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Speaker 1: Hello the Internet, and welcome to this episode of the

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Speaker 1: Weekly Zeitgeist.

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Speaker 2: Uh.

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Speaker 1: These are some of our favorite segments from this week,

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Speaker 1: all edited together into one NonStop infotainment laugh stravaganza.

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Speaker 2: Uh yeah.

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Speaker 1: So, without further ado, here is the Weekly Zeitgeist.

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Speaker 2: Miles.

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Speaker 1: We are thrilled to be joined by an acclaimed wildlife

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Speaker 1: ecologist and conservationist who specializes in researching how human activity

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Speaker 1: influences the behavior of wild animals. M m She's a

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Speaker 1: TV host and the host of the PBS Nature podcast

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Speaker 1: Going Wild with Doctor ray Wing Grant, which makes sense

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Speaker 1: because she is doctor ray Win Grant.

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Speaker 2: I'm here here, welcome back.

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Speaker 3: Oh I really love having so many memories.

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Speaker 2: Yeah. Yeah, we loved having you last time. And we're like,

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Speaker 2: now that we're talking to experts, let's talk to it.

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Speaker 2: Let's really digging into a real expert.

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Speaker 1: Yeah, let's spend some time doing some research and like

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Speaker 1: just you know, really square up, make ourselves seem extremely smart.

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Speaker 2: And that's what we're doing.

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Speaker 1: We put put our brains together and have put together

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Speaker 1: a list of some of the hardest hitting, science based,

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Speaker 1: deeply researched, science based questions in your area of expertise.

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Speaker 3: This is like my all over again.

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Speaker 2: Yeah, yeah, it is exactly. This is on and it's

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Speaker 2: going to be on the record, right right, are high

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Speaker 2: stays incredibly high?

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Speaker 1: So we're going to get to that in a moment,

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Speaker 1: But before we do, we still like to ask our guests,

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Speaker 1: what is something from your search history that's revealing about

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Speaker 1: who you are or what you're up to.

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Speaker 3: Oh, well, I have something. I hope this can kind

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Speaker 3: of be the great equalizer. Perhaps because I'm a scientist, right,

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Speaker 3: I'm an environmental scientist, a wildlife ecologist. I have all

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Speaker 3: this expertise, and yet ever so often I have to google,

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Speaker 3: like the simpler things just to make sure that I'm

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Speaker 3: explaining it correctly. So two weeks ago, I was with

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Speaker 3: a film crew and filming a television show. It's called

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Speaker 3: Wild Kingdom. It's great. You can watch it's on NBC

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Speaker 3: streaming on Peacock. And I was with the crew and

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Speaker 3: we were in a place I mean, I gotta gotta

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Speaker 3: sneak it in. We were in Texas, or in Central Texas,

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Speaker 3: in a place that has dinosaur footprints, right, Like this

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Speaker 3: part of Central Texas used to be an ocean. And

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Speaker 3: then at the point that there were these dinosaurs. It

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Speaker 3: was like more of a swamp and they sunk their

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Speaker 3: giant feet into the mud and then it just like

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Speaker 3: there was a drought and they just solidified and they're

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Speaker 3: still there. It's amazing. So talking to the crew about dinosaurs,

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Speaker 3: this is just like rural central Texas too. And somehow

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Speaker 3: we got into the topic of fossil fuels and one

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Speaker 3: of the producers on the show didn't know where fossil

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Speaker 3: fuels came from, Like she didn't understand the word fossil

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Speaker 3: that's part of fossil frut. So fossil fuels are like

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Speaker 3: you know, the gas you put in your car is

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Speaker 3: a type of fossil fuel, right right, It's what's contributing

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Speaker 3: to climate change. And so I was explained to her, like, girl, yeah,

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Speaker 3: it's when dinosaurs lived and then they died. Their bodies

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Speaker 3: decomposed and sunk into the earth. But because it's been

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Speaker 3: millions of years, those decomposed dinosaur bodies have liquefied because

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Speaker 3: it's so hot down there and turned into essentially like

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Speaker 3: oil that we drill up and used to put in

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Speaker 3: our cars and used to you know, power stuff, and

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Speaker 3: we've you know, contaminated the whole atmosphere because of it,

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Speaker 3: and her mind was blown to the point that I

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Speaker 3: started getting like a little bit concerned. I was like,

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Speaker 3: that is that right?

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Speaker 2: So that what we would sometimes call fossils, those slowly,

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Speaker 2: over a course of long decomposition became fuel.

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Speaker 3: So let me just say I was right. I mean

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Speaker 3: I had to google it because I was like, I mean,

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Speaker 3: I study living animals, not dead runs. But I mean,

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Speaker 3: but that is accurate, right, So fossil fuels like scientists

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Speaker 3: throw that turn around, politicians thrown around, but it's literally fossils.

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Speaker 3: We have them because it's decomposed dinosaurs from under the earth.

