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Speaker 1: Hey, I normally the show with normalist takes, but when

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Speaker 1: in the news it's weird.

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Speaker 2: I'm Mary Catherine's hand and I'm Karl Marcowitz. How are you,

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Speaker 2: Mary Catherine.

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Speaker 3: I'm doing all right.

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Speaker 1: And I forgot that yesterday I forgot I did not

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Speaker 1: give a or this week, I did not give a

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Speaker 1: shout out to Charlie Pooths for the National anthem, which.

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Speaker 3: Was gorgeously arranged, beautifully performed.

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Speaker 1: He's a great guy as a He has perfect pitch,

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Speaker 1: so he like knows every note without context.

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Speaker 3: You can just play him a note and he knows

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Speaker 3: what it is.

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Speaker 1: And he does all this like fascinating music theory on

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Speaker 1: his social media.

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Speaker 3: And when that flyover happened and he.

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Speaker 1: Finished, there's a clip on the nfl X account of

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Speaker 1: him reacting to the anthem and to the moment and

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Speaker 1: to the flyover, and he is just so obviously tearful,

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Speaker 1: way honored, and it was such a nice moment.

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Speaker 2: Yeah, he fit the moment and he sounded greatly. Are

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Speaker 2: we asking for too much that that's what we're looking

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Speaker 2: for from the performances, like make them good and don't

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Speaker 2: make them stand out too much in a negative way. Period, like,

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Speaker 2: don't make them too scandalous, don't make them too political.

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Speaker 2: Just a normal show would have done it for everybody.

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Speaker 2: And you know what it could have been in Spanish.

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Speaker 2: The Spanish part was really not the problem. It was

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Speaker 2: the leftism, and the more days go by, the more

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Speaker 2: that seems to be the message. I think from most

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Speaker 2: people that the Spanish part was a side issue for

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Speaker 2: some people, but for the most part, it was what

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Speaker 2: is he talking about?

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Speaker 1: My favorite joke is how other Spanish speakers are like, oh,

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Speaker 1: we didn't understand them either.

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Speaker 2: Right, Oh yeah, all right, you know, so let's get

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Speaker 2: into it.

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Speaker 3: Do some news.

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Speaker 1: Okay, Well, there are fights brewing in Congress. There was

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Speaker 1: a small cr that's the Continuing resolution that we used

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Speaker 1: to stop gap fund our govern because we don't do

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Speaker 1: it in a functional fashion.

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Speaker 2: Were just going to keep talking about that every time

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Speaker 2: they do it, and everybody.

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Speaker 1: Like signed off on it, except the part that got

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Speaker 1: left out was the Department of Homeland Security because the

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Speaker 1: Democrats want to have a fight about Homeland Security. The

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Speaker 1: funding for that will run out February thirteenth, this friday,

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Speaker 1: so they're negotiating about what this looks like the problem

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Speaker 1: for Democrats in this fight is that they are risking

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Speaker 1: a shutdown over something like I think they sincerely care

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Speaker 1: about not doing immigration reform. I think it's a sincere

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Speaker 1: belief that they hold. But they're going to potentially shut

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Speaker 1: down the government over something that is not in this

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Speaker 1: funding bill, right because ice and border patrol were funded

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Speaker 1: for several years in the one big beautiful bill, so

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Speaker 1: that's done. The things they are arguing over the thing

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Speaker 1: they would shut down the government for our FEMA, Coast

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Speaker 1: Guard and some other thhs TSA, so it won't actually

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Speaker 1: affect the thing that they are talking about. So that's

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Speaker 1: where we are on that fight at the moment.

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Speaker 2: It's like they're scrambling around just to find something to

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Speaker 2: oppose because that's what gets their people going well.

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Speaker 1: And they had said, Okay, our ask is the body cams,

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Speaker 1: and they're like, oh wait, maybe we don't like bodycams.

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Speaker 1: So it's gonna be hard to make a deal if

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Speaker 1: you don't know what you want. The other thing they're

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Speaker 1: asking for is judicial warrants for picking up people who

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Speaker 1: have final orders of deportation. That is meant to make

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Speaker 1: this process nearly impossible. A final order of deportation, by

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Speaker 1: the way, means you have had due process. Yeah, that's

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Speaker 1: what that means, You've written through a process. So I

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Speaker 1: don't agree with that part of it. I think there

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Speaker 1: are other things that they could make compromises on, but

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Speaker 1: I don't know where this is headed, and I don't

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Speaker 1: think people want to shut down.

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Speaker 2: Yeah, although I feel like Americans don't even notice when

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Speaker 2: there is a shutdown, only the people they aren't getting paid.

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Speaker 1: They're diminishing returns on the pr hullablue. I'm a shut

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Speaker 1: down because we do it so much. I did find

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Speaker 1: it interesting that Dana Bash on CNN asked Hakeem Jeffries

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Speaker 1: a tough question about this.

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Speaker 4: Here she is, we know that ICE is completely and

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Speaker 4: totally out of control. They've gone way too far, and

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Speaker 4: the American people want them reined in because immigration enforcement

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Speaker 4: should be fair, it should be just, and it should

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Speaker 4: be humane. So dramatic changes are necessary to the manner

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Speaker 4: in which the Department of Homeland Security officers are conducting

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Speaker 4: themselves before any funding bill should move forward.

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Speaker 5: So you say very clearly that this, and it's clearer

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Speaker 5: in your proposals, this is about raining in ICE and

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Speaker 5: the CBP. But those agencies, as you well now, are

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Speaker 5: very well funded already through the Big Beautiful Bill Act.

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Speaker 5: That's what the President called it, and it passed last year.

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Speaker 5: So what that means is that a shutdown would really

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Speaker 5: only impact un related agencies FEMA, TSA, FAA. So how

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Speaker 5: is pushing for these changes and potentially not getting there

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Speaker 5: help bring in an immigration crackdown?

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Speaker 2: Wow?

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Speaker 3: I mean tricky, right?

