 3: as Maria was saying, we just did a high profile

809
00:45:42,200 --> 00:45:48,239
Speaker 3: death disseection on Celeste Revis and her association with this

810
00:45:48,360 --> 00:45:52,200
Speaker 3: singer David, and we really go into all of the

811
00:45:52,239 --> 00:45:55,040
Speaker 3: different things that they look at at autopsy, like what

812
00:45:55,120 --> 00:45:57,440
Speaker 3: this body might look like when it comes out of

813
00:45:57,480 --> 00:46:01,000
Speaker 3: the trunk, and how they look at it in the

814
00:46:01,040 --> 00:46:05,000
Speaker 3: autopsy room. We external exam imaging that will do what

815
00:46:05,120 --> 00:46:07,040
Speaker 3: bones they're looking at and things like that. So it's

816
00:46:07,080 --> 00:46:08,759
Speaker 3: really interesting. So check that out.

817
00:46:09,160 --> 00:46:11,640
Speaker 1: Head over to the grossroom dot com now to sign up.

818
00:46:13,440 --> 00:46:16,120
Speaker 1: All right, So a teacher has been put on administrative

819
00:46:16,200 --> 00:46:18,600
Speaker 1: leave after the school found out she was a surrogate

820
00:46:18,680 --> 00:46:19,960
Speaker 1: for another family.

821
00:46:20,920 --> 00:46:23,640
Speaker 3: All right, so what's the big part of this story.

822
00:46:23,719 --> 00:46:25,200
Speaker 3: She works at a Catholic school.

823
00:46:25,680 --> 00:46:28,600
Speaker 1: Yeah, so she works at a Catholic school, and so

824
00:46:28,880 --> 00:46:33,920
Speaker 1: apparently Catholics consider sarrogacy to be unethical. And I thought

825
00:46:33,960 --> 00:46:37,400
Speaker 1: in this source we watched today about the story that

826
00:46:37,600 --> 00:46:39,920
Speaker 1: a parent at the school made a really good point

827
00:46:39,960 --> 00:46:42,920
Speaker 1: that if you're going to put a teacher on leave

828
00:46:42,960 --> 00:46:45,480
Speaker 1: because you don't believe in sarrogacy. You also should not

829
00:46:45,560 --> 00:46:49,040
Speaker 1: accept tuition from families that have used surrogates or gone

830
00:46:49,080 --> 00:46:49,880
Speaker 1: through IVF.

831
00:46:51,560 --> 00:46:54,520
Speaker 3: Wasn't Mary kind of like a surrogant? Wasn't she like

832
00:46:54,840 --> 00:46:57,759
Speaker 3: holding a baby that wasn't kind of really hers the

833
00:46:57,880 --> 00:46:58,760
Speaker 3: Virgin Mary?

834
00:46:59,239 --> 00:47:04,239
Speaker 4: Yes, you mean it's she just didn't have a spontaneous

835
00:47:04,760 --> 00:47:07,360
Speaker 4: baby that's not scientifically.

836
00:47:06,920 --> 00:47:11,080
Speaker 3: But like what but wasn't it like I sound like

837
00:47:11,080 --> 00:47:14,759
Speaker 3: such a bad Catholic. Wasn't it like this this like

838
00:47:15,400 --> 00:47:18,560
Speaker 3: this being inside her? Like I did they really?

839
00:47:18,640 --> 00:47:19,319
Speaker 1: Like? What?

840
00:47:19,600 --> 00:47:22,200
Speaker 3: Was she like his mom? Or was she just like

841
00:47:22,239 --> 00:47:24,880
Speaker 3: a carrier of like of Jesus.

842
00:47:25,760 --> 00:47:29,120
Speaker 1: So you're saying that Mary is God's surrogate?

843
00:47:32,719 --> 00:47:38,000
Speaker 2: Yeah, I mean if you want to pose it that way,

844
00:47:38,200 --> 00:47:42,200
Speaker 2: that's oh my god, all of these people are going

845
00:47:42,280 --> 00:47:43,200
Speaker 2: to attack me on this.

846
00:47:43,320 --> 00:47:46,080
Speaker 3: I listen, I didn't go to Catholic school really, and

847
00:47:46,200 --> 00:47:49,360
Speaker 3: I like went to CCD and I didn't really pay attention.

848
00:47:49,400 --> 00:47:52,319
Speaker 1: So sorry, but we're Catholic. Sorry if we're offending you,

849
00:47:52,400 --> 00:47:54,680
Speaker 1: but this is bullshit. I understand if they don't want

850
00:47:54,680 --> 00:47:57,560
Speaker 1: to cover her maternityly for a child that's not her own,

851
00:47:58,200 --> 00:48:01,400
Speaker 1: but like to say, like you don't believe insarrogacy in

852
00:48:01,480 --> 00:48:03,719
Speaker 1: this modern age is so ridiculous.

853
00:48:04,880 --> 00:48:08,000
Speaker 3: Well, it goes with it goes with the religion. Let

854
00:48:08,000 --> 00:48:10,400
Speaker 3: me tell you a story, guys, this is a good story.

855
00:48:10,840 --> 00:48:13,960
Speaker 3: So I went to Catholic school in ninth grade when

856
00:48:13,960 --> 00:48:17,200
Speaker 3: I got pregnant with Maria, and they told me that

857
00:48:17,280 --> 00:48:20,520
Speaker 3: I wasn't allowed to be at the school because I

858
00:48:20,640 --> 00:48:23,360
Speaker 3: was pregnant and I couldn't be wearing a uniform pregnant

859
00:48:23,400 --> 00:48:25,640
Speaker 3: at the school. But they also told me if I

860
00:48:25,680 --> 00:48:28,360
Speaker 3: got an abortion that I would get kicked out. So

861
00:48:28,480 --> 00:48:32,040
Speaker 3: there you go. That's the guess Catholicism wrapped up for you.

862
00:48:32,800 --> 00:48:34,920
Speaker 1: It's just so hypocritical.

863
00:48:36,400 --> 00:48:38,760
Speaker 3: Yeah, that's why a lot of people have a problem

864
00:48:38,800 --> 00:48:39,120
Speaker 3: with it.

865
00:48:39,400 --> 00:48:41,560
Speaker 1: So this happened in Vineland, New Jersey, which is not

866
00:48:41,719 --> 00:48:43,640
Speaker 1: very far from where we live. I'm gonna call them out,

867
00:48:43,640 --> 00:48:47,759
Speaker 1: Saint Mary's. Everybody look them up, Saint Mary's. So this

868
00:48:47,840 --> 00:48:50,640
Speaker 1: woman that's the teacher there said she was.

869
00:48:51,239 --> 00:48:54,840
Speaker 3: Carrying a fucking baby for somebody. That's like that's like

870
00:48:55,080 --> 00:48:59,000
Speaker 3: a that's like a they're like a special saint. Yes,

871
00:49:00,440 --> 00:49:03,880
Speaker 3: like God, this is this is why I can't do it.

872
00:49:03,920 --> 00:49:04,640
Speaker 3: I can't do it.

873
00:49:04,760 --> 00:49:06,920
Speaker 1: I can't do it. Either Sorry if people are offended

874
00:49:06,920 --> 00:49:08,279
Speaker 1: by this, but if you don't think this is the

875
00:49:08,280 --> 00:49:10,880
Speaker 1: most ridiculous thing you've ever heard, you need to reevaluate

876
00:49:10,960 --> 00:49:14,880
Speaker 1: your values. So this lady is saying the teacher that

877
00:49:15,000 --> 00:49:17,600
Speaker 1: she was a surrogate for I guess the same family

878
00:49:17,719 --> 00:49:20,000
Speaker 1: when she worked at another Catholic school in Philly, and

879
00:49:20,000 --> 00:49:22,240
Speaker 1: they had no problem with it, as they shouldn't because

880
00:49:22,320 --> 00:49:24,000
Speaker 1: don't they preach acceptance.

881
00:49:25,320 --> 00:49:30,880
Speaker 3: So we're just like family bringing life into the world. Yes,

882
00:49:31,239 --> 00:49:34,880
Speaker 3: like some people just like have their anatomy broken and

883
00:49:34,920 --> 00:49:37,200
Speaker 3: can't do it and need help anyway.

884
00:49:37,719 --> 00:49:41,040
Speaker 1: Yes, so there's no problem there. So she's now carrying

885
00:49:41,080 --> 00:49:44,799
Speaker 1: the sibling of the first child she carried, and she's

886
00:49:44,800 --> 00:49:48,279
Speaker 1: twenty five weeks pregnant, and she told the principle about it,

887
00:49:48,360 --> 00:49:50,200
Speaker 1: and that's when they decided to put her on paid

888
00:49:50,280 --> 00:49:54,640
Speaker 1: administrative leave while they investigate the situation. What's to investigate?

889
00:49:55,000 --> 00:50:00,439
Speaker 3: Like you, we might have talked about a story. Why ago,

890
00:50:00,800 --> 00:50:04,240
Speaker 3: wasn't there something that happened that somebody got fired because

891
00:50:04,239 --> 00:50:07,000
Speaker 3: of from a Catholic school because they were like taking

892
00:50:07,040 --> 00:50:09,600
Speaker 3: birth control or there was something with the birth control.

893
00:50:10,560 --> 00:50:12,600
Speaker 1: Maybe it was the.

894
00:50:12,680 --> 00:50:16,880
Speaker 3: Insurance, the health insurance wouldn't cover birth control. I don't know,

895
00:50:16,920 --> 00:50:17,880
Speaker 3: it's something to do.

896
00:50:18,080 --> 00:50:19,360
Speaker 1: Yeah, it was something like that.