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Speaker 3: So like the gas you put in your car is

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Speaker 3: dinosaur body gas, right that we drive and it combusts

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Speaker 3: and you know, makes all.

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Speaker 1: These dinosaur body like it's not it's not like plant

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Speaker 1: body or something.

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Speaker 3: It's not plants. It's like decomposed animal matter. So it's

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Speaker 3: like dinosaurs. It's like all those old crustaceans. And I mean,

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Speaker 3: it's it's a bunch of stuff that used to live.

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Speaker 3: One day humans will be that same liquefied substance and

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Speaker 3: people could use.

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Speaker 2: Us a cool Wikipedia oil.

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Speaker 4: Why does Wikipedia says they I think it's like they

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Speaker 4: might be or I might be wrong, but I believe

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Speaker 4: it's like if it's plans, it's from those like ancient oceans,

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Speaker 4: right that like right like not like not like you

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Speaker 4: know grad Yeah, it's all prehistoric from before there were

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Speaker 4: people to take down the data of like how it

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Speaker 4: all started and what decomposed. It's just like organic matter,

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Speaker 4: but it's a lot of it is like really big

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Speaker 4: animals like dinosaurs.

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Speaker 3: Okay, so using their bodies.

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Speaker 2: I have to apologize to the listeners. I've been calling

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Speaker 2: fossil fuels dinosaur farts that were just cooking dinosaur farts

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Speaker 2: for our guess, so I.

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Speaker 1: Looking them, I always said, I said, yeah, what is

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Speaker 1: that even cooking farts?

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Speaker 2: Yeah, yeah, we're cooking them to get our cars started.

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Speaker 2: But yes, it's the bodies, not the fart.

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Speaker 3: I mean, I feel like that's like click baity enough.

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Speaker 3: Like a lot of people, you know, you just hear

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Speaker 3: this word over and over and you're just like, I get,

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Speaker 3: I guess that just means like dirty gases that go

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Speaker 3: into that atmosphere. But it's really I mean, it was

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Speaker 3: interesting to make the connection while looking at a dinosaur

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Speaker 3: footprint and like marveling at it to be like, Oh,

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Speaker 3: I interacted dinosaurs all the time, right.

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Speaker 2: And you will have your come up in dinosaurs. You

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Speaker 2: will help.

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Speaker 3: Destroy our remain relevant.

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Speaker 1: Remain dinosaur fart to dinosaur fart, as the Bible says, yeah, my, my,

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Speaker 1: how I would have searched that. What you were just

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Speaker 1: talking about is how dinosaurs footprints Texas? Because I only

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Speaker 1: talked to Google in the dumbest phrases.

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Speaker 3: But we were in Glen Rose, Texas. If you ever

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Speaker 3: go there, you'll be astonished because there are legit huge

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Speaker 3: dinosaur footprints, like and it's just there's just out in

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Speaker 3: the in the community. It's just it's this rural, rural

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Speaker 3: part of central Texas that is like, you know, kind.

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Speaker 2: Of oh, do they have like like dinosaur statues there too?

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Speaker 3: Instead they have the other big statues like off the

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Speaker 3: highway kind of statues. But it is the country like

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Speaker 3: it is like it is not urban. It is a

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Speaker 3: wild place, but it's just very accessible. So let me

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Speaker 3: just say the dinosaur footprints are super accessibly just like

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Speaker 3: kind of walk upon them.

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Speaker 1: Really, I'm looking at a picture from the Smithsonian magazine

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Speaker 1: and it has the dinosaur footprints and then to make

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Speaker 1: sure you know that it's Texas, somebody just dropped a

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Speaker 1: cowboy hat on top of them.

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Speaker 2: For scale with yeah yeah, scale, Yeah, how many cowboy

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Speaker 2: hats tall? Are you? Jack? If we're doing the Texas measurement? Joe,

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Speaker 2: what's something you think is over it?

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Speaker 5: Las Vegas? A lot of friends who Las Vegas is

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Speaker 5: a destination. First time I went, I was like, I

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Speaker 5: cannot believe how much of a scam this openly is,

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Speaker 5: Like like they're really not hiding it, you know, they're

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Speaker 5: they're selling the high roller lifestyle to people who can't

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Speaker 5: afford it, and those people are hopping it up like dogs,

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Speaker 5: And it's really it almost doesn't even feel like deception

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Speaker 5: because it's it's all there. You could all the information

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Speaker 5: is there. You will go and you will lose a

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Speaker 5: ton of money with the promise, with a very American promise,

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Speaker 5: that you could get rich buying into the system that

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Speaker 5: is built specifically to take everything you have.

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Speaker 2: Yeah yeah, yeah, yeah, I love it. I love it.

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Speaker 2: Luck be a lady. Hey, you're to win with that attitude, Joey,

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Speaker 2: Let me tell you something. Let me tell you gotta

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Speaker 2: lose three hundred to make three hundred.