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Speaker 1: And whoever's idea it was to put that funding in

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Speaker 1: the one Big Beautiful Bill very smart.

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Speaker 3: Brilliant because it forestalled exactly all.

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Speaker 2: Of this, right this discussion, because yes it was Stephen

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Speaker 2: Miller on that, but who knows.

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Speaker 1: But the general mood, like you know, we talked about

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Speaker 1: the pr fight, there wasn't extremely a beyond expectations jobs

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Speaker 1: report today that I think signals that if Republicans could

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Speaker 1: claw back some of the some of the fields, some

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Speaker 1: of the vibe shift, right that the fact that it

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Speaker 1: might be happening now in the early part of the

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Speaker 1: year is very good news for them. There were one

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Speaker 1: hundred and thirty k jobs posted now that could be revised,

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Speaker 1: but the forecast was like forty eight to seventy.

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Speaker 3: Yeah, so that's a very large number. Particularly in the

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Speaker 3: AI age.

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Speaker 2: Exactly, unemployment fell to four point three percent. Of course,

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Speaker 2: in the telling of this story, the telling isn't going

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Speaker 2: to be politically neutral, and that's where the Trump administration

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Speaker 2: has its difficulties because when The New York Times writes

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Speaker 2: about this report, obviously they try to portray it in

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Speaker 2: the worst manner possible. One of the things that they

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Speaker 2: say is that maybe companies didn't hire as many people

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Speaker 2: for the holidays as they normally do, and so that

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Speaker 2: therefore they didn't need to did not need to lay

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Speaker 2: them off in January. Is this possible? Who knows? They

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Speaker 2: provide no evidence for this whatsoever. It's literally just an

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Speaker 2: idea they have on their Live Update page about the economy.

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Speaker 1: That seems like you should back that up with something.

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Speaker 1: But I do think that Trump and Republicans should not

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Speaker 1: ignore the environment that they are in. Right to tell

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Speaker 1: yourself that everyone's getting this message clearly is not wise

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Speaker 1: because if you listen to Harrietton, who's running the numbers

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Speaker 1: from the polling on the economy and jobs, he has

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Speaker 1: this to say about how people are perceiving this, particularly independence.

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Speaker 6: Donald Trump took a beautiful swan and turned it into

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Speaker 6: an ugly duckling as far as the American people are concerned,

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Speaker 6: because these numbers, as John and I were discussing just

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Speaker 6: before this segment, absolutely crazy, and how the American people

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Speaker 6: have totally turned on Donald Trump. Take a look here,

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Speaker 6: Trump's net appropriating on jobs and employment in January twenty

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Speaker 6: twenty five. Look at that overall plus nine points. Hey,

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Speaker 6: that's pretty good. But down he goes minus thirteen points overall.

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Speaker 6: But you think that's nuts, Take a look at the independence.

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Speaker 6: They go from plus seven way way way down off

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Speaker 6: the screen to minus thirty points. That's a thirty seven

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Speaker 6: point drop in the net approval for Donald Trump among

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Speaker 6: independence on the issue of jobs and employments.

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Speaker 7: Again, with independence, just consistently, we're seeing these staggering changes.

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Speaker 6: Over just a year, just one years of time.

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Speaker 7: All right, This next chart is actually the one that

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Speaker 7: really blew my mind.

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Speaker 3: It's about people's views of.

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Speaker 7: The job market in general over a similar period.

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Speaker 6: Yeah, okay, if you think these numbers are crazy, this

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Speaker 6: next one these are bonkers. Okay, what are we talking

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Speaker 6: about here? Americans rate the job market is bad or

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Speaker 6: good February twenty twenty five, equal share say fair or

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Speaker 6: say bad? Or good forty two, forty two. Look at

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Speaker 6: this now over just a year's time. Now the clear

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Speaker 6: majority fifty two percent up like a rocket rate it

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Speaker 6: as bad, compared to just thirty three percent down in

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Speaker 6: the basement who rated as good. So what we've seen

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Speaker 6: is Americans rating the job market. It was an even

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Speaker 6: split a year ago, and now the clear majority by

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Speaker 6: a nineteen point margin rate it is bad rather than good.

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Speaker 6: And that goes a long way to explain why Donald

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Speaker 6: Trump's numbers on jobs and unemployment have.

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Speaker 3: Fallen to them.

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Speaker 7: Just be clear, this is Donald Trump's presidency. During Donald

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Speaker 7: Trump's presidency, these views have changed a lot.

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Speaker 2: Yeah, they can't, you know. So blame this on just

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Speaker 2: bad media coverage, which of course I do think deserves

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Speaker 2: some blame, like media loves to talk down the economy

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Speaker 2: and Republican as president. But it can't just be that

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Speaker 2: Americans need to be feeling some other sensation here that

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Speaker 2: isn't being picked up in the actual numbers. And I

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Speaker 2: wonder maybe that is just AI on the very near

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Speaker 2: horizon moving towards us and people understanding that things are

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Speaker 2: going to get tough. I think before you know, if

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Speaker 2: they get better, I wanted to say before they get better,

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Speaker 2: but that's not a given. This is something really different,

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Speaker 2: and I don't know if that's really what it is.

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Speaker 2: If Americans are seeing the AI thing coming at them

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Speaker 2: and thinking like things are about to get really rough

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Speaker 2: and we're not going to get into this. But there

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Speaker 2: was a big piece today out by this guy named

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Speaker 2: Matt Schumer, and he said, something big is happening is

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Speaker 2: the name of the piece if you want to look

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Speaker 2: it up, but it's about how AI is here and

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Speaker 2: we need to like really reckonize what that means. And

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Speaker 2: he compares it to you know, the water rushing in

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Speaker 2: and suddenly it's around your chest and you don't realize that.

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Speaker 2: And that's where we are with AI. Maybe Americans know that.