897
00:50:20,360 --> 00:50:24,359
Speaker 3: Yeah, I mean it is, it is. Everybody knows what

898
00:50:24,400 --> 00:50:24,759
Speaker 3: it is.

899
00:50:24,800 --> 00:50:24,920
Speaker 1: Like.

900
00:50:24,960 --> 00:50:28,640
Speaker 3: It just it's just it's messed up because I think

901
00:50:28,640 --> 00:50:32,880
Speaker 3: that most normal people are like, Okay, she's clearly doing

902
00:50:32,920 --> 00:50:39,839
Speaker 3: a good deed and this is just like you, maybe

903
00:50:39,920 --> 00:50:42,080
Speaker 3: they don't want to you.

904
00:50:42,000 --> 00:50:44,880
Speaker 1: Would think carrying a child for a family that can't

905
00:50:44,880 --> 00:50:47,400
Speaker 1: do it themselves, you would be considered a good Christian,

906
00:50:48,640 --> 00:50:52,239
Speaker 1: not banished from your school that you work at. And

907
00:50:52,320 --> 00:50:54,080
Speaker 1: what does her being a surrogate have to do with

908
00:50:54,080 --> 00:50:57,200
Speaker 1: her teaching kindergardeners? She's a kindergarten teacher.

909
00:50:57,760 --> 00:51:01,640
Speaker 3: Do you think that maybe they're like, you know, because

910
00:51:01,680 --> 00:51:05,000
Speaker 3: they like to put on this front that everything's okay,

911
00:51:05,120 --> 00:51:10,000
Speaker 3: Like she she's not going home till she's not gonna

912
00:51:10,000 --> 00:51:12,360
Speaker 3: have that baby after she has it, and she's like

913
00:51:13,000 --> 00:51:16,959
Speaker 3: she might not be married whatever. Like do you think

914
00:51:17,000 --> 00:51:20,000
Speaker 3: that that's it that they care about the impression that

915
00:51:20,040 --> 00:51:21,680
Speaker 3: it's putting on the kids. I mean, I don't know.

916
00:51:21,719 --> 00:51:24,799
Speaker 3: I think that's a good lesson to be like, yeah,

917
00:51:25,160 --> 00:51:28,880
Speaker 3: like it's like in Fuller House when Kimmy Gibbler is

918
00:51:28,920 --> 00:51:32,319
Speaker 3: carrying the baby for Stephanie, like because she couldn't have

919
00:51:32,400 --> 00:51:35,359
Speaker 3: a baby, Like you're you're like awesome for doing that.

920
00:51:35,360 --> 00:51:37,320
Speaker 3: That's like a good thing to show people.

921
00:51:37,960 --> 00:51:40,319
Speaker 1: Well, that's what I'm trying to say, Like this, and

922
00:51:40,400 --> 00:51:42,440
Speaker 1: this is my problem with the church. I mean with

923
00:51:42,560 --> 00:51:47,319
Speaker 1: our exit, with our situation specifically, right, it's like you're

924
00:51:47,360 --> 00:51:49,440
Speaker 1: gonna get kicked out. But then again, they let my

925
00:51:49,520 --> 00:51:52,439
Speaker 1: dad stay fifty percent responsible for the friend.

926
00:51:52,600 --> 00:51:55,600
Speaker 3: Yeah, well because he played football, so that was important

927
00:51:55,640 --> 00:51:58,879
Speaker 3: to the school. I have another actualism with that too,

928
00:51:59,040 --> 00:52:03,440
Speaker 3: like when so you know, when you're Catholic, you're supposed

929
00:52:03,440 --> 00:52:07,440
Speaker 3: to baptize your child, which they encourage. But they said,

930
00:52:08,000 --> 00:52:11,560
Speaker 3: so you have to baptize this child, but you can't

931
00:52:11,600 --> 00:52:14,120
Speaker 3: do it where we normally do it because of your situation.

932
00:52:14,280 --> 00:52:15,560
Speaker 1: So I had to dis a banstard.

933
00:52:15,680 --> 00:52:18,319
Speaker 3: So yes, so you had to get baptized in the

934
00:52:18,360 --> 00:52:23,080
Speaker 3: rectory with like two nuns and like nobody could see it.

935
00:52:23,160 --> 00:52:25,319
Speaker 3: We were like snuck in the back door to do it.

936
00:52:25,880 --> 00:52:28,840
Speaker 3: Well that's when momm was like I'm done here.

937
00:52:29,080 --> 00:52:32,799
Speaker 1: Well exactly, and like let me tell you, any trial

938
00:52:32,920 --> 00:52:35,320
Speaker 1: coming out of me is not going through that system

939
00:52:35,400 --> 00:52:39,359
Speaker 1: because they have treated us horribly. And I think this

940
00:52:39,440 --> 00:52:40,560
Speaker 1: is another example.

941
00:52:40,719 --> 00:52:45,240
Speaker 3: It's just weird because I think to say a blanket

942
00:52:45,280 --> 00:52:47,919
Speaker 3: statement of that. We were just talking about this with

943
00:52:48,000 --> 00:52:50,400
Speaker 3: Paul when we did the episode where he just traveled

944
00:52:50,400 --> 00:52:54,520
Speaker 3: to Indonesia and he said those people were Catholics. It's

945
00:52:54,600 --> 00:52:57,520
Speaker 3: just like it varies from place to place. Like I

946
00:52:57,560 --> 00:53:02,880
Speaker 3: know Catholic organizations that are like very welcoming of like

947
00:53:03,000 --> 00:53:06,640
Speaker 3: gay couples and things like that. It's just like they're

948
00:53:06,840 --> 00:53:09,799
Speaker 3: way more open minded to like what's really going on

949
00:53:09,880 --> 00:53:13,279
Speaker 3: in the world in twenty twenty five, whereas like this

950
00:53:13,440 --> 00:53:16,480
Speaker 3: particular one is just not so well.

951
00:53:16,560 --> 00:53:18,360
Speaker 1: This this is my thing, Like I don't have a

952
00:53:18,400 --> 00:53:21,239
Speaker 1: problem with religion. I have a problem with this in

953
00:53:21,280 --> 00:53:24,359
Speaker 1: particular because they're constantly preaching this one way of life,

954
00:53:24,680 --> 00:53:28,879
Speaker 1: yet they're never living it. They're actually like the most

955
00:53:28,960 --> 00:53:33,000
Speaker 1: judgmental people most of the time truth. And that's why I.

956
00:53:32,960 --> 00:53:36,399
Speaker 3: Can't get yeah, like not yeah, I mean, I don't

957
00:53:36,400 --> 00:53:39,920
Speaker 3: want to say most I know. I know a few

958
00:53:40,239 --> 00:53:46,320
Speaker 3: religious people that are like very like selfless and kind

959
00:53:46,560 --> 00:53:50,000
Speaker 3: and and like of course they're living like I have

960
00:53:50,160 --> 00:53:53,200
Speaker 3: like like really really good friends that are like that,

961
00:53:53,880 --> 00:53:59,319
Speaker 3: and I always am kind of like I respect that

962
00:53:59,400 --> 00:54:02,239
Speaker 3: they they're very they're just like good people. They're like

963
00:54:02,320 --> 00:54:05,480
Speaker 3: here to help and to do good things. And then

964
00:54:05,600 --> 00:54:08,080
Speaker 3: I know some others that I'm just like, yeah, you

965
00:54:08,160 --> 00:54:11,480
Speaker 3: going to church is not helping. How shitty you are?

966
00:54:11,560 --> 00:54:11,719
Speaker 3: You know?

967
00:54:12,360 --> 00:54:14,520
Speaker 1: If anything, it makes them where So like yeah, and

968
00:54:14,520 --> 00:54:16,839
Speaker 1: I agree with you, Like of course there's like there's

969
00:54:16,920 --> 00:54:19,440
Speaker 1: people that do live by it and are really good people,

970
00:54:19,719 --> 00:54:21,800
Speaker 1: and then there's people that use it as an excuse

971
00:54:21,880 --> 00:54:24,319
Speaker 1: to be a complete asshole. And I just think like

972
00:54:24,760 --> 00:54:28,000
Speaker 1: this is a situation of like I would be more

973
00:54:28,080 --> 00:54:30,160
Speaker 1: understanding if they were just like, since this isn't going

974
00:54:30,239 --> 00:54:31,719
Speaker 1: to be your baby, we're not going to cover your

975
00:54:31,760 --> 00:54:33,920
Speaker 1: maternity leave. But like that doesn't even seem to be

976
00:54:34,000 --> 00:54:36,640
Speaker 1: the case in this story. Like I just have a

977
00:54:36,680 --> 00:54:37,680
Speaker 1: moral issue with it.

978
00:54:38,200 --> 00:54:42,439
Speaker 3: Yeah, Like I mean this is the thing, Like as

979
00:54:42,440 --> 00:54:44,640
Speaker 3: far as I'm concerned, this is the law that I

980
00:54:44,719 --> 00:54:48,040
Speaker 3: always thought of, at least working in New Jersey anyway,

981
00:54:48,160 --> 00:54:52,120
Speaker 3: Like you don't legally have to tell your employer that

982
00:54:52,160 --> 00:54:55,880
Speaker 3: you're pregnant. Like cause you know, my friend Andrew I

983
00:54:55,920 --> 00:54:59,080
Speaker 3: was talking about earlier, like she she couldn't get she

984
00:54:59,120 --> 00:55:03,160
Speaker 3: was having problems right when she finally got pregnant with

985
00:55:03,239 --> 00:55:07,720
Speaker 3: her first baby. She didn't tell anybody at work until

986
00:55:07,800 --> 00:55:11,319
Speaker 3: she was like twenty six weeks I think twenty four

987
00:55:11,400 --> 00:55:14,279
Speaker 3: or twenty six weeks if she was. She and she's

988
00:55:14,360 --> 00:55:18,160
Speaker 3: like a little tiny nugget, so she was visibly pregnant

989
00:55:18,760 --> 00:55:22,040
Speaker 3: and like she and like nobody could ask her. Legally,

990
00:55:22,120 --> 00:55:24,480
Speaker 3: you can't say like are you. You can't do that,

991
00:55:24,960 --> 00:55:26,759
Speaker 3: So like she should have just went to school and

992
00:55:26,800 --> 00:55:28,640
Speaker 3: taught and just been like whatever.