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Speaker 6: You know what I mean, to lose money to make money,

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Speaker 6: you gotta lose your two hundred. You never were in

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Speaker 6: the game, pal, you gotta lose your children's entire college

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Speaker 6: fund to make children's college.

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Speaker 2: At a blackjack table and he already and I'm like, yeah, dude,

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Speaker 2: I'm broke. They're like, you gotta lose, like you know,

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Speaker 2: you gotta look come out three hundred to start winning.

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Speaker 2: I'm like that sounds a fucking wild, dude, Like I

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Speaker 2: was like reckless even cashing in like a hundred bucks here, right, No, totally.

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Speaker 5: And I'm also like really astounded by how not I mean,

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Speaker 5: like we were affecting that kind of rat packing voice.

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Speaker 5: But you go into a casino and there's there's nothing

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Speaker 5: classy about it. It's just like a bunch of flashing lights.

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Speaker 5: Everything is like a giant iPhone, you know. It's yeah, you.

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Speaker 2: Know an that take your money?

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Speaker 3: Yeah.

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Speaker 5: Yeah, he's like huge screens where at least I don't know,

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Speaker 5: maybe at one point there was a charm and you

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Speaker 5: can still like pull a lever if you want, but most.

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Speaker 2: Of it is digital.

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Speaker 5: Yeah, just just gaudy and not like you kind of want.

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Speaker 5: I mean, I would want like, oh, let's get a

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Speaker 5: little bit of a little bit of velvet, a little this,

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Speaker 5: and maybe you can get that some places, but for

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Speaker 5: the most part, it's all just really yellow and gross.

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Speaker 2: Yeah, it's so funny, Like I have such a I

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Speaker 2: used to go there a lot when I was younger,

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Speaker 2: you know, because I was just kind of into like,

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Speaker 2: you know, it was a lot of my friends are

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Speaker 2: just into that, like let's go going Vegas man, right,

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Speaker 2: And then I hadn't gone for a few years, and

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Speaker 2: then Jack and I recently went over the summer to

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Speaker 2: go see like the NBA Summer League, and it was

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Speaker 2: like surreal, where like I was feeling like I was

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Speaker 2: watching like an old part of myself die while I

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Speaker 2: was there, and also seeing like a new future from us.

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Speaker 2: Like I was like, wait, these smells. Like I used

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Speaker 2: to be blacked out in these lobbies, like not knowing

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Speaker 2: what was going on, and now I'm like, uh, it

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Speaker 2: feels a little different. I just is it an.

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Speaker 1: Underage drinking destination like when you lived three hours from it?

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Speaker 1: Cause like I when I was in high school, I

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Speaker 1: drove to from Boston to Montreal.

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Speaker 2: To to get fucked up. Wow. Yeah, Nah, I mean,

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Speaker 2: that's how my think problem was. It was just like

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Speaker 2: to Joe's point, like it was like I was on

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Speaker 2: that mirage ship where I'm like, let's go to Vegas.

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Speaker 2: Now i only have circus circus money, so like to

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Speaker 2: stay there. So like for sure the place I'm gonna

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Speaker 2: stay is so fucked up that I'm just gonna be

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Speaker 2: so fucked up that i don't have to go back

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Speaker 2: to that room until like four in the morning. Right.

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Speaker 2: And But at the same time, like I was always

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Speaker 2: like feeling myself when I was there because I was

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Speaker 2: putting so much like weight into like partying in Vegas

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Speaker 2: and stuff. Got it? Yeah, yeah, Hey, but you can

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Speaker 2: drive a Lambo out there and shoot a fucking machine gun.

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Speaker 2: So yeah, you know, so that's all that matters.

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Speaker 1: Got me right back, That's all I want to do

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Speaker 1: when I wake up in the morning, I wake up

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Speaker 1: quaking with just a desire to shoot a machine gun

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Speaker 1: out of the window of a Lambo and drive by.

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Speaker 2: Yeah, Gabe, what's something you think is underrated?

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Speaker 7: All right, I'm very passionate about this because sushi is

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Speaker 7: expensive everywhere. There's a twenty four hour grocery store next

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Speaker 7: to my apartment that for like six bucks, you can

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Speaker 7: get a sushi roll and it is just powering my

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Speaker 7: whole life. Yeah, So grocery store sushi when it's good under.

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Speaker 2: Yeah yeah yeah, if you can get it. Like there's

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Speaker 2: a there's a local market that I'm surprised sells sushi,

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Speaker 2: but it seems like they have a business where like

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Speaker 2: this sushi company owns the refrigerator case that they're just

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Speaker 2: asking like their market to have in there. So I

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Speaker 2: found out when they come drop the ship, and so

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Speaker 2: the times I've gone for the drop and I'm like, oh, yeah,

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Speaker 2: this is fucking this is great for fucking seven bucks. Absolutely,

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Speaker 2: I knew it was good. When they started to use

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Speaker 2: that health food store as a as like a sham

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Speaker 2: restaurant on grub Hub where you buy sushi and you

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Speaker 2: don't know, I'm like, oh, they think they're a whole restaurant.