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Speaker 1: Yeah, I do think there's some anxiety about that. And

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Speaker 1: it's sort of ironic because AI. I think probably a

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Speaker 1: little bit of a bubble is propping up some of

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Speaker 1: the accompany in the markets, but then it might be

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Speaker 1: making people anxious when.

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Speaker 3: They look at the outlook for their own lives.

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Speaker 1: And you know, he can keep messaging this consistently as

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Speaker 1: they should all year long, but yes, I do think

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Speaker 1: there's there's something else going on here, and if you

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Speaker 1: have Democrat enthusiasm against Trump plus the falloff in independence,

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Speaker 1: that's a really bad recipe for a midterm that was

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Speaker 1: already going to be hard. Right, although say I should

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Speaker 1: say this started in If it started in January twenty

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Speaker 1: twenty five, it's like, okay, well, this is like the

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Speaker 1: very beginning of your job.

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Speaker 3: So yeah, it's like it's like he hadn't done anything yet.

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Speaker 1: But I do think there's there's something more going on

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Speaker 1: there that they must heed at the White House, because

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Speaker 1: they need to speak to people's actual feelings about this

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Speaker 1: instead of only throwing numbers at them, which is what

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Speaker 1: Biden tried to do too many times.

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Speaker 3: He said like, oh no, this is healthy. Look how

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Speaker 3: healthy this is? Right, But if people don't feel it.

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Speaker 2: That doesn't matter. You're up a break exactly. Another issue

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Speaker 2: is that crime is down significantly, and that's also being

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Speaker 2: obviously talked about in a way that is very specific

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Speaker 2: to the Trump administration. Axios had to remove a post

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Speaker 2: of a story that noted that violent crime dropped sharply

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Speaker 2: across America's biggest cities in twenty twenty five, and he

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Speaker 2: had to they we've bleaded a previous post of the story,

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Speaker 2: which compared the drop in violent crime to Trump's arguments

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Speaker 2: for deploying federal troops to US cities, because the headline

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Speaker 2: was like, despite Trump's entry into these cities.

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Speaker 1: Despite Trump's cracked down on crime, right, crime down down?

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Speaker 2: Yeah, yeah, and yeah. It's interesting the way that it

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Speaker 2: all gets portrayed. Press Secretary Caroline love It said, this

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Speaker 2: ridiculous framing is why Americans don't trust the media. President Trump,

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Speaker 2: securing the border, mobilizing federal law enforcement to arrest violent criminals,

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Speaker 2: and deporting the worst of the worst illegal aliens is

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Speaker 2: exactly what's driving the massive drop in crime. The headline

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Speaker 2: again was crime plunges in major cities despite Trump's crackdown rhetoric.

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Speaker 3: Like, O, guys, that's what's happening here, right.

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Speaker 1: And the thing is, I do I do think people

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Speaker 1: the homicide drop alone while at crime in general, but

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Speaker 1: the homicide drop alone is such a huge story. Now,

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Speaker 1: it did go up during the twenty twenty to twenty

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Speaker 1: three insanity period.

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Speaker 3: But because of liberal policies.

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Speaker 1: And now it's coming down because someone did the opposite.

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Speaker 3: That's what happened, and there.

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Speaker 2: Are some liberals waking up to this, Philopovic tweeted, one

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Speaker 2: of the things I've really changed my mind on is

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Speaker 2: public order enforcement. I think a lot of liberals, like

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Speaker 2: me assumed people do things like turnstile jumping, we're poor

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Speaker 2: or just kids. But it seems like actually a small

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Speaker 2: number of people just do a lot of antisocial shit.

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Speaker 2: And she was responding to a graph that showed that

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Speaker 2: San Francisco's BART, that's their public transportation system, installed anti

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Speaker 2: fair hopping gates and the person rights the amount of

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Speaker 2: station maintenance and cleanup they had to do went to

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Speaker 2: basically zero. So the people who were jumping and not

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Speaker 2: jumping the turnstiles and not paying the fair were also

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Speaker 2: the ones destroying the train station. And you're like, have

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Speaker 2: you heard of Rudy Giuliani and this broken windows theory?

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Speaker 2: Because we knew this in the nineties. Why are you

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Speaker 2: guys so far behind? And why is it such a

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Speaker 2: battle for you to face reality when it's not what

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Speaker 2: you wanted it to be. I think, you know, conservatives

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Speaker 2: change their minds on stuff when new data presents itself.

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Speaker 8: I wish liberals did that a little bit faster faster. Yeah,

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Speaker 8: there is a preference just to honor the criminal. There's

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Speaker 8: just a reflexive need on the left to go, well,

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Speaker 8: surely this person's rights are important, this person's story makes

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Speaker 8: them sympathetic. This person should be placed in a hierarchy

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Speaker 8: above a person who would just like to ride the

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Speaker 8: bart in peace. But that's not how normal people think.

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Speaker 8: That's how weirdo ideological people think.

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Speaker 3: And it was.

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Speaker 1: The Washington Metro has improved greatly because they've got a

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Speaker 1: general manager who thinks that fair evasions should be cracked

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Speaker 1: down upon, and as a result, it's much nicer to

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Speaker 1: ride the Metro. It does the job it's supposed to do,

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Speaker 1: far better than it did a couple of years ago.

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Speaker 3: And he said, not all fair skippers.

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Speaker 1: Commit violent crime and vandalism, but all people who commit

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Speaker 1: violent crime and vandalism skipped their fair Yep.

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Speaker 2: I'm telling you, I think Rudy Giuliani might have said

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Speaker 2: those exact words in like nineteen ninety five. But okay,

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Speaker 2: so it's fine, it's fine, and we'll just, you know,

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Speaker 2: get to it a little later.

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Speaker 3: Here learn the lesson again. How many pandemics will it

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Speaker 3: take to learn the lesson? One wonders. Anyway, I don't

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Speaker 3: want to get too dark.