993
00:55:29,280 --> 00:55:32,040
Speaker 1: Well, I think most people want to think like by

994
00:55:32,160 --> 00:55:33,920
Speaker 1: saying it, it's not going to be an issue.

995
00:55:34,000 --> 00:55:35,840
Speaker 3: Yeah, and like you want to prepare them for the

996
00:55:35,920 --> 00:55:37,719
Speaker 3: leave and everything like that, But I don't think you

997
00:55:37,800 --> 00:55:40,640
Speaker 3: have to legally tell your employer anyway. So, like, I mean,

998
00:55:40,680 --> 00:55:42,440
Speaker 3: she was trying to just do the right thing, but

999
00:55:43,880 --> 00:55:45,279
Speaker 3: clearly that backfired.

1000
00:55:45,600 --> 00:55:47,600
Speaker 1: And I really agree with the parent that said they

1001
00:55:47,640 --> 00:55:50,520
Speaker 1: should not accept the tuition if they morally think it's wrong,

1002
00:55:50,560 --> 00:55:52,520
Speaker 1: then you should also not allow the families to go there,

1003
00:55:52,520 --> 00:55:55,680
Speaker 1: and you shouldn't take their money, Yeah, exactly, because it's

1004
00:55:55,760 --> 00:55:58,080
Speaker 1: very Again, you'll take the money, but you won't have

1005
00:55:58,200 --> 00:56:01,279
Speaker 1: a kindergarten teacher at work who's doing a very nice

1006
00:56:01,320 --> 00:56:04,040
Speaker 1: thing for a family and need so like, God.

1007
00:56:04,239 --> 00:56:07,920
Speaker 4: My blood pressure is so Oh, we could tell, Okay,

1008
00:56:07,960 --> 00:56:10,879
Speaker 4: we could tell. So last week the story came up

1009
00:56:12,200 --> 00:56:14,839
Speaker 4: a mother and daughter who were pregnant by the same man,

1010
00:56:14,920 --> 00:56:16,960
Speaker 4: and I was pretty sure we covered it, but I

1011
00:56:17,000 --> 00:56:19,080
Speaker 4: really looked through all the backlog on the episodes.

1012
00:56:19,760 --> 00:56:21,359
Speaker 3: I don't remember talking about this.

1013
00:56:21,760 --> 00:56:25,120
Speaker 1: We couldnot find it. I could not find it anywhere.

1014
00:56:25,719 --> 00:56:28,799
Speaker 1: So this story is a thing. The mother, who was

1015
00:56:28,840 --> 00:56:31,399
Speaker 1: in her forties, started a relationship with the younger guy.

1016
00:56:31,480 --> 00:56:34,200
Speaker 1: They moved in together, then her twenty two year old

1017
00:56:34,280 --> 00:56:36,680
Speaker 1: daughter moves in with them and also starts a relationship

1018
00:56:36,680 --> 00:56:39,040
Speaker 1: with the man in the house. So then they find

1019
00:56:39,080 --> 00:56:41,719
Speaker 1: out they're both pregnant by him, and they're do only

1020
00:56:41,800 --> 00:56:44,680
Speaker 1: one week apart from each other. And you would think

1021
00:56:44,719 --> 00:56:47,120
Speaker 1: most people would be highly disturbed by this, but they

1022
00:56:47,120 --> 00:56:48,600
Speaker 1: are pretty stoked about it.

1023
00:56:49,120 --> 00:56:51,000
Speaker 3: Do you think this is real? Because I don't.

1024
00:56:51,440 --> 00:56:53,920
Speaker 1: I actually don't. Because they're both on only fans, I

1025
00:56:54,000 --> 00:56:57,040
Speaker 1: got them a lot of attention, and this other information

1026
00:56:57,160 --> 00:56:59,400
Speaker 1: came out that they apparently all still live in the

1027
00:56:59,400 --> 00:57:02,680
Speaker 1: same house, share a bed, and that's incestuous, and I

1028
00:57:02,719 --> 00:57:04,360
Speaker 1: don't believe that it's really happening.

1029
00:57:04,800 --> 00:57:06,440
Speaker 3: Oh, I think that that could happen.

1030
00:57:06,800 --> 00:57:09,400
Speaker 1: No, that could happen, but it happens in case it happens,

1031
00:57:09,560 --> 00:57:14,680
Speaker 1: because this story's from like February and they were looking,

1032
00:57:15,040 --> 00:57:17,400
Speaker 1: you know, pretty pregnant in the pictures and there's been

1033
00:57:17,440 --> 00:57:19,880
Speaker 1: no information if these children were ever born and where

1034
00:57:19,880 --> 00:57:20,200
Speaker 1: they are.

1035
00:57:21,440 --> 00:57:24,040
Speaker 3: Do you think it, like, if it is real, it

1036
00:57:24,080 --> 00:57:27,520
Speaker 3: could just be like holy shit, like this is actually

1037
00:57:27,720 --> 00:57:32,840
Speaker 3: really terrible for everyone involved. Maybe it just like clicked

1038
00:57:33,680 --> 00:57:38,280
Speaker 3: like oh yeah, my my, I can't even this kind

1039
00:57:38,280 --> 00:57:41,880
Speaker 3: of shit confuses me so much. So, like her daughter

1040
00:57:42,520 --> 00:57:46,520
Speaker 3: is having a baby, so that's her grandchild, and her

1041
00:57:46,560 --> 00:57:49,480
Speaker 3: mom's having a baby, so that's her sibling.

1042
00:57:51,040 --> 00:57:54,000
Speaker 1: Yeah, so her mom's baby is gonna be her sibling,

1043
00:57:54,160 --> 00:57:56,840
Speaker 1: and then her daughter's baby's gonna be her grandchild but

1044
00:57:57,000 --> 00:57:59,320
Speaker 1: also her kid's half sibling.

1045
00:58:00,160 --> 00:58:04,760
Speaker 3: Yeah, like it's it's so weird. But I like, listen,

1046
00:58:04,880 --> 00:58:07,040
Speaker 3: I didn't even know who this person was until I

1047
00:58:07,120 --> 00:58:09,600
Speaker 3: looked at their names, and one of them is Jade

1048
00:58:09,800 --> 00:58:12,720
Speaker 3: teen and the other one is Danny Swings. Well I'm

1049
00:58:12,760 --> 00:58:15,000
Speaker 3: just like the yeah, Like I was just like whose

1050
00:58:15,080 --> 00:58:18,000
Speaker 3: names like whatever, so and then I looked it up

1051
00:58:18,040 --> 00:58:20,280
Speaker 3: and I was like, yeah, pretty typical of what I

1052
00:58:20,360 --> 00:58:23,920
Speaker 3: expected to see. So it's like to me, it's just

1053
00:58:23,960 --> 00:58:29,040
Speaker 3: like it. I hope, listen, I hope for society and

1054
00:58:29,120 --> 00:58:31,439
Speaker 3: for just everything that this is made up.

1055
00:58:32,440 --> 00:58:35,000
Speaker 1: Well, we were talking, we were joking like what if

1056
00:58:35,000 --> 00:58:37,080
Speaker 1: we got right in at the same time, and a

1057
00:58:37,160 --> 00:58:40,600
Speaker 1: couple of listeners set me stories that that's like really

1058
00:58:40,640 --> 00:58:45,320
Speaker 1: common in Utah. I guess because Mormons have children very young,

1059
00:58:45,520 --> 00:58:49,160
Speaker 1: and they often have a lot of kids, so sometimes

1060
00:58:49,160 --> 00:58:51,520
Speaker 1: it will overlap where like the oldest daughter and the

1061
00:58:51,560 --> 00:58:52,800
Speaker 1: mom are having kids.

1062
00:58:52,960 --> 00:58:55,400
Speaker 3: I can see that, like if you have a kid

1063
00:58:55,400 --> 00:58:59,160
Speaker 3: when you're nineteen or twenty, in theory, you could have

1064
00:58:59,360 --> 00:59:01,760
Speaker 3: a kid up in so you're forty something like, it's

1065
00:59:01,800 --> 00:59:02,760
Speaker 3: totally possible.

1066
00:59:03,480 --> 00:59:05,280
Speaker 1: Yeah, I mean, I don't think that's going to be

1067
00:59:05,360 --> 00:59:06,360
Speaker 1: happening in our case.

1068
00:59:06,600 --> 00:59:12,000
Speaker 3: But it's not. I'm not having markets. It's pellets. I'm yeah,

1069
00:59:12,160 --> 00:59:15,880
Speaker 3: the pellets will prevent me hopefully, well not really because

1070
00:59:16,120 --> 00:59:18,640
Speaker 3: they're actually going to they would cause a problem, but

1071
00:59:18,840 --> 00:59:21,720
Speaker 3: I have taken care of that all right.

1072
00:59:21,800 --> 00:59:25,000
Speaker 1: Last story a woman issuing the hospital she worked at

1073
00:59:25,080 --> 00:59:27,760
Speaker 1: after they fired her for reporting that two newborns were

1074
00:59:27,800 --> 00:59:30,360
Speaker 1: given to the wrong mothers and breastfed dude.