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Speaker 8: Hell yeah, I love I love outing a good ghost restaurant.

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Speaker 2: That's always yeah favorite. Yeah.

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Speaker 7: Remember during the pandemic, it was Chuck E Cheese.

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Speaker 2: They changed the name.

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Speaker 7: They were like raise famous and it was just a

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Speaker 7: Chuck E Cheese up and the Chris is.

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Speaker 8: Hot Chicken, and you just it's like this is Denny's. Yeah, yeah,

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Speaker 8: what the fuck. Yeah, there was a few different ones

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Speaker 8: that everyone yeah, everyone just was like Squally's that's what.

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Speaker 2: Yes, well done, well squaleh yeah, man, that's fu. But

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Speaker 2: the other thing though, too, if you got an Asian

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Speaker 2: market nearby, or like someone has like a good fishmonger,

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Speaker 2: you could save money buying sashimi grade fish and just

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Speaker 2: buy your own microwave rice and put a little bit

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Speaker 2: of sushi, Like, buy yourself some sushi seasoning vinegar for

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Speaker 2: your rice, do the microwave pack, and you could buy

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Speaker 2: a fucking big ass piece of fresh salmon for fucking

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Speaker 2: like six seven bucks by my house and I'm my bro,

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Speaker 2: slice this up.

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Speaker 7: Shit fuckish. I love that TikTok guy, the sushi guy.

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Speaker 7: He goes to Costco and buys a big piece of

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Speaker 7: salmon and just turns it into sushi.

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Speaker 9: Oh, breaks it down. Okay, yeah, you gotta do that.

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Speaker 9: I'd be afraid of the parasite. Yeah, he explains all that.

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Speaker 9: He explains that they're in there. You'll be good.

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Speaker 2: You just take pills for that. They eat the pills

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Speaker 2: your life. Just take iodine. You'll be fine. You'll be fine.

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Speaker 2: You'll be fine, you'll be fine. All right, We're gonna

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Speaker 2: take a break. Let's come back and we'll talk about

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Speaker 2: the life and times of Donald Trump after this. And

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Speaker 2: we're back.

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Speaker 1: We are, And so we want to take this opportunity

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Speaker 1: to check in with you, doctor Grenn about how you,

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Speaker 1: as a scientist, perceive some of the news that we

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Speaker 1: cover on a regular basis, and that is entering the

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Speaker 1: zeitgeist on a regular basis. As the sign in my

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Speaker 1: front yard will attest. In this house, we believe in science. Okay, no,

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Speaker 1: but we we do believe. We don't think COVID was

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Speaker 1: caused by five gen Okay, speak for yourself, speak for yourself.

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Speaker 1: We don't think vaccines killed every celebrity who has died

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Speaker 1: since twenty nineteen, since before the pandemic. Yeah, yeah, okay,

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Speaker 1: that's good.

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Speaker 2: That's good, but good solid take.

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Speaker 1: So, I guess you'll be shocked to know Miles is

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Speaker 1: not a scientist. But I am also not a scientist.

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Speaker 1: How do you think about communicating as a scientist to

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Speaker 1: non scientists? Like how strategic are you when communicating with

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Speaker 1: with those of us who may not I'm not going

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Speaker 1: to confirm that I don't have a PhD.

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Speaker 2: In the science. Well, look, I think getting I'm on

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Speaker 2: Reddit are slash science, so I think I have a

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Speaker 2: good grasp on things. But yes, how how would you

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Speaker 2: in a world of contentious information? What's what's it like?

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Speaker 2: What do you do? How do you you know?

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Speaker 1: You know?

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Speaker 3: I got to say, I got to say that I

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Speaker 3: work really hard at it, and I am also gifted

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Speaker 3: with a type of science that I do that is

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Speaker 3: highly visual, right, Like there are like chemists out there,

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Speaker 3: people who study like micro organisms, that it's harder for

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Speaker 3: them to show the science as they're doing it right,

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Speaker 3: or mighty interesting to look at. But I study large animals.

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Speaker 3: I study large carnivores, bears and lions and mountain lions

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Speaker 3: and wolves, and the science behind studying them might be

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Speaker 3: very technical or like you know, very mathy or very analytical,

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Speaker 3: but kind of the basics of it are fun to

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Speaker 3: look at and highly engaging. So I just I get

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Speaker 3: that benefit just automatically that like people might tune in

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Speaker 3: if I show like a hibernating bear, there's a huge

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Speaker 3: science behind that, But the visual also speaks volumes, right,

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Speaker 3: So there's that. And then I also wanted to just

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Speaker 3: shout out how identity plays a huge role into how

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Speaker 3: I approach science communication, and I even think how I

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Speaker 3: got into it because as a you know, I almost

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Speaker 3: had a young black woman, but I should create that

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Speaker 3: as a as a millennial, that used to mean young

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Speaker 3: as a millennial black woman. I always was a part

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Speaker 3: of my community, right, Like my professional community was always

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Speaker 3: so different from my personal, my, my you know, social community.