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Speaker 2: Yeah. Jill also tweeted about Washington, DC, and she said

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Speaker 2: that there was an article in the Washington Post that

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Speaker 2: basically found that some huge percentage of crime in Washington,

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Speaker 2: d C. Was committed by like three hundred people, just

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Speaker 2: thousands and thousands of crimes by people who crimed over

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Speaker 2: and over and over again. It's like, yeah, yes, what

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Speaker 2: we know about this?

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Speaker 1: Yes, and you revolving dured them for years and years

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Speaker 1: and years to trample the rights of everyone else in

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Speaker 1: your city. It is a wild thing that they have

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Speaker 1: been in favor of.

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Speaker 2: Not great. And if we could just I mean I

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Speaker 2: say we, but I mean them, if they could just

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Speaker 2: let go of blaming making sure that Donald Trump doesn't

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Speaker 2: receive credit for anything, we could all live better.

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Speaker 3: Yeah.

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Speaker 2: If we just follow policies that have worked before, despite

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Speaker 2: Trump being in support of them, that would be a

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Speaker 2: good thing.

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Speaker 1: Well, and even if you're a person who has some

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Speaker 1: misgivings about, okay, how is this being conducted right on

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Speaker 1: the margins in National Guard or with whomever, one must

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Speaker 1: admit nonetheless that a one hundred year low in some

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Speaker 1: places in homicides is good.

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Speaker 3: That the city of DC going many weeks without a

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Speaker 3: murder at a time is good that I believe that. Yeah.

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Speaker 1: The fact that I can go to Union Station and

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Speaker 1: not be harassed or possibly threatened is good.

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Speaker 2: Yeah.

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Speaker 3: People like that.

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Speaker 2: I like that. I like when no crime is committed

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Speaker 2: around me. It's just it's a plus for me.

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Speaker 3: It's a plus. It's a plus.

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Speaker 2: All Right, We're going to take a short break and

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Speaker 2: come back to the biggest story in the normy world,

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Speaker 2: which we have not talked about at all, the disappearance

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Speaker 2: of Nancy Guthrie, the mom of Savannah Guthrie, And we'll.

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Speaker 3: Be right back to discuss that.

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Speaker 2: We are back on normally. Where Nancy Guthrie has been

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Speaker 2: missing for today is twelve days. By the time you

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Speaker 2: hear this, it might be thirteen days. And a local

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Speaker 2: delivery driver was taken into custody and questioned for several

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Speaker 2: hours on Tuesday about the abduction, but then he was released.

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Speaker 2: He seemed to be very surprised about being taken in.

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Speaker 2: He had not heard of the TV personality or her mom,

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Speaker 2: And yeah, they really have seemed to have no leads.

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Speaker 2: Is where this is now? The thing is that I

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Speaker 2: hear from a lot of people, why is this such

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Speaker 2: a big story, and I have to say, I think

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Speaker 2: this should be a big story. I am not a

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Speaker 2: true crime I'm person in any way, so I'm not

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Speaker 2: like following this with all the details, and I'm not

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Speaker 2: trying to find the real killer or you know, kidnapper

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Speaker 2: in this case with everybody. But I absolutely think a

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Speaker 2: woman in her eighties taken out of her home, possibly

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Speaker 2: for because her daughter is famous and they want to

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Speaker 2: have a ransom. Yes, I do think that should be

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Speaker 2: a story. She's eighty four years old and kidnapped from

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Speaker 2: her house. Blood on the porch. Yeah, I think that

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Speaker 2: deserves to be a large national story where we don't

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Speaker 2: shrug our shoulders and say, yeah, kidnapped senior citizen, what

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Speaker 2: are you going to do?

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Speaker 3: Yeah?

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Speaker 1: Well, I think it might shine light on other instances

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Speaker 1: where this happened that have gotten less attention. I think

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Speaker 1: a lot of people feel connected to Savannah Gusrie, particularly

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Speaker 1: when you do a morning show. I did a morning

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Speaker 1: show on radio for a couple of years or even

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Speaker 1: I think it's just for one year. It was many

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Speaker 1: years ago. People still identify me with that morning show

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Speaker 1: because when you wake up with a personality and you're

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Speaker 1: hearing about their life every day and you're connecting with

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Speaker 1: them while you're having your coffee. It is a It

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Speaker 1: is a real thing. It's the parasocial relationship. So I

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Speaker 1: think a lot of people feel connected to Spannah Guthrie.

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Speaker 1: They see their mother in her mother and the fright

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Speaker 1: over the idea that this could happen. It's also there's

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Speaker 1: a lot of intrigue that there's been rumors that it

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Speaker 1: might be a family member. There's are rumors that it

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Speaker 1: could be based on Savannah being famous. There are video

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Speaker 1: of Savannah and her brothers and sisters speaking to camera

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Speaker 1: trying to reach the person who might be holding their mother. Right.

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Speaker 1: There's a lot here, and there are a lot of

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Speaker 1: ambusur sleuths who want to get tautamas. I likes I

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Speaker 1: like you am sort of like non normy on this

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Speaker 1: because I am not bought in on true crime as

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Speaker 1: it's happening. If you give me a documentary with all

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Speaker 1: the facts later, I will watch it.

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Speaker 3: But I get a.

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Speaker 1: Little nervous about the speculation and being careful about these

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Speaker 1: things while it's happening.

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Speaker 3: But uh, the you know, the ring camera video of

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Speaker 3: a man coming to.

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Speaker 1: Her door very very creepy with a mask on, possibly

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Speaker 1: two masks on. It's very unclear whether that where you

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Speaker 1: can see his eyes are actually his eyes. If so,

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Speaker 1: he has very distinctively groomed eyebrows. So look into that everybody,

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Speaker 1: and it's very creepy. I would also add, just as

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Speaker 1: an addendum to our topic the other day, the ring camera.

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Speaker 1: She did not have a subscription that she was paying

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Speaker 1: for and have it anyway.

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Speaker 3: FBI nonetheless has the videos.

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Speaker 1: Just that's why I everyone it's definitely just for looking

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Speaker 1: for dogs anyway.