1075
00:59:30,640 --> 00:59:36,840
Speaker 3: This hospital is you've heard me say before, horrible experience

1076
00:59:37,000 --> 00:59:41,040
Speaker 3: both times I gave birth. Well guess what it was there.

1077
00:59:42,880 --> 00:59:46,120
Speaker 1: Well, I'm not really surprised because I do know a

1078
00:59:46,160 --> 00:59:48,560
Speaker 1: couple of people that had great experiences there, but I

1079
00:59:48,600 --> 00:59:51,560
Speaker 1: feel like I know more people that had bad experiences there.

1080
00:59:52,360 --> 00:59:56,040
Speaker 1: And this incident happened in the summer. So let me

1081
00:59:56,080 --> 00:59:58,720
Speaker 1: go over what happened. This nurse is saying that she

1082
00:59:58,880 --> 01:00:01,160
Speaker 1: arrived to her seven as shift and the night nurse

1083
01:00:01,200 --> 01:00:03,240
Speaker 1: told her that two babies were brought to the nursery

1084
01:00:03,280 --> 01:00:06,360
Speaker 1: overnight by request, but had since been returned to the families.

1085
01:00:07,040 --> 01:00:10,280
Speaker 1: So the morning nurse starts doing her rounds, goes into

1086
01:00:10,320 --> 01:00:13,040
Speaker 1: the first room, check the barcode on the bassinet and

1087
01:00:13,120 --> 01:00:16,520
Speaker 1: the mother, but never actually actually checked the babies bracelet

1088
01:00:16,560 --> 01:00:19,840
Speaker 1: because she was breastfeeding her about to breastfeed. Same thing

1089
01:00:19,880 --> 01:00:22,240
Speaker 1: happened in the next room. She goes to a couple

1090
01:00:22,280 --> 01:00:24,640
Speaker 1: other rooms, and then she goes back to the first

1091
01:00:24,640 --> 01:00:28,320
Speaker 1: patient getting ready to discharge her, and the mom is

1092
01:00:28,320 --> 01:00:31,640
Speaker 1: distressed because her the baby that she just breastfeeds bracelet

1093
01:00:31,760 --> 01:00:35,720
Speaker 1: does not match her child's name, and then they realized

1094
01:00:35,720 --> 01:00:36,840
Speaker 1: that there was a mix up.

1095
01:00:38,800 --> 01:00:42,600
Speaker 3: Dude, this is a really big deal, like really really

1096
01:00:42,600 --> 01:00:48,439
Speaker 3: big deal, and it honestly, I feel like there's such

1097
01:00:48,480 --> 01:00:54,440
Speaker 3: safeguards in place to make this impossible to happen. And God, like,

1098
01:00:54,480 --> 01:00:57,560
Speaker 3: if you've delivered with these people working there, wouldn't you

1099
01:00:57,680 --> 01:01:01,440
Speaker 3: be scared that like this, Like is this the first

1100
01:01:01,440 --> 01:01:02,440
Speaker 3: time this has happened?

1101
01:01:02,840 --> 01:01:05,720
Speaker 1: Well, personally, I would never go there because of other

1102
01:01:05,760 --> 01:01:11,000
Speaker 1: hearts I've heard, specifically with you. But I don't under

1103
01:01:11,200 --> 01:01:14,160
Speaker 1: I just I can't understand it. Like they are saying

1104
01:01:14,200 --> 01:01:16,280
Speaker 1: they have these barcodes on the bes and nette on

1105
01:01:16,320 --> 01:01:18,800
Speaker 1: the baby on the mother to match it. So I

1106
01:01:18,880 --> 01:01:21,840
Speaker 1: don't understand what happened with the night nurse. I'm a

1107
01:01:21,880 --> 01:01:24,800
Speaker 1: little more forgiving of the morning nurse, but she still

1108
01:01:24,840 --> 01:01:27,120
Speaker 1: should have checked the baby, even if the baby was

1109
01:01:27,200 --> 01:01:32,280
Speaker 1: being breastfed. But then again, like you know, she did

1110
01:01:32,400 --> 01:01:34,240
Speaker 1: check the best net and the mom, but she was

1111
01:01:34,240 --> 01:01:36,200
Speaker 1: saying she didn't want to disrupt the parent and she

1112
01:01:36,320 --> 01:01:40,200
Speaker 1: didn't physically hand that baby off, So you would want

1113
01:01:40,240 --> 01:01:42,320
Speaker 1: to think that the night nurse did it. But these

1114
01:01:42,360 --> 01:01:44,200
Speaker 1: protocols are in place, so this doesn't.

1115
01:01:43,920 --> 01:01:47,480
Speaker 3: Happen, all right, So this so she got so she

1116
01:01:48,320 --> 01:01:52,000
Speaker 3: told she's the one that noticed the problem and brought

1117
01:01:52,000 --> 01:01:57,640
Speaker 3: it to her supervisors, which in the hospital they always

1118
01:01:57,640 --> 01:02:00,440
Speaker 3: want you to report when there's a mistake because and

1119
01:02:00,440 --> 01:02:04,360
Speaker 3: that to me is a really big mistake, like a

1120
01:02:04,400 --> 01:02:06,440
Speaker 3: really really really big mistake.

1121
01:02:06,400 --> 01:02:08,560
Speaker 1: A huge mistake. What if they sent the kid home

1122
01:02:08,560 --> 01:02:09,680
Speaker 1: with my family?

1123
01:02:10,120 --> 01:02:14,080
Speaker 3: I just can't, like, you know, a lot, I've heard

1124
01:02:14,120 --> 01:02:16,480
Speaker 3: a lot of comments online of people saying, like, how

1125
01:02:16,520 --> 01:02:18,680
Speaker 3: do you not recognize your baby? And this and that,

1126
01:02:18,760 --> 01:02:22,320
Speaker 3: And it's like I get that, Like I feel like

1127
01:02:23,160 --> 01:02:26,080
Speaker 3: when I had my kids, they just looked so specific

1128
01:02:26,440 --> 01:02:29,840
Speaker 3: that I just know what their faces like permanently tattooed

1129
01:02:29,880 --> 01:02:30,400
Speaker 3: in my mind.

1130
01:02:30,520 --> 01:02:30,680
Speaker 4: Right.

1131
01:02:31,280 --> 01:02:33,360
Speaker 3: But at the same time, it's like a lot of

1132
01:02:33,400 --> 01:02:37,000
Speaker 3: women are like they have the epidoral and they're coming

1133
01:02:37,000 --> 01:02:38,480
Speaker 3: out of this and they're coming out of that, like

1134
01:02:39,240 --> 01:02:42,120
Speaker 3: you just had a baby, obviously you don't feel great.

1135
01:02:42,200 --> 01:02:45,320
Speaker 3: You're tired because you haven't slept, and like there's just

1136
01:02:45,320 --> 01:02:48,760
Speaker 3: like a lot of different reasons. And when you're there

1137
01:02:48,880 --> 01:02:51,200
Speaker 3: and they hand you a baby and say like here's

1138
01:02:51,200 --> 01:02:56,320
Speaker 3: your baby, like you might not even question it because

1139
01:02:56,360 --> 01:02:58,040
Speaker 3: like why would they give you the why would you

1140
01:02:58,080 --> 01:03:01,520
Speaker 3: think you have to check the bracelet? Right? But and

1141
01:03:01,520 --> 01:03:05,919
Speaker 3: and like Listen, I don't know that the mothers at

1142
01:03:05,920 --> 01:03:10,720
Speaker 3: this point can really have a lawsuit because the bottom

1143
01:03:10,800 --> 01:03:14,040
Speaker 3: line is is that like nothing happened. They checked both

1144
01:03:14,080 --> 01:03:17,680
Speaker 3: the babies and the mothers for they checked the mothers

1145
01:03:17,680 --> 01:03:21,600
Speaker 3: for infectious disease, because that would definitely be like lawsuit worthy.

1146
01:03:21,680 --> 01:03:25,880
Speaker 3: Like let's say the mom had HIV or something like that, right,

1147
01:03:26,400 --> 01:03:28,240
Speaker 3: one of them did and one of them did. You know,

1148
01:03:28,640 --> 01:03:31,320
Speaker 3: then you're like you just exposed my baby to like

1149
01:03:31,680 --> 01:03:33,240
Speaker 3: this blood borne pathogen.

1150
01:03:34,120 --> 01:03:36,680
Speaker 1: Well, it's just more of a disturbing thing, right, not

1151
01:03:36,720 --> 01:03:38,040
Speaker 1: necessarily like.

1152
01:03:38,000 --> 01:03:43,640
Speaker 3: It's disturbing, it's disturbing, and think about like like I

1153
01:03:43,640 --> 01:03:47,440
Speaker 3: would just feel so hurt and and and traumatize that

1154
01:03:47,600 --> 01:03:51,400
Speaker 3: like my kid was being like smelling someone else and

1155
01:03:51,440 --> 01:03:54,160
Speaker 3: like drinking someone else's milk, Like it just would upset

1156
01:03:54,200 --> 01:03:58,160
Speaker 3: me so so bad. But like yeah, but like listen,

1157
01:03:58,240 --> 01:04:00,240
Speaker 3: it's the same shit with me at that staatee is

1158
01:04:00,280 --> 01:04:04,400
Speaker 3: that hospital, Like it totally traumatized our whole family. But

1159
01:04:04,520 --> 01:04:06,880
Speaker 3: like the bottom line is like I'm still alive, and

1160
01:04:06,880 --> 01:04:08,800
Speaker 3: so is Lily, and so like you.