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Speaker 3: And because of that, I was always telling stories about

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Speaker 3: what I was doing to my community, which is predominantly

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Speaker 3: Black women my own age, right or maybe their brothers

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Speaker 3: and their husbands or their boyfriends or you know, my family.

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Speaker 3: And so because there was such a disconnect between like

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Speaker 3: ecologists and the people I spend my free time with,

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Speaker 3: without really trying, without being purposeful, I would talk a

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Speaker 3: lot about what I do or where I'd been, or

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Speaker 3: why I was going to these places or the cool

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Speaker 3: stuff that I found. And so I found that just naturally,

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Speaker 3: storytelling or just science communication became a thing. And then

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Speaker 3: of course I was also like growing up, I was

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Speaker 3: such a nerd. So imagine me in college. I went

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Speaker 3: to college in Atlanta, and there was this wonderful black community,

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Speaker 3: and I was the girl who was like obsessed with

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Speaker 3: recycling right, like environmental health, like picking up litter. I

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Speaker 3: was the recycling coordinator form my dorm, right, and so

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Speaker 3: I was also that person no matter what my identity was.

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Speaker 3: That is like knocking on people's dorm rooms and being

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Speaker 3: like it's recycling day, like bringing all of your bottles

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Speaker 3: of ninety nine bananas or whatever.

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Speaker 2: No, I'm collecting them. I put them up on my

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Speaker 2: a pyramid out next to my gray Goose bottles, so

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Speaker 2: they know I at one point could afford I have class.

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Speaker 3: So I think that in so many of the ways

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Speaker 3: that I've been involved in science, there's been also a

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Speaker 3: practice to it that you can see, right, you can

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Speaker 3: see someone collecting recycling, right, but there's like a science

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Speaker 3: behind why that's important and how it works. And you

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Speaker 3: can see someone like hiking in the wilderness looking for

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Speaker 3: a bear, and there's a science behind that. So, you know,

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Speaker 3: I think that I might have been super challenged in

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Speaker 3: other ways, but I've just had this amazing benefit of

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Speaker 3: what I do or what I care about, and how

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Speaker 3: visual it is and how a person can kind of

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Speaker 3: symbolize a lot of that, and so I haven't struggled

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Speaker 3: too much. You know, I get like I do get

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Speaker 3: the like comments on Facebook I got. I recently got

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Speaker 3: an email through my website about someone like kind of

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Speaker 3: threatening me to tell a story the right way right.

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Speaker 3: It was really interesting. There's a bird called the atwater

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Speaker 3: prairie chicken in central Texas. It's a highly endangered bird

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Speaker 3: that has this terrible name because the word chicken is

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Speaker 3: in it. But it's actually one of these like remarkable

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Speaker 3: birds in the sage grouse family. So it has these

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Speaker 3: like yellow cheeks that puff up really big, and they

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Speaker 3: do like one of those mating dances that you'd see

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Speaker 3: on all the natural history shows. It's like an incredible bird.

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Speaker 3: And this guy sent an email and he was like,

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Speaker 3: you better like if your show does a story on

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Speaker 3: the Atwater prairie chicken, you better do it right because

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Speaker 3: so many other people have done it wrong. You know,

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Speaker 3: that's what those things are. I was like, you don't

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Speaker 3: even know what we're doing, you know, like like there's

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Speaker 3: no context here. But he was like threatening me, like

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Speaker 3: little old me about this prairie chicken, you know. And

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Speaker 3: so it's just very interesting that I do get people

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Speaker 3: who don't like my communication, you know, I do get

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Speaker 3: people who find problems in it, usually for no good reason. Sure,

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Speaker 3: but I don't get a lot of deniers when it

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Speaker 3: comes to what I'm communicating, And and.

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Speaker 2: That is special to continue down this because I think

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Speaker 2: this is it's relevant, right, because we're it's such an

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Speaker 2: era too where it's people like I got to see

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Speaker 2: it to believe it. For a lot of scientific stuff,

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Speaker 2: like they're like I don't know how a vaccine works,

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Speaker 2: and like and I remember like the like was it

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Speaker 2: the CDC's like here's a fucking video. Man, Yeah, I'm

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Speaker 2: not gonna watch that. It's fucking nonsense. But like for

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Speaker 2: things that are measurable, right, and like for people like

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Speaker 2: if seeing is believing a lot of times, how I

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Speaker 2: guess in that sense, how are you seeing climate change?