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Speaker 5: I am.

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Speaker 1: I am glad if it helps in this case, but

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Speaker 1: that was an interesting good of information for me, and

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Speaker 1: I really hope she can get home safe.

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Speaker 3: This is a very scary situation.

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Speaker 2: Absolutely.

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Speaker 3: Yeah.

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Speaker 2: The thing is, it's so scary that it's been so

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Speaker 2: long and they have very little to go on. But yeah,

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00:20:47,800 --> 00:20:51,399
Speaker 2: we're obviously praying for her safe return. We're not going

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Speaker 2: to be sensationalizing it here and talking about possible motives

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Speaker 2: and situations when nobody really seems to know anything. Yeah, well,

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00:21:00,000 --> 00:21:01,240
Speaker 2: well she gets home.

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Speaker 1: I wanted to add one thing that our friend Nancy Rammelman,

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Speaker 1: who is a great follow on ex at Nancy ram Romm.

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Speaker 1: She wrote a piece that sort of it fits in

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Speaker 1: with this, like all of our worries about our elderly

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Speaker 1: relatives as they age and if they're alone. She wrote

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Speaker 1: a piece for Real Clear Investigations called Caring for Mom

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Speaker 1: as an Education in scams and fraud. And this is

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Speaker 1: a freight train that is coming for the aging population.

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Speaker 1: Oh yeah, the AI voice scams. I mean people were

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Speaker 1: doing scams on the elderly over the phone without the

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Speaker 1: AI voice technology, and it is going to get worse.

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Speaker 1: And I do think there are ways that with code

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Speaker 1: words and such, you can protect your loved ones and

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Speaker 1: try to be as proactive about educating people as possible

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Speaker 1: on these fronts. So I would recommend that as a

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Speaker 1: read as we think about, Yeah, these worries as we

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Speaker 1: move forward.

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Speaker 2: Absolutely have a conversation with anybody in your life. I

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Speaker 2: would say old or young, because there's always these stories

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Speaker 2: about like a thirty something who ends up giving away

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Speaker 2: their life savings and you know, to a scammer on

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Speaker 2: the phone. It's older people are definitely more susceptible to

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Speaker 2: these scams. But I think I've had this conversation definitely

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Speaker 2: with my mom, but also with you know, friends my

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Speaker 2: age and also with my children. Just don't somebody calls

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Speaker 2: you and it sounds like me, or it sounds like

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Speaker 2: someone you know. Hang up, call that person back, It

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Speaker 2: doesn't matter. Just hang up and call call the person

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Speaker 2: that they're claiming to be. Yes, but don't believe anything.

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Speaker 2: Don't answer your phone is actually my message, and like, well,

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Speaker 2: don't believe and have them leave a message.

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Speaker 3: A good A good one to a good.

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Speaker 1: Rule of some I think is not to always believe

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Speaker 1: the sense of urgency from whatever rando is calling you

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00:22:43,359 --> 00:22:46,280
Speaker 1: on your phone, because they inculcate a sense of urgency

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Speaker 1: on purpose so that you then start to panic about

441
00:22:49,359 --> 00:22:51,920
Speaker 1: whatever this situation is, and that sort of shuts off

442
00:22:51,920 --> 00:22:53,040
Speaker 1: the thinking part of your brain.

443
00:22:53,200 --> 00:22:55,000
Speaker 3: I almost got fished the other day by the Kurt

444
00:22:55,000 --> 00:22:55,600
Speaker 3: Loader hack.

445
00:22:55,920 --> 00:22:58,359
Speaker 1: I was like, oh yeah, let me help out Kurt Loader,

446
00:22:58,359 --> 00:23:00,280
Speaker 1: and then I was like, Kurt Loader doesn't be my help?

447
00:23:00,280 --> 00:23:02,800
Speaker 2: What is that? I was like, you would never, I mean,

448
00:23:02,960 --> 00:23:05,199
Speaker 2: none of your friends would ever DM you and be

449
00:23:05,280 --> 00:23:07,800
Speaker 2: like vote for me in this contest. In fact, you

450
00:23:08,080 --> 00:23:11,720
Speaker 2: know which friends would and it wouldn't be you know

451
00:23:11,800 --> 00:23:12,240
Speaker 2: what I mean.

452
00:23:13,359 --> 00:23:16,919
Speaker 1: I'm thinking of them now, I do wish for a

453
00:23:17,000 --> 00:23:20,480
Speaker 1: safe resolution to this. It's very bizarre. And I was

454
00:23:20,520 --> 00:23:25,040
Speaker 1: down in Richmond lobbying my legislatures, not state legislators, not

455
00:23:25,119 --> 00:23:27,000
Speaker 1: to ruin private schooling because that's what they're up to

456
00:23:27,040 --> 00:23:27,600
Speaker 1: in Virginia.

457
00:23:27,760 --> 00:23:28,000
Speaker 2: Hmm.

458
00:23:28,280 --> 00:23:30,000
Speaker 1: They want to just turn it into public schools, which

459
00:23:30,040 --> 00:23:31,800
Speaker 1: is fun since they failed us for a couple of years.

460
00:23:31,840 --> 00:23:33,800
Speaker 1: But anyway, I was down there talking to the normies

461
00:23:33,800 --> 00:23:35,080
Speaker 1: and guess what the normies first.

462
00:23:34,840 --> 00:23:38,520
Speaker 3: Asked me about Nancy Guthrie. Wow, that's what everybody wants

463
00:23:38,560 --> 00:23:39,080
Speaker 3: to talk about.