1161
01:04:08,760 --> 01:04:09,400
Speaker 1: Can't do anything.

1162
01:04:09,440 --> 01:04:12,200
Speaker 3: You can't do anything, and like I don't want to

1163
01:04:12,240 --> 01:04:14,400
Speaker 3: just be like, oh I like, I don't even want

1164
01:04:14,440 --> 01:04:16,560
Speaker 3: to sue them. They get money for myself. I just wanted,

1165
01:04:16,840 --> 01:04:19,400
Speaker 3: like I want to sue them because nobody else that

1166
01:04:19,480 --> 01:04:22,480
Speaker 3: goes there even knows that that happened. And listen, the

1167
01:04:22,560 --> 01:04:26,000
Speaker 3: same thing here, Nobody would have known this happened until

1168
01:04:26,000 --> 01:04:29,760
Speaker 3: this nurse was like I got fired for the wrong reason.

1169
01:04:29,880 --> 01:04:34,120
Speaker 1: Well exactly, and so she's claiming because she reported it,

1170
01:04:34,200 --> 01:04:37,520
Speaker 1: that's why they fired her. Yeah, which is like cover.

1171
01:04:37,400 --> 01:04:41,360
Speaker 3: It up, which is not cool because like if you

1172
01:04:41,520 --> 01:04:43,800
Speaker 3: want to send a message to your employees like hey,

1173
01:04:43,800 --> 01:04:47,200
Speaker 3: when there's a problem, you need to report it. Listen,

1174
01:04:47,280 --> 01:04:49,520
Speaker 3: I know how this hospital is though, they like want

1175
01:04:49,520 --> 01:04:51,640
Speaker 3: their shit to look good, their numbers and stuff. And

1176
01:04:52,600 --> 01:04:55,680
Speaker 3: I'm actually curious, like if this even got reported to

1177
01:04:55,720 --> 01:04:58,640
Speaker 3: who it should have got reported to. But think about this,

1178
01:04:58,640 --> 01:05:01,160
Speaker 3: This happened in when July and we're just hearing about

1179
01:05:01,200 --> 01:05:03,200
Speaker 3: it now. We never would have heard about it. And

1180
01:05:03,240 --> 01:05:05,360
Speaker 3: then you have to think about how many times does

1181
01:05:05,400 --> 01:05:08,960
Speaker 3: this happen there that we didn't hear about things at all? Well,

1182
01:05:09,120 --> 01:05:11,440
Speaker 3: like swept under the rug, swept under the rug. And

1183
01:05:11,480 --> 01:05:14,800
Speaker 3: now look like like if I had a baby there

1184
01:05:14,840 --> 01:05:17,280
Speaker 3: within the past year or something, I would be like

1185
01:05:17,880 --> 01:05:20,040
Speaker 3: freaking out, freaking out. I'd be like, do I have

1186
01:05:20,080 --> 01:05:21,840
Speaker 3: my kid? Did they switch it? Did they not check

1187
01:05:21,880 --> 01:05:22,440
Speaker 3: the bracelet?

1188
01:05:22,520 --> 01:05:25,440
Speaker 1: Like because listen, like how would you? I mean, I

1189
01:05:25,440 --> 01:05:27,120
Speaker 1: get what people are saying to you. I mean, obviously

1190
01:05:27,160 --> 01:05:28,960
Speaker 1: I never had a baby, so like, I don't know

1191
01:05:29,000 --> 01:05:30,800
Speaker 1: what it's like when you first give birth, but like

1192
01:05:31,200 --> 01:05:33,400
Speaker 1: I'm thinking, like, what if a mom had a C section,

1193
01:05:33,440 --> 01:05:35,360
Speaker 1: it was on all these drugs and was out of

1194
01:05:35,400 --> 01:05:38,720
Speaker 1: it exactly like you're saying, like, oh, it's totally possible.

1195
01:05:38,720 --> 01:05:41,520
Speaker 1: And would you even notice unless the kids started getting

1196
01:05:41,600 --> 01:05:44,000
Speaker 1: older and you were like, wow, this kid looks nothing

1197
01:05:44,160 --> 01:05:46,160
Speaker 1: like me or the child's father.

1198
01:05:46,440 --> 01:05:49,880
Speaker 3: No, it's I don't I would think that I would,

1199
01:05:49,880 --> 01:05:54,280
Speaker 3: but I don't. I don't know, like I don't, I

1200
01:05:54,320 --> 01:05:55,920
Speaker 3: don't know. I don't want to say because I've never

1201
01:05:55,920 --> 01:05:58,040
Speaker 3: been in that position, but I have been in the

1202
01:05:58,080 --> 01:05:59,880
Speaker 3: position of it being like in the middle of the

1203
01:06:00,320 --> 01:06:02,520
Speaker 3: and then waking me up and saying like, here's your baby,

1204
01:06:02,560 --> 01:06:04,080
Speaker 3: you want to feed it? And I was finally in

1205
01:06:04,120 --> 01:06:06,880
Speaker 3: a dead sleep, and like, I like, I just took

1206
01:06:06,920 --> 01:06:08,640
Speaker 3: the kid and stuck her on my boob. I didn't

1207
01:06:08,680 --> 01:06:12,200
Speaker 3: really like like it, like you know, what I mean.

1208
01:06:13,040 --> 01:06:16,960
Speaker 1: I think this hospital presents as this like beautiful resort

1209
01:06:17,080 --> 01:06:19,360
Speaker 1: brand news, state of the art, But.

1210
01:06:19,880 --> 01:06:25,320
Speaker 3: That's exactly that that that's exactly my opinion on it

1211
01:06:25,360 --> 01:06:27,960
Speaker 3: is that like and I've said that, I've said that

1212
01:06:28,040 --> 01:06:30,120
Speaker 3: from the beginning, like they care more about what it

1213
01:06:30,160 --> 01:06:33,040
Speaker 3: looks like instead of like like I'd rather go to

1214
01:06:33,080 --> 01:06:36,280
Speaker 3: the grimiest hospital ever if the people work in there,

1215
01:06:36,320 --> 01:06:39,160
Speaker 3: like know what they're doing, because ultimately, like I don't

1216
01:06:39,200 --> 01:06:42,720
Speaker 3: want to be at the Ritz Carlton delivering a baby,

1217
01:06:42,800 --> 01:06:45,080
Speaker 3: like I want you know, we I was just talking

1218
01:06:45,120 --> 01:06:47,120
Speaker 3: to you about this, like when a couple of my

1219
01:06:47,160 --> 01:06:50,480
Speaker 3: friends delivered at a Pennsylvania hospital, Like they had to

1220
01:06:50,480 --> 01:06:53,120
Speaker 3: share a room with somebody because it's a small city hospital.

1221
01:06:53,360 --> 01:06:56,120
Speaker 3: But like those they they know their shit they're doing.

1222
01:06:56,360 --> 01:06:59,600
Speaker 3: They're doing awesome work there, Like you don't care about

1223
01:06:59,600 --> 01:07:02,360
Speaker 3: that kind of stuff, having your own room, your husband

1224
01:07:02,400 --> 01:07:04,400
Speaker 3: can sleep in the room, Like who gives a shit?

1225
01:07:04,520 --> 01:07:06,280
Speaker 3: Like I kind of want to go home with the

1226
01:07:06,280 --> 01:07:09,400
Speaker 3: baby that came out of my vagina, Like sorry.

1227
01:07:09,520 --> 01:07:12,880
Speaker 1: Well, of course, I mean this is unacceptable on all levels,

1228
01:07:12,920 --> 01:07:17,120
Speaker 1: and like I don't necessarily agree with them firing the

1229
01:07:17,200 --> 01:07:20,480
Speaker 1: nurse that reported it, like I agree, she didn't take

1230
01:07:20,560 --> 01:07:24,160
Speaker 1: this step right, but she did check something. It's not

1231
01:07:24,200 --> 01:07:26,360
Speaker 1: like she walked in there and glazed over that. And

1232
01:07:26,440 --> 01:07:28,680
Speaker 1: she wasn't the nurse that physically handed them off to

1233
01:07:28,720 --> 01:07:31,600
Speaker 1: the wrong families. Ooh, or who did the mix up?

1234
01:07:31,640 --> 01:07:33,120
Speaker 1: So like what happened to the nurse?

1235
01:07:33,240 --> 01:07:35,280
Speaker 3: I kind of Actually I don't know if I I mean,

1236
01:07:35,360 --> 01:07:37,480
Speaker 3: I know that it doesn't look good when a person

1237
01:07:37,560 --> 01:07:41,960
Speaker 3: reports something and gets fired, but like the whole reason,

1238
01:07:43,440 --> 01:07:45,600
Speaker 3: like I've never been a nurse, but I'm a PA

1239
01:07:45,640 --> 01:07:49,480
Speaker 3: and work in a hospital, right, Like there's certain things

1240
01:07:49,480 --> 01:07:52,800
Speaker 3: that you're supposed to do every time because that's how

1241
01:07:52,840 --> 01:07:54,040
Speaker 3: you catch mistakes.

1242
01:07:54,520 --> 01:07:57,160
Speaker 1: But they were already like in the middle of breastfeeding

1243
01:07:57,160 --> 01:07:59,640
Speaker 1: when that nurse went into the room the first time,

1244
01:07:59,720 --> 01:08:01,200
Speaker 1: so like it was already done.