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Speaker 2: Because this is another thing that people are like, I

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Speaker 2: don't have it's cold today, therefore, like fine, shut up,

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Speaker 2: But how are you seeing that sort of manifest in

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Speaker 2: the physical world that of like these environments of the

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Speaker 2: species that you study, because that's one thing like obviously

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Speaker 2: you're not like an atmospheric scientist, but you very much

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Speaker 2: do understand how climate is impacting animals. So in that sense,

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Speaker 2: how are you seeing this play out? Like at that scale,

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Speaker 2: because I'm sure that's indicative to like the sort of

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Speaker 2: chain reaction that could happen with our environmental systems. Right.

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Speaker 3: And you know, it's really interesting that you bring that

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Speaker 3: up because I kind of want to put this disclaimer

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Speaker 3: out that climate change impacts wild animals tremendously in a

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Speaker 3: way that's not okay, But I think that we need

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Speaker 3: to solve the issues of climate change to help people first.

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Speaker 3: You know, there's a lot of people who like kind

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Speaker 3: of care more about animals than people, or they might

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Speaker 3: be convinced to care if there's an animal story rather

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Speaker 3: than like, oh, people in this developing nation are suffering

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Speaker 3: kind of story.

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Speaker 2: But you see how they're how emaciated their dogs.

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Speaker 3: Are exactly no, exactly exactly. So I always want to

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Speaker 3: point out, like I like, I live and breathe wild

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Speaker 3: animals every day. I've dedicated my life to saving them

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Speaker 3: and keeping them on this planet. And I think people

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Speaker 3: are more important and more urgently need saving, right because

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Speaker 3: climate change is devastating entire communities of people right now.

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Speaker 3: With that said, bears, right, bears are a perfect example

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Speaker 3: of been studying bears for thirteen years and we're seeing

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Speaker 3: how climate change is impacting all different kinds of bears.

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Speaker 3: So one of the things that we love about bears

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Speaker 3: as like Americans, is that they hibernate in the winter.

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Speaker 3: It gets cold, and they go into their den and

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Speaker 3: they hibernate and they sleep for you know, two four

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Speaker 3: six months at a time. Well, they actually need all

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Speaker 3: kinds of environmental cues to enter hibernation, right, So it's

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Speaker 3: not like they just like look at a calendar and

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Speaker 3: say like, oh my gosh, it's November fifteenth, Like, yeah,

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Speaker 3: time to go, right, It's like their ecosystem has to

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Speaker 3: signal to them is coming. The temperature drops, maybe precipitation increases,

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Speaker 3: maybe because some snow, right, the trees stop producing food.

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Speaker 3: The other animal species they eat, whether it's fish or deer,

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Speaker 3: go away. Everyone is locking down and there's nothing to eat.

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Speaker 3: That's when bears chemical balance changes and hibernation starts. Actually

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Speaker 3: their metabolism slows down, right, that's like body chemistry within them.

432
00:23:25,880 --> 00:23:28,640
Speaker 3: But that's not going to work if it stays warm, right,

433
00:23:28,720 --> 00:23:31,199
Speaker 3: if the trees keep producing, if the bunny rabbits keep

434
00:23:31,240 --> 00:23:34,000
Speaker 3: hopping around, that doesn't happen. So in some of the

435
00:23:34,040 --> 00:23:37,440
Speaker 3: places that I've studied black bears in the Western United States.

436
00:23:37,720 --> 00:23:42,679
Speaker 3: There have been these winters recently where the temperature hasn't

437
00:23:42,760 --> 00:23:47,600
Speaker 3: dropped and the snow hasn't fallen until like February, and

438
00:23:47,680 --> 00:23:51,280
Speaker 3: so the bears have remained active. But then when February

439
00:23:51,359 --> 00:23:54,879
Speaker 3: comes and in one week it's you know, three months

440
00:23:54,880 --> 00:23:58,880
Speaker 3: of snow and everything shuts down. They're not hibernating already.

441
00:23:58,880 --> 00:24:02,359
Speaker 3: Their bodies haven't got into that hibernation state. They might

442
00:24:02,400 --> 00:24:04,600
Speaker 3: not be able to get there in time, and they

443
00:24:04,640 --> 00:24:08,400
Speaker 3: may starve, or they may freeze to death, or they

444
00:24:08,440 --> 00:24:12,360
Speaker 3: may die, or they may come into your garage and

445
00:24:12,680 --> 00:24:15,520
Speaker 3: look for a warm place and some food. So we're

446
00:24:15,560 --> 00:24:20,359
Speaker 3: finding that climate change not only impacts like the bear's

447
00:24:20,400 --> 00:24:23,119
Speaker 3: perception of what season it is and whether or not

448
00:24:23,160 --> 00:24:26,360
Speaker 3: it's time to hibernate, but it could also increase conflicts

449
00:24:26,400 --> 00:24:28,800
Speaker 3: with people, right because they kind of freak out. They're like,

450
00:24:28,840 --> 00:24:31,480
Speaker 3: all I need is some food. It was available last week,

451
00:24:31,560 --> 00:24:33,880
Speaker 3: it's not this week, So where can I find it?