464
00:23:39,160 --> 00:23:41,760
Speaker 2: Well, if we hear anything else, we'll have more news

465
00:23:41,800 --> 00:23:45,760
Speaker 2: in the next few episodes, but for now, which pray

466
00:23:45,760 --> 00:23:49,880
Speaker 2: for the Guthrie family. Yeah, be right back with more

467
00:23:50,040 --> 00:23:57,960
Speaker 2: on Normally. We are back on Normally where reports last

468
00:23:58,040 --> 00:24:03,760
Speaker 2: week revealed that to forty percent of students at Stanford University,

469
00:24:03,880 --> 00:24:07,240
Speaker 2: one of the top top schools in the country, are

470
00:24:07,320 --> 00:24:10,320
Speaker 2: claiming to have a disability in order to get special

471
00:24:10,320 --> 00:24:14,720
Speaker 2: accommodations and that stuff like more time on tests or

472
00:24:15,720 --> 00:24:20,480
Speaker 2: extra time to study things like that. It's really insane

473
00:24:21,040 --> 00:24:24,879
Speaker 2: that the numbers are this high, and it frankly sounds

474
00:24:24,960 --> 00:24:27,480
Speaker 2: like a lot of them just make it up. They

475
00:24:27,520 --> 00:24:30,440
Speaker 2: get things like being alone in a room on a

476
00:24:30,520 --> 00:24:36,359
Speaker 2: t to take test or exemptions from certain requirements. It's bananas.

477
00:24:36,400 --> 00:24:39,520
Speaker 2: And again Stanford and at schools at Brown and Harvard,

478
00:24:39,920 --> 00:24:43,399
Speaker 2: more than twenty percent now register as disabled in this

479
00:24:43,520 --> 00:24:44,560
Speaker 2: way well.

480
00:24:44,560 --> 00:24:47,320
Speaker 3: And they also get sometimes their own room.

481
00:24:47,600 --> 00:24:49,840
Speaker 1: If they have social anxiety, they get a solar room,

482
00:24:49,880 --> 00:24:52,560
Speaker 1: which used to be very sought after and kind of

483
00:24:52,720 --> 00:24:55,679
Speaker 1: the slope here. The slippery slope here has been The

484
00:24:56,240 --> 00:24:59,520
Speaker 1: Americans Disabilities Act in nineteen ninety was supposed to allow

485
00:24:59,560 --> 00:25:02,280
Speaker 1: for many important accommodations for people to be able to

486
00:25:02,280 --> 00:25:04,800
Speaker 1: get into buildings to be part of higher education when

487
00:25:04,840 --> 00:25:07,800
Speaker 1: they couldn't before, and then in two thousand and eight

488
00:25:08,200 --> 00:25:11,200
Speaker 1: they sort of widened it and encouraged people to include

489
00:25:11,800 --> 00:25:18,200
Speaker 1: other more lax medical diagnoses mental health issues, psychological health issues,

490
00:25:18,680 --> 00:25:22,760
Speaker 1: and as the number of people who either self diagnosed

491
00:25:22,800 --> 00:25:26,160
Speaker 1: or are diagnosed with these ADHD with anxiety, with depression,

492
00:25:26,200 --> 00:25:29,600
Speaker 1: as that goes up in these elite colleges, it becomes

493
00:25:29,640 --> 00:25:33,240
Speaker 1: the way to compete is that you end up getting

494
00:25:33,280 --> 00:25:36,440
Speaker 1: more help and more accommodations because if you claim this,

495
00:25:36,880 --> 00:25:38,919
Speaker 1: which is pretty easy to do, they've taken all the

496
00:25:39,000 --> 00:25:41,040
Speaker 1: verification requirements down quite a bit.

497
00:25:41,440 --> 00:25:42,760
Speaker 3: Then there you are.

498
00:25:42,800 --> 00:25:45,760
Speaker 1: You're off to the races with not the same hurdles

499
00:25:46,160 --> 00:25:48,919
Speaker 1: as a student who doesn't claim any of these things.

500
00:25:49,440 --> 00:25:52,560
Speaker 1: And there's an Atlantic piece on this that notes if

501
00:25:52,560 --> 00:25:55,040
Speaker 1: the rise and accommodations were purely a result of more

502
00:25:55,040 --> 00:25:57,760
Speaker 1: disabled students making it to college, the increase would be

503
00:25:57,760 --> 00:26:01,000
Speaker 1: more pronounced at less selective institutions than so called ivy

504
00:26:01,000 --> 00:26:04,760
Speaker 1: Bluss schools. In fact, the opposite appears to be true.

505
00:26:05,040 --> 00:26:08,640
Speaker 1: According to Robert Weiss, he's a psychology professor's research, only

506
00:26:08,680 --> 00:26:10,920
Speaker 1: three to four percent of students at public two years

507
00:26:11,480 --> 00:26:14,680
Speaker 1: two year colleges receive accommodations, a proportion that has stayed

508
00:26:14,680 --> 00:26:17,479
Speaker 1: relatively stable over the past ten to fifteen years. So

509
00:26:18,280 --> 00:26:21,640
Speaker 1: it's definitely still in those areas.

510
00:26:21,760 --> 00:26:24,280
Speaker 2: Yeah, so I have you know, I have a son

511
00:26:24,320 --> 00:26:28,880
Speaker 2: who gets accommodations and often chooses not to, which also

512
00:26:28,960 --> 00:26:32,760
Speaker 2: drives me crazy. But you know that's the thing. The

513
00:26:32,800 --> 00:26:35,719
Speaker 2: people who get like say extra time on tests, like

514
00:26:36,119 --> 00:26:38,440
Speaker 2: they're often like, I don't want it. I don't want

515
00:26:38,480 --> 00:26:40,880
Speaker 2: to be different from my classmates. But then you get

516
00:26:40,920 --> 00:26:44,040
Speaker 2: to this like cutting, you know, cutthroat environment, and they're like,

517
00:26:44,119 --> 00:26:45,680
Speaker 2: I do want it. I want to I want to

518
00:26:45,720 --> 00:26:49,359
Speaker 2: be better than my classmates at any cost. Yes, And

519
00:26:49,400 --> 00:26:51,840
Speaker 2: the thing is that, like, of course, that you can

520
00:26:51,880 --> 00:26:55,199
Speaker 2: concentrate better if you're sitting in your own room. My

521
00:26:55,280 --> 00:26:59,240
Speaker 2: other son was that he's really into history. He goes

522
00:26:59,240 --> 00:27:01,879
Speaker 2: to these history comps Petitians, and last week we were

523
00:27:01,920 --> 00:27:03,720
Speaker 2: at a history competition and I was like, Oh, I

524
00:27:03,720 --> 00:27:05,920
Speaker 2: feel like he's going to like smoke these other kids.