1245
01:08:01,520 --> 01:08:05,120
Speaker 3: No, it was done, but she she didn't when she

1246
01:08:05,200 --> 01:08:07,680
Speaker 3: went in. You're saying that she checked the best inet

1247
01:08:07,760 --> 01:08:10,040
Speaker 3: and and then thought it was okay and then didn't

1248
01:08:10,040 --> 01:08:12,680
Speaker 3: realize it until I after, like the mom picked it up,

1249
01:08:12,920 --> 01:08:14,960
Speaker 3: Like when when she went in the room and saw

1250
01:08:15,000 --> 01:08:18,040
Speaker 3: the basinet there and checked it. They have a list

1251
01:08:18,080 --> 01:08:21,679
Speaker 3: that's like check bascinet. It's the same with us. Ready listen,

1252
01:08:22,000 --> 01:08:26,679
Speaker 3: totally different situation. We get a body for autopsy, right, Yeah,

1253
01:08:26,760 --> 01:08:30,599
Speaker 3: there's a toe tag that's on the bag itself. There's

1254
01:08:30,640 --> 01:08:33,120
Speaker 3: a toe tag that's on the toe, and there's a

1255
01:08:33,160 --> 01:08:36,439
Speaker 3: bracelet on the patient. We have to check every single

1256
01:08:36,479 --> 01:08:38,960
Speaker 3: one of them if they're not the same, which has

1257
01:08:39,000 --> 01:08:41,920
Speaker 3: happened a couple of times that they're not the same.

1258
01:08:42,360 --> 01:08:45,479
Speaker 3: I literally had the wrong body one time in the bag.

1259
01:08:46,880 --> 01:08:49,080
Speaker 3: If you don't do and I could have cut that

1260
01:08:49,160 --> 01:08:52,720
Speaker 3: body if I didn't check, and I would have done

1261
01:08:52,760 --> 01:08:56,240
Speaker 3: the autopsy on a completely wrong person. Because mistakes happen.

1262
01:08:56,280 --> 01:08:59,280
Speaker 3: People are human, right, That's why those checks are in place.

1263
01:08:59,320 --> 01:09:01,080
Speaker 3: So every single time I took a body out of

1264
01:09:01,080 --> 01:09:03,639
Speaker 3: the fridge, i'd have put it on the autopsy table.

1265
01:09:04,120 --> 01:09:07,519
Speaker 3: Check the bag, check or check the bag, check the

1266
01:09:07,560 --> 01:09:09,760
Speaker 3: toe tag, check the bracelet, and then check the chart

1267
01:09:10,200 --> 01:09:12,320
Speaker 3: and it and we have like what's called like a

1268
01:09:12,400 --> 01:09:16,040
Speaker 3: time out, like me and one of the residents or something. Okay,

1269
01:09:16,320 --> 01:09:21,559
Speaker 3: this is mister Jones. Yep, mister Jones, mister Jones, mister Jones. Okay,

1270
01:09:21,880 --> 01:09:25,240
Speaker 3: same medical couple, digits of the medical record number yep, yep.

1271
01:09:25,400 --> 01:09:27,800
Speaker 3: Same date of birth yep, yep, yep. Okay, we have

1272
01:09:27,800 --> 01:09:31,720
Speaker 3: the right patient, and that's what she didn't do. Like,

1273
01:09:32,560 --> 01:09:35,240
Speaker 3: I understand that she checked the bassinette, but her protocol

1274
01:09:35,320 --> 01:09:37,120
Speaker 3: is to check the baby too, and she didn't do it.

1275
01:09:37,439 --> 01:09:40,479
Speaker 1: No, totally, she she was still wrong. But like, did

1276
01:09:40,520 --> 01:09:43,240
Speaker 1: the other nurse not give I'm assuming the other nurs.

1277
01:09:43,080 --> 01:09:46,519
Speaker 3: I'm sure I'm sure she'd I'm sure everybody that had

1278
01:09:46,560 --> 01:09:47,559
Speaker 3: something to do with it.

1279
01:09:48,840 --> 01:09:49,880
Speaker 1: I would agree with her.

1280
01:09:49,920 --> 01:09:52,479
Speaker 3: I feel like I feel like they should have. Yeah,

1281
01:09:52,520 --> 01:09:56,759
Speaker 3: I feel like they should have maybe like reprimanded her, maybe,

1282
01:09:56,800 --> 01:10:02,200
Speaker 3: And like because now because now like everybody knows what happened,

1283
01:10:02,360 --> 01:10:06,160
Speaker 3: and clearly they don't like that the negative press for sure,

1284
01:10:06,200 --> 01:10:12,160
Speaker 3: because and like who really saw the article? I mean

1285
01:10:12,200 --> 01:10:13,840
Speaker 3: I would just be like, no, like this is a

1286
01:10:13,880 --> 01:10:16,000
Speaker 3: really big deal. I'm more mad that they didn't say

1287
01:10:16,000 --> 01:10:17,280
Speaker 3: anything about it when it happened.

1288
01:10:17,320 --> 01:10:19,360
Speaker 1: You know, well, yeah, and it might have been more

1289
01:10:19,400 --> 01:10:22,320
Speaker 1: on our radar because you had such a bad experience there.

1290
01:10:22,160 --> 01:10:24,840
Speaker 3: So like exactly, of course, when it popped up on

1291
01:10:24,880 --> 01:10:26,960
Speaker 3: the news, I was just like, oh, really, shocker.

1292
01:10:27,600 --> 01:10:29,880
Speaker 1: Yeah, all right, let's move on to Questions of the Week.

1293
01:10:29,880 --> 01:10:32,280
Speaker 1: Every Friday on the ap Mother Knows Death Instagram account

1294
01:10:32,400 --> 01:10:35,800
Speaker 1: or on our YouTube channel. You can ask us whatever

1295
01:10:35,880 --> 01:10:39,680
Speaker 1: questions you want. First, do you recall your first ever autopsy?

1296
01:10:39,840 --> 01:10:44,000
Speaker 1: What was the experience like the first time? Yes, I do.

1297
01:10:44,000 --> 01:10:46,320
Speaker 3: Do you mean first autopsy I ever saw or first

1298
01:10:46,320 --> 01:10:48,160
Speaker 3: one I ever did?

1299
01:10:51,040 --> 01:10:53,719
Speaker 1: Maybe both? Just do a brief runner.

1300
01:10:53,760 --> 01:10:57,000
Speaker 3: Okay, so the first one I ever saw was a

1301
01:10:57,080 --> 01:11:03,040
Speaker 3: guy who had HIV and ended up dying from complications

1302
01:11:03,040 --> 01:11:08,200
Speaker 3: from AIDS. That was cool. That was during that was

1303
01:11:08,240 --> 01:11:14,400
Speaker 3: when I was still a cydotech. It was an interesting

1304
01:11:14,479 --> 01:11:19,160
Speaker 3: experience because I really had only seen one dead person

1305
01:11:19,240 --> 01:11:21,519
Speaker 3: prior to that in my entire life, when my uncle

1306
01:11:21,600 --> 01:11:25,800
Speaker 3: died so and he was a viewing, so it just

1307
01:11:25,920 --> 01:11:29,320
Speaker 3: was a different situation. And it was just very weird

1308
01:11:29,360 --> 01:11:34,439
Speaker 3: because you walk into the autopsy room and this was

1309
01:11:34,479 --> 01:11:38,040
Speaker 3: at Hanuman Hospital, which isn't even a hospital anymore, like

1310
01:11:38,120 --> 01:11:39,880
Speaker 3: my favorite morgue of all time. Because it was on

1311
01:11:39,920 --> 01:11:41,880
Speaker 3: the fifth floor and I had windows and you could

1312
01:11:41,880 --> 01:11:45,640
Speaker 3: see the whole skyline. It was really cool, but you know,

1313
01:11:45,680 --> 01:11:49,760
Speaker 3: there's residents there, doctors, medical students. The room was full

1314
01:11:49,800 --> 01:11:51,920
Speaker 3: of like ten people, and I'm just kind of like,

1315
01:11:52,160 --> 01:11:54,519
Speaker 3: there's a dead person right there, Like why are you

1316
01:11:54,560 --> 01:11:56,920
Speaker 3: guys all Just like hanging around like this is nothing

1317
01:11:59,120 --> 01:12:02,360
Speaker 3: and yes. So so that was that and it was cool.

1318
01:12:02,400 --> 01:12:04,160
Speaker 3: I didn't even get to assist or anything. I just

1319
01:12:04,200 --> 01:12:06,760
Speaker 3: like stood in the corner and just was watching and

1320
01:12:06,880 --> 01:12:09,360
Speaker 3: just couldn't believe what I was looking at. And then

1321
01:12:09,520 --> 01:12:11,960
Speaker 3: the very first one that I did by myself, I

1322
01:12:12,000 --> 01:12:15,720
Speaker 3: would say, well, the very first one that I ever

1323
01:12:15,840 --> 01:12:20,080
Speaker 3: cut was at the Medical Examiner's office on somebody that

1324
01:12:20,280 --> 01:12:24,280
Speaker 3: was severely decomposed with like the maggots in the anus

1325
01:12:24,320 --> 01:12:27,519
Speaker 3: and everything. It was so messy, but those people aren't

1326
01:12:27,520 --> 01:12:31,000
Speaker 3: having a viewing, so they're really good to start to

1327
01:12:31,160 --> 01:12:34,640
Speaker 3: practice doing incisions on first, because if you don't do

1328
01:12:34,720 --> 01:12:37,320
Speaker 3: it perfect, you know they're not going to have a viewing.

1329
01:12:37,920 --> 01:12:40,840
Speaker 3: So that was the very first one I cut. And

1330
01:12:40,840 --> 01:12:43,040
Speaker 3: then the very first one that I cut by myself

1331
01:12:43,240 --> 01:12:45,519
Speaker 3: was a cardiac tamp and I was the cause of death.