452
00:24:33,920 --> 00:24:37,359
Speaker 3: In your trash can? And that is also a problem.

453
00:24:37,520 --> 00:24:39,400
Speaker 1: It's got to be a heart just like on their

454
00:24:39,480 --> 00:24:42,439
Speaker 1: natural like if they're not getting the rest that they

455
00:24:42,480 --> 00:24:45,880
Speaker 1: had in the past, right, like that doesn't that affect them?

456
00:24:46,480 --> 00:24:46,679
Speaker 5: You know?

457
00:24:47,640 --> 00:24:50,440
Speaker 2: Are they cranky?

458
00:24:50,480 --> 00:24:52,480
Speaker 3: They are cranky. Bears are a lot like us, they

459
00:24:52,520 --> 00:24:55,399
Speaker 3: just aren't. They're hungry, they have They're angry.

460
00:24:55,600 --> 00:24:57,880
Speaker 2: I need three months of sleep in the world.

461
00:24:58,200 --> 00:25:02,240
Speaker 3: They're angry like as do I. Yeah, there are bears

462
00:25:02,280 --> 00:25:05,959
Speaker 3: in warm places where they never hibernate. So there are

463
00:25:05,960 --> 00:25:09,720
Speaker 3: bears in Florida, right, like in the Everglades. It's swampy,

464
00:25:09,760 --> 00:25:11,960
Speaker 3: it's warm, and they don't hibernate in the winter. But

465
00:25:12,040 --> 00:25:17,199
Speaker 3: let me clarify that setting up a hibernation den is

466
00:25:17,359 --> 00:25:21,359
Speaker 3: the most important and the most critical for surviving periods

467
00:25:21,400 --> 00:25:24,160
Speaker 3: where there's no food, right, So like classic winter when

468
00:25:24,160 --> 00:25:28,879
Speaker 3: there's no food and female bears give birth in hibernation,

469
00:25:29,600 --> 00:25:31,959
Speaker 3: they need to set up a hibernation down. They need

470
00:25:32,040 --> 00:25:34,680
Speaker 3: to slow down their metabolism. They need to go into

471
00:25:34,680 --> 00:25:37,560
Speaker 3: a hibernation state in order to give birth because when

472
00:25:37,600 --> 00:25:40,640
Speaker 3: they do, they give birth. Every January. Every bear that's

473
00:25:40,680 --> 00:25:44,520
Speaker 3: ever lived in the history of no North American bears

474
00:25:44,680 --> 00:25:47,040
Speaker 3: has given birth in January, every single one.

475
00:25:47,160 --> 00:25:49,800
Speaker 2: It's the most It's like my favorite doctor, I'm gonna

476
00:25:49,800 --> 00:25:50,640
Speaker 2: have to fact check.

477
00:25:50,480 --> 00:25:54,480
Speaker 3: That checked it now, like you have you have my permission.

478
00:25:54,600 --> 00:25:56,000
Speaker 3: They're born in January.

479
00:25:56,320 --> 00:25:57,720
Speaker 2: Let me call it Tim Ferris.

480
00:25:57,760 --> 00:26:00,280
Speaker 1: Really quick, they realize how much better they'd get it,

481
00:26:00,359 --> 00:26:02,359
Speaker 1: Hockey if they were born a little bit later.

482
00:26:02,600 --> 00:26:03,800
Speaker 3: Oh just slightly later.

483
00:26:04,040 --> 00:26:05,680
Speaker 2: Oh wow, you're really going to Malcolm Black.

484
00:26:07,560 --> 00:26:10,560
Speaker 3: When I was doing my PhD research in the Lake

485
00:26:10,600 --> 00:26:13,200
Speaker 3: Tahoe area on black bears, we would just give every

486
00:26:13,240 --> 00:26:17,080
Speaker 3: bear a January first birthday, and it was more about

487
00:26:17,119 --> 00:26:19,000
Speaker 3: it was less about when they were born and more

488
00:26:19,000 --> 00:26:21,280
Speaker 3: about what year, right as opposed to like what day

489
00:26:21,359 --> 00:26:25,840
Speaker 3: or what just January, And so the moms and mama

490
00:26:25,840 --> 00:26:29,840
Speaker 3: bears like have to stay in their den for you know,

491
00:26:30,080 --> 00:26:33,879
Speaker 3: sixteen twenty weeks because they give birth to these one

492
00:26:34,000 --> 00:26:38,159
Speaker 3: pound like hairless, kind of blind little cubs right like

493
00:26:38,240 --> 00:26:41,560
Speaker 3: they're they're they're little. Bears are huge, right, Bears are

494
00:26:41,560 --> 00:26:44,360
Speaker 3: bigger than people and they give birth to these tiny,

495
00:26:44,480 --> 00:26:47,600
Speaker 3: little like fist sized cups.