525
00:27:06,160 --> 00:27:08,159
Speaker 2: And then this kid like starts talking to him like

526
00:27:08,240 --> 00:27:10,879
Speaker 2: just making friends banter, and I'm like, oh, it's over this.

527
00:27:11,040 --> 00:27:13,240
Speaker 2: He's going to be so focused on this new friend

528
00:27:13,600 --> 00:27:17,280
Speaker 2: that he's like yeah, and he came in second. But

529
00:27:17,359 --> 00:27:19,480
Speaker 2: I'm just saying, had he not made a new friend,

530
00:27:19,520 --> 00:27:20,040
Speaker 2: he would.

531
00:27:19,800 --> 00:27:23,720
Speaker 3: Have been in first. That's amazing, you know, all right, but.

532
00:27:23,680 --> 00:27:26,000
Speaker 2: At least he knows how to make friends. You gotta

533
00:27:26,040 --> 00:27:28,520
Speaker 2: say that. That's like, you know, that's more important, right

534
00:27:28,560 --> 00:27:29,480
Speaker 2: than coming in first.

535
00:27:29,600 --> 00:27:31,520
Speaker 1: He's not going to turn out like one of these

536
00:27:31,560 --> 00:27:34,480
Speaker 1: students in this Atlantic story that one administrator told me

537
00:27:34,480 --> 00:27:36,320
Speaker 1: that a student at a public college in California had

538
00:27:36,320 --> 00:27:38,959
Speaker 1: permission to bring their mother to class. This became a

539
00:27:38,960 --> 00:27:41,480
Speaker 1: problem because the mom turned out to be an enthusiastic

540
00:27:41,480 --> 00:27:43,960
Speaker 1: class participant. Actually that kid of yours might enjoy that

541
00:27:43,960 --> 00:27:46,440
Speaker 1: accommodation and you participated in class.

542
00:27:46,480 --> 00:27:50,639
Speaker 2: No, no, no, he would enjoy it and I would not.

543
00:27:52,640 --> 00:27:54,880
Speaker 1: They also note, and I think this is important that

544
00:27:55,080 --> 00:27:56,840
Speaker 1: and I think it comes from social media. A lot

545
00:27:56,920 --> 00:28:00,800
Speaker 1: of these students are starting to view this as the identity,

546
00:28:01,960 --> 00:28:06,040
Speaker 1: and by the time colleges see them, they've self diagnosed

547
00:28:06,400 --> 00:28:10,600
Speaker 1: with neurodevelopmental disorders that they may not even have.

548
00:28:11,560 --> 00:28:11,800
Speaker 3: Yeah.

549
00:28:11,840 --> 00:28:14,600
Speaker 1: True, this is byttributing all their difficulties to a disability.

550
00:28:14,600 --> 00:28:18,359
Speaker 1: They are pathologizing normal challenges, which is the thing that

551
00:28:18,400 --> 00:28:20,320
Speaker 1: we see over and over again that worries us and

552
00:28:20,359 --> 00:28:22,120
Speaker 1: that I refuse to do with my kids.

553
00:28:22,640 --> 00:28:25,520
Speaker 2: Yeah, that's the thing. It's like, you don't want them

554
00:28:25,560 --> 00:28:29,840
Speaker 2: to internalize their struggles and turn it into their personality.

555
00:28:30,040 --> 00:28:31,920
Speaker 2: And the fact that some of these kids don't even

556
00:28:31,960 --> 00:28:34,920
Speaker 2: have struggles and that becomes their whole personality, it's kind

557
00:28:34,920 --> 00:28:38,200
Speaker 2: of a problem. I forgot the name of the comedian

558
00:28:38,240 --> 00:28:41,040
Speaker 2: on SNL, but he said, like him and his sister

559
00:28:41,200 --> 00:28:43,520
Speaker 2: tried to get depression, but their mom wouldn't let them

560
00:28:43,560 --> 00:28:44,760
Speaker 2: because she was an immigrant.

561
00:28:45,320 --> 00:28:49,720
Speaker 3: She was like, like, you're depressed. No, yes, he's fantastic.

562
00:28:51,040 --> 00:28:55,959
Speaker 2: Yeah, so good. Also at Stanford, they are doing an

563
00:28:56,000 --> 00:29:01,440
Speaker 2: experiment where they built a match making algorithm. A student

564
00:29:01,480 --> 00:29:04,640
Speaker 2: built a match making algorithm and it has consumed the

565
00:29:04,680 --> 00:29:08,960
Speaker 2: school because every week singles get a match in their

566
00:29:09,720 --> 00:29:14,640
Speaker 2: you know, inbox and you're matched with somebody, and it's

567
00:29:14,880 --> 00:29:18,240
Speaker 2: become such a huge deal. Matches drop every Tuesday night.

568
00:29:18,440 --> 00:29:21,320
Speaker 2: Students huddle in dorm rooms and libraries to find out

569
00:29:21,360 --> 00:29:24,840
Speaker 2: who the algorithm chose for them. It's a real big

570
00:29:24,880 --> 00:29:29,480
Speaker 2: deal and it's interesting because they're so excited about this

571
00:29:29,880 --> 00:29:33,280
Speaker 2: and it is clearly because they don't know how to

572
00:29:33,320 --> 00:29:37,040
Speaker 2: meet people on their own. I love it because why not, like,

573
00:29:37,080 --> 00:29:39,120
Speaker 2: at least you get a chance to meet somebody, at

574
00:29:39,200 --> 00:29:41,120
Speaker 2: least you have a chance at having a date and

575
00:29:41,160 --> 00:29:44,480
Speaker 2: all of that. But it's wild that this is where

576
00:29:44,480 --> 00:29:46,800
Speaker 2: we are, like here is your date for the week.