1332
01:12:45,560 --> 01:12:49,840
Speaker 3: And that was that was like really exciting to work

1333
01:12:49,880 --> 01:12:51,960
Speaker 3: with the pathol just on that because I didn't I

1334
01:12:51,960 --> 01:12:53,760
Speaker 3: had never seen it in real life. But when I

1335
01:12:53,800 --> 01:12:55,760
Speaker 3: took the chest plate off, I was like, oh my god,

1336
01:12:55,800 --> 01:12:58,160
Speaker 3: this is so cool, like I knew what it was so.

1337
01:12:59,280 --> 01:13:01,559
Speaker 1: All right too. If a woman dies, do you check

1338
01:13:01,600 --> 01:13:03,760
Speaker 1: to see if she's pregnant during an autopsy.

1339
01:13:04,720 --> 01:13:09,200
Speaker 3: I mean we don't. We're not when I opened the uterus,

1340
01:13:09,240 --> 01:13:11,920
Speaker 3: I'm not looking for that. But like if we saw it,

1341
01:13:12,000 --> 01:13:15,160
Speaker 3: we would see it if it was there, Like at least,

1342
01:13:15,520 --> 01:13:18,000
Speaker 3: I don't know what they do for medical examiner cases

1343
01:13:18,000 --> 01:13:21,640
Speaker 3: because like let's say a person gets shot, like a

1344
01:13:21,680 --> 01:13:24,760
Speaker 3: woman gets shot, a child bearing age woman gets shot

1345
01:13:24,800 --> 01:13:28,280
Speaker 3: in the head. They might they I don't. I don't

1346
01:13:28,320 --> 01:13:30,120
Speaker 3: know if they're gonna take out the uterus and like

1347
01:13:30,200 --> 01:13:33,559
Speaker 3: open the uterus and stuff. They probably do, they just

1348
01:13:33,600 --> 01:13:35,920
Speaker 3: don't do a thorough as an autopsy as you do

1349
01:13:36,000 --> 01:13:38,360
Speaker 3: in a medical institution most of the time at the

1350
01:13:38,360 --> 01:13:42,200
Speaker 3: emmy's office, because like if they could determine the cause

1351
01:13:42,200 --> 01:13:47,439
Speaker 3: of death, then but what if like she was pregnant

1352
01:13:47,479 --> 01:13:49,360
Speaker 3: and like that's why she got killed. I don't know,

1353
01:13:49,760 --> 01:13:51,120
Speaker 3: or like is that what you were gonna say?

1354
01:13:51,320 --> 01:13:54,320
Speaker 1: No, Like couldn't it be like double homicide if you

1355
01:13:54,439 --> 01:13:57,640
Speaker 1: kill an unborn bait? Like yeah, Like I don't, I

1356
01:13:58,160 --> 01:14:01,280
Speaker 1: don't know, Like I'm a like, I just don't know

1357
01:14:01,320 --> 01:14:04,280
Speaker 1: what they do there because when I went there, it

1358
01:14:04,360 --> 01:14:07,200
Speaker 1: was like we didn't always look at every single organ

1359
01:14:07,320 --> 01:14:11,000
Speaker 1: like that, like certain places. It just depends which one,

1360
01:14:11,040 --> 01:14:13,000
Speaker 1: because some places are just like we just want to

1361
01:14:13,040 --> 01:14:14,679
Speaker 1: find out the cause of death. We have a cause

1362
01:14:14,680 --> 01:14:17,000
Speaker 1: of death. This person out a cardiac TAMPAA. That's how

1363
01:14:17,160 --> 01:14:17,479
Speaker 1: we died.

1364
01:14:17,520 --> 01:14:19,400
Speaker 3: We don't need to be examined in their prostate land

1365
01:14:19,400 --> 01:14:23,320
Speaker 3: and stuff like the hospital though for sure, like we

1366
01:14:23,439 --> 01:14:25,479
Speaker 3: take all the organs out, we cut them open, and

1367
01:14:25,520 --> 01:14:28,680
Speaker 3: we look and we even look at them under the microscope,

1368
01:14:28,680 --> 01:14:33,160
Speaker 3: whereas the medical examiner won't always do that as well.

1369
01:14:34,520 --> 01:14:35,960
Speaker 3: So yeah, I've never seen it.

1370
01:14:36,000 --> 01:14:36,400
Speaker 1: We did.

1371
01:14:37,080 --> 01:14:41,080
Speaker 3: I believe when I was in surgical pathology at some

1372
01:14:41,320 --> 01:14:45,000
Speaker 3: point in my education that there was a case that

1373
01:14:45,040 --> 01:14:49,520
Speaker 3: there was a hysterectomy done and there was a fetus inside,

1374
01:14:49,920 --> 01:14:51,840
Speaker 3: and that was like I remember it being like a

1375
01:14:51,880 --> 01:14:54,639
Speaker 3: really huge deal. But I wasn't personally involved in the case,

1376
01:14:54,720 --> 01:14:59,240
Speaker 3: so I just kind of tried to like eavesdrop but

1377
01:14:59,360 --> 01:15:01,840
Speaker 3: stay out of it. And it was it was like

1378
01:15:01,880 --> 01:15:03,479
Speaker 3: while I was still in school, so I wasn't like

1379
01:15:03,479 --> 01:15:05,960
Speaker 3: one hundred percent of like what was happening and stuff.

1380
01:15:05,960 --> 01:15:09,400
Speaker 3: And but yeah, all.

1381
01:15:09,360 --> 01:15:11,679
Speaker 1: Right, three, why do you think women are more into

1382
01:15:11,720 --> 01:15:12,760
Speaker 1: true crime than men?

1383
01:15:16,560 --> 01:15:18,719
Speaker 3: I don't. I don't know, to be honest, it's definitely

1384
01:15:18,720 --> 01:15:21,880
Speaker 3: a thing. We could say one hundred percent is a thing.

1385
01:15:22,320 --> 01:15:26,040
Speaker 1: I think a lot of it is, like you know,

1386
01:15:26,479 --> 01:15:28,720
Speaker 1: I think a lot of it is like disbelief that

1387
01:15:28,720 --> 01:15:32,400
Speaker 1: that happens, and just like the pure fascination of that.

1388
01:15:32,479 --> 01:15:35,160
Speaker 1: And then I also think, like, for me, what I

1389
01:15:35,280 --> 01:15:38,960
Speaker 1: like the most is the investigation component because I like

1390
01:15:39,040 --> 01:15:41,360
Speaker 1: seeing how like all the pieces get put together.

1391
01:15:42,439 --> 01:15:47,000
Speaker 3: Do you think it's because women like like drama.

1392
01:15:47,960 --> 01:15:49,679
Speaker 1: Well, sure, that's a huge element.

1393
01:15:49,840 --> 01:15:55,400
Speaker 3: Like for example, sometimes Gabe will tell me something about

1394
01:15:55,680 --> 01:15:58,080
Speaker 3: one of his friends or something at work or something,

1395
01:15:58,200 --> 01:16:02,120
Speaker 3: and I'm and then like, my first question is like, well,

1396
01:16:02,160 --> 01:16:04,680
Speaker 3: what happened, Like, tell me what happened? And he's like,

1397
01:16:04,840 --> 01:16:08,479
Speaker 3: I don't know. Believe me, I don't know. I don't know.

1398
01:16:08,520 --> 01:16:10,360
Speaker 3: They just got divorced. I don't know. He went to

1399
01:16:10,439 --> 01:16:13,760
Speaker 3: jail for the night. And I'm like, well, why what happened? Oh,

1400
01:16:13,800 --> 01:16:18,160
Speaker 3: I don't know? Like women have this like no, I

1401
01:16:18,200 --> 01:16:20,360
Speaker 3: want to know everything. I need to know every single

1402
01:16:20,400 --> 01:16:22,960
Speaker 3: detail of this, like how did this go down? Men

1403
01:16:23,120 --> 01:16:28,000
Speaker 3: like like I'm I'm I'm being totally sexist here, but listen,

1404
01:16:28,479 --> 01:16:33,360
Speaker 3: crime con it's palpable. It's definitely like every single I

1405
01:16:33,720 --> 01:16:36,080
Speaker 3: think there were two men that came up to me

1406
01:16:36,240 --> 01:16:41,240
Speaker 3: the entire time that were by themselves. Yeah, now with

1407
01:16:41,320 --> 01:16:44,439
Speaker 3: their literally two men. Lots of other men were with

1408
01:16:44,479 --> 01:16:48,000
Speaker 3: a wife or a girlfriend. But and And like the

1409
01:16:48,000 --> 01:16:52,000
Speaker 3: majority of men that I talked to were presenters. Yes,

1410
01:16:52,160 --> 01:16:55,920
Speaker 3: not not there, it's and And Gabe went with us

1411
01:16:55,920 --> 01:16:57,800
Speaker 3: to crime Con last year and he said the same thing.

1412
01:16:57,840 --> 01:17:00,000
Speaker 3: He was just like, yo, this is like all chicks here.

1413
01:17:00,360 --> 01:17:05,080
Speaker 3: He noticed it right away. My analytics on Instagram eighty

1414
01:17:05,120 --> 01:17:09,920
Speaker 3: seven percent female. There's something about it obviously that like

1415
01:17:12,520 --> 01:17:14,880
Speaker 3: you know, there's something, there's something to it, and I

1416
01:17:14,960 --> 01:17:17,559
Speaker 3: just wonder what that is. Not to say that, because

1417
01:17:17,600 --> 01:17:20,200
Speaker 3: there are lots I know, lots of men that are

1418
01:17:20,200 --> 01:17:24,799
Speaker 3: like very inquisitive and stuff. But another thing to consider

1419
01:17:24,840 --> 01:17:28,560
Speaker 3: too is that in my profession as a pathologists assistant,

1420
01:17:28,680 --> 01:17:32,120
Speaker 3: it's mostly at least when I went to school, and

1421
01:17:32,120 --> 01:17:36,200
Speaker 3: stuff like heavy heavy female, like back in the day

1422
01:17:36,240 --> 01:17:39,320
Speaker 3: it was male, and then like now I would say

1423
01:17:39,320 --> 01:17:41,679
Speaker 3: that the field is heavily female.

1424
01:17:42,720 --> 01:17:44,960
Speaker 1: Well, let me use this as an example, like this

1425
01:17:45,120 --> 01:17:48,080
Speaker 1: morning I go to Ricky, did you hear about that

1426
01:17:48,080 --> 01:17:50,960
Speaker 1: girl that was found in that Sanger's car? No, he

1427
01:17:51,000 --> 01:17:52,840
Speaker 1: hasn't heard of it of course, which I'm like, it's

1428
01:17:52,840 --> 01:17:54,439
Speaker 1: all over the news. How have you not heard of it?

1429
01:17:55,000 --> 01:17:58,080
Speaker 1: And then he's just like, oh, that sucks, not like

1430
01:17:58,400 --> 01:18:01,840
Speaker 1: how did she get there? What was their deal? Why

1431
01:18:01,920 --> 01:18:04,280
Speaker 1: was she dating an older guy? Like I feel like

1432
01:18:04,320 --> 01:18:08,200
Speaker 1: women just naturally are so much more inquisitive and curious. Dude?

1433
01:18:08,240 --> 01:18:10,080
Speaker 1: Did they just saying that the answers?

1434
01:18:10,880 --> 01:18:13,320
Speaker 3: I said to the girls, We're all sitting down eating

1435
01:18:13,320 --> 01:18:15,240
Speaker 3: dinner last night, and I said, did you ever hear

1436
01:18:15,280 --> 01:18:17,920
Speaker 3: of this singer guy David? Because he's like a social

1437
01:18:18,000 --> 01:18:22,000
Speaker 3: media He's like he has like an unusual way of

1438
01:18:22,000 --> 01:18:23,800
Speaker 3: being a singer, Like I think he made a bunch

1439
01:18:23,840 --> 01:18:27,160
Speaker 3: of videos and yeah, he like backdoored it kind of right.

1440
01:18:27,720 --> 01:18:31,840
Speaker 3: So so of course they're like, I mean they like

1441
01:18:31,920 --> 01:18:33,519
Speaker 3: spit off the whole story. To me, I was like,

1442
01:18:33,520 --> 01:18:35,400
Speaker 3: I just wrote about this all day and you literally

1443
01:18:35,439 --> 01:18:38,160
Speaker 3: know every single detail of it, Like it's it's insane

1444
01:18:38,880 --> 01:18:41,839
Speaker 3: because their girl, that's just like how they are, Whereas

1445
01:18:41,880 --> 01:18:43,760
Speaker 3: like if you were talking to a boy, I think

1446
01:18:43,800 --> 01:18:46,360
Speaker 3: that they would just be like, oh, I guess.

1447
01:18:46,560 --> 01:18:49,280
Speaker 1: On the other hand, my husband could give me every

1448
01:18:49,320 --> 01:18:51,800
Speaker 1: step of every person that's ever played on the Philadelphia

1449
01:18:51,800 --> 01:18:53,479
Speaker 1: flyers for the last thirty five years.

1450
01:18:53,880 --> 01:18:56,800
Speaker 3: But otherwise no interesting, no.

1451
01:18:56,880 --> 01:18:58,120
Speaker 1: Question, No, it's true.

1452
01:18:58,240 --> 01:19:01,960
Speaker 3: So I think that that's why I think also like

1453
01:19:02,640 --> 01:19:05,679
Speaker 3: women tend to be and this is just like general

1454
01:19:05,720 --> 01:19:08,880
Speaker 3: because I know that some guys are are like that too,

1455
01:19:08,920 --> 01:19:14,760
Speaker 3: but women tend to be more emotional. So like you,

1456
01:19:15,160 --> 01:19:18,240
Speaker 3: if you watch a movie that's like like a romance

1457
01:19:18,320 --> 01:19:21,840
Speaker 3: movie or anything, like, you cry, right, You're just like

1458
01:19:21,880 --> 01:19:24,760
Speaker 3: you get invested in the story and you feel like

1459
01:19:25,000 --> 01:19:28,840
Speaker 3: you you cry because you feel like personally affected by it, right,

1460
01:19:29,280 --> 01:19:33,439
Speaker 3: Like dudes don't always get bothered by that kind of stuff.

1461
01:19:33,439 --> 01:19:36,800
Speaker 3: It's just like it's like the whole like women are

1462
01:19:36,920 --> 01:19:40,080
Speaker 3: or men are from Mars, women are from Venus. Thing like,

1463
01:19:40,920 --> 01:19:44,920
Speaker 3: there is something to be said about that that. Like

1464
01:19:45,360 --> 01:19:48,760
Speaker 3: people can cross over for sure and have different like

1465
01:19:49,120 --> 01:19:53,000
Speaker 3: I think like I have way more like male things

1466
01:19:53,080 --> 01:19:56,960
Speaker 3: like that than the average chick, right, but like for

1467
01:19:57,040 --> 01:19:59,920
Speaker 3: the most part, there's like a different way of thinking

1468
01:20:00,520 --> 01:20:02,840
Speaker 3: about things and reacting to things.

1469
01:20:04,040 --> 01:20:07,439
Speaker 1: It is interesting to think about. Okay, guys, Next Friday,

1470
01:20:07,479 --> 01:20:09,400
Speaker 1: we are gonna be at the Wildlife CSI at Lake

1471
01:20:09,439 --> 01:20:12,240
Speaker 1: to Buy Us Wildlife Park, and then the following weekend

1472
01:20:12,280 --> 01:20:15,040
Speaker 1: I will be volunteering at the Keeping Hope Alive Golf Classic,

1473
01:20:15,080 --> 01:20:17,080
Speaker 1: and the weekend after that we will have a live

1474
01:20:17,120 --> 01:20:19,400
Speaker 1: show at Darkside, New Jersey in Edison.

1475
01:20:19,920 --> 01:20:21,920
Speaker 3: You have to tell them about the Mother Nos Death

1476
01:20:21,960 --> 01:20:24,160
Speaker 3: golf cart. It's like there will be Mother Nose Depth

1477
01:20:24,240 --> 01:20:24,920
Speaker 3: golf carts.

1478
01:20:24,960 --> 01:20:27,760
Speaker 1: We're gonna take really cute photos for them and it's

1479
01:20:27,800 --> 01:20:30,880
Speaker 1: gonna be really cool to drive around and your little

1480
01:20:30,920 --> 01:20:32,679
Speaker 1: pink well, the whole golf cart is not gonna be pink,

1481
01:20:32,680 --> 01:20:35,000
Speaker 1: but it's gonna have our pink sticker on it, all right, good,

1482
01:20:35,439 --> 01:20:38,200
Speaker 1: it'll be cute. If you have reviews for us, please

1483
01:20:38,200 --> 01:20:40,519
Speaker 1: head over to Apple or Spotify. You could leave them there.

1484
01:20:40,560 --> 01:20:43,040
Speaker 1: Please subscribe to our YouTube channel, and if you have

1485
01:20:43,080 --> 01:20:45,080
Speaker 1: a story for us, please submit it to stories at

1486
01:20:45,120 --> 01:20:46,479
Speaker 1: Mothernosdeath dot com.

1487
01:20:46,680 --> 01:20:53,559
Speaker 3: See you, guys, thank you for listening to Mother Nos Death.

1488
01:20:54,280 --> 01:20:57,960
Speaker 3: As a reminder, my training is as a pathologist assistant.

1489
01:20:58,760 --> 01:21:02,200
Speaker 3: I have a master's level education and specialize in anatomy

1490
01:21:02,240 --> 01:21:05,880
Speaker 3: and pathology education. I am not a doctor and I

1491
01:21:05,880 --> 01:21:09,719
Speaker 3: have not diagnosed or treated anyone dead or alive without

1492
01:21:09,720 --> 01:21:15,120
Speaker 3: the assistance of a licensed medical doctor. This show, my website,

1493
01:21:15,240 --> 01:21:18,599
Speaker 3: and social media accounts are designed to educate and inform

1494
01:21:18,640 --> 01:21:22,880
Speaker 3: people based on my experience working in pathology, so they

1495
01:21:22,920 --> 01:21:26,320
Speaker 3: can make healthier decisions regarding their life and well being.

1496
01:21:27,439 --> 01:21:30,320
Speaker 3: Always remember that science is changing every day and the

1497
01:21:30,360 --> 01:21:33,679
Speaker 3: opinions expressed in this episode are based on my knowledge

1498
01:21:33,680 --> 01:21:37,320
Speaker 3: of those subjects at the time of publication. If you

1499
01:21:37,400 --> 01:21:41,280
Speaker 3: are having a medical problem, have a medical question, or

1500
01:21:41,439 --> 01:21:45,679
Speaker 3: having a medical emergency, please contact your physician or visit

1501
01:21:45,760 --> 01:21:51,080
Speaker 3: an urgent care center, emergency room, or hospital. Please rate, review,

1502
01:21:51,160 --> 01:21:55,560
Speaker 3: and subscribe to Mother Knows Death on Apple, Spotify, YouTube,

1503
01:21:55,800 --> 01:22:05,440
Speaker 3: or anywhere you get podcasts. Thanks