496
00:26:47,760 --> 00:26:48,120
Speaker 2: Right wow.

497
00:26:48,440 --> 00:26:51,480
Speaker 3: I mean I personally am jealous, like human beings should

498
00:26:51,560 --> 00:26:53,760
Speaker 3: be able to do that, right, Like, we are smaller

499
00:26:53,880 --> 00:26:55,919
Speaker 3: and we give birth to these enormous babies and it

500
00:26:55,920 --> 00:26:58,440
Speaker 3: turns us apart. So bears they have these like nice

501
00:26:58,440 --> 00:27:01,160
Speaker 3: little births. The babies just slip out right, and then

502
00:27:01,359 --> 00:27:03,919
Speaker 3: they just nurse from their moms and the protection of

503
00:27:03,920 --> 00:27:07,840
Speaker 3: this hibernation den for a couple of months, like two

504
00:27:07,960 --> 00:27:10,440
Speaker 3: or three months, and then they emerge from the den altogether.

505
00:27:10,480 --> 00:27:12,880
Speaker 3: So the mama bearon needs to prepare for hibernation by

506
00:27:12,960 --> 00:27:16,240
Speaker 3: packing on the pounds, getting as fat as she possibly

507
00:27:16,280 --> 00:27:21,120
Speaker 3: can in order to not eat, not drink, not urinate,

508
00:27:21,240 --> 00:27:24,760
Speaker 3: not defecate, and just urt birth and nurse some babies

509
00:27:24,840 --> 00:27:28,720
Speaker 3: for several months. And if the climate is not giving

510
00:27:28,760 --> 00:27:30,600
Speaker 3: her that signal that it is time to do that,

511
00:27:30,720 --> 00:27:32,080
Speaker 3: then she won't be ready.

512
00:27:32,680 --> 00:27:34,919
Speaker 2: And the like, if you play it out to the

513
00:27:35,000 --> 00:27:38,240
Speaker 2: worst possible outcome, it's that like the cycle gets disrupted,

514
00:27:38,400 --> 00:27:41,520
Speaker 2: disrupted to the point that the population just begin dwindling.

515
00:27:41,760 --> 00:27:45,720
Speaker 3: That's right, We just stop having births like successful berths. Right,

516
00:27:45,800 --> 00:27:47,840
Speaker 3: So it's less about sometimes people are worried about like

517
00:27:47,920 --> 00:27:51,000
Speaker 3: hunting them, like outright killing of them, and it's more

518
00:27:51,040 --> 00:27:55,400
Speaker 3: about like females of reproductive age, like having successful berths

519
00:27:55,440 --> 00:27:57,320
Speaker 3: over and over, and that's if we don't have that,

520
00:27:57,359 --> 00:27:59,119
Speaker 3: then we don't have a future of the species.

521
00:27:59,480 --> 00:28:02,120
Speaker 2: You said something really interesting earlier that I wanted to

522
00:28:02,119 --> 00:28:04,879
Speaker 2: touch back on. They don't. And I was always curious

523
00:28:04,920 --> 00:28:07,080
Speaker 2: about this. They don't pooper pee that whole time.

524
00:28:07,359 --> 00:28:08,360
Speaker 3: Yeah, isn't that crazy?

525
00:28:09,160 --> 00:28:12,639
Speaker 2: I always wondered how that. I don't know. I remember

526
00:28:12,680 --> 00:28:14,320
Speaker 2: as a kid hearing that. I'm like, they got to

527
00:28:14,400 --> 00:28:16,840
Speaker 2: poop a little bit, probably.

528
00:28:16,400 --> 00:28:19,840
Speaker 3: They Okay, okay, So let me just say because scientists

529
00:28:19,880 --> 00:28:22,640
Speaker 3: are always going to give a good like, it depends, right,

530
00:28:22,680 --> 00:28:26,960
Speaker 3: So here's my scientist. It depends for accuracy. There haven't

531
00:28:27,040 --> 00:28:29,879
Speaker 3: been a lot of studies done on hibernating bears. You

532
00:28:29,880 --> 00:28:33,040
Speaker 3: can imagine why, right, Like, it is very hard to

533
00:28:33,080 --> 00:28:34,080
Speaker 3: study these animals.

534
00:28:34,160 --> 00:28:36,480
Speaker 1: Yeah, it seems so cozy in there. I would be

535
00:28:36,520 --> 00:28:38,920
Speaker 1: all about that. If you need somebody to go in there.

536
00:28:40,680 --> 00:28:42,720
Speaker 2: All right, cool, I'll be back in a couple hours.

537
00:28:42,920 --> 00