577
00:29:47,680 --> 00:29:48,040
Speaker 3: Yeah.

578
00:29:48,200 --> 00:29:51,520
Speaker 1: I'm always torn on these things because I don't begrudge

579
00:29:51,560 --> 00:29:54,040
Speaker 1: a new tool for meeting people, right, I think that's

580
00:29:54,280 --> 00:29:56,480
Speaker 1: you know, but I think we did get so far

581
00:29:56,520 --> 00:29:59,720
Speaker 1: into optimization, and we get so far into so many choices.

582
00:30:00,120 --> 00:30:03,040
Speaker 1: But then you're like you're always doing the grasses greener thing.

583
00:30:03,560 --> 00:30:08,080
Speaker 1: You're not really evaluating, You're not enjoying these dates. I

584
00:30:08,120 --> 00:30:11,200
Speaker 1: do hope that maybe it encourages more people to when

585
00:30:11,240 --> 00:30:13,200
Speaker 1: they get that prompt to go maybe I should go

586
00:30:13,240 --> 00:30:15,560
Speaker 1: out in real life and hang out with this person.

587
00:30:16,160 --> 00:30:18,960
Speaker 1: But I hate to sound like an old fogy, but man,

588
00:30:19,400 --> 00:30:21,200
Speaker 1: you just really used to go to the bar and

589
00:30:21,240 --> 00:30:22,200
Speaker 1: say hi to people.

590
00:30:22,440 --> 00:30:25,680
Speaker 3: That was Yeah, the algorithm did not do it for.

591
00:30:25,560 --> 00:30:28,280
Speaker 2: You, right, And the thing is that they're using the

592
00:30:28,360 --> 00:30:31,720
Speaker 2: algorithm to talk to people who they already like in

593
00:30:31,760 --> 00:30:35,320
Speaker 2: real life. So here's a story of freshman Wilson Adkins

594
00:30:35,400 --> 00:30:37,760
Speaker 2: began chatting with a girl from his dorm just as

595
00:30:37,840 --> 00:30:39,920
Speaker 2: date dropped this is the name of the app was

596
00:30:39,960 --> 00:30:43,360
Speaker 2: getting buzz. His friends took notice. A feature allows users

597
00:30:43,360 --> 00:30:46,080
Speaker 2: to couple two people to boost their odds of matching.

598
00:30:46,640 --> 00:30:49,000
Speaker 2: Students get an email alert if their friends propose a

599
00:30:49,040 --> 00:30:51,640
Speaker 2: match for them. Adkins got three. At once, I knew

600
00:30:51,640 --> 00:30:54,719
Speaker 2: they were conspiring, he said. Sure enough, Adkins and his

601
00:30:54,720 --> 00:30:57,280
Speaker 2: classmate were paired with a ninety nine point seven percent

602
00:30:57,640 --> 00:31:00,360
Speaker 2: compatibility score. So now it looks like I had been

603
00:31:00,400 --> 00:31:03,960
Speaker 2: scheming and forcing this to happen, Atkins said, But now

604
00:31:04,360 --> 00:31:08,400
Speaker 2: they're hanging out. So yeah, if you didn't need the app,

605
00:31:08,480 --> 00:31:10,760
Speaker 2: you were already talking well.

606
00:31:10,800 --> 00:31:14,080
Speaker 1: And also that seems like just an old version of

607
00:31:14,320 --> 00:31:15,640
Speaker 1: peer pressure put online.

608
00:31:15,680 --> 00:31:17,480
Speaker 3: Like in the old days, they just be like, y'all

609
00:31:17,520 --> 00:31:18,000
Speaker 3: like each other.

610
00:31:18,400 --> 00:31:20,400
Speaker 1: They tease you about it, right, and then these two

611
00:31:20,400 --> 00:31:22,400
Speaker 1: people would actually talk to each other if they were

612
00:31:22,440 --> 00:31:23,160
Speaker 1: nervous before.

613
00:31:23,640 --> 00:31:27,160
Speaker 2: They called it shipping, Mary Catherine, I learned that from

614
00:31:27,160 --> 00:31:30,960
Speaker 2: my teenagers. They ship their friends like the shift their friends.

615
00:31:31,000 --> 00:31:32,920
Speaker 3: Well, yep, I guess you can do it on an

616
00:31:32,920 --> 00:31:33,640
Speaker 3: app now.

617
00:31:34,800 --> 00:31:37,040
Speaker 2: Yeah, but you can do it without the app, you

618
00:31:37,160 --> 00:31:40,080
Speaker 2: really could. Whatever whatever way you crazy kids need to

619
00:31:40,080 --> 00:31:43,440
Speaker 2: make it happen. You know, go meet some people in

620
00:31:43,480 --> 00:31:45,800
Speaker 2: real life life, even if you have to meet them

621
00:31:45,800 --> 00:31:46,640
Speaker 2: online first.

622
00:31:47,120 --> 00:31:49,480
Speaker 3: Yeah. Just get out there, man, You can.

623
00:31:49,360 --> 00:31:52,480
Speaker 2: Get out there.

624
00:31:53,160 --> 00:31:53,880
Speaker 3: That you made up.

625
00:31:56,040 --> 00:31:59,480
Speaker 2: Thanks for joining us on Normally Normally airs Tuesdays and Thursdays,

626
00:31:59,480 --> 00:32:02,560
Speaker 2: and you can subscribe anywhere you get your podcasts. Get

627
00:32:02,560 --> 00:32:06,240
Speaker 2: in touch with us at normallythepod at gmail dot com.

628
00:32:06,240 --> 00:32:09,280
Speaker 2: Thanks for listening and when things get weird at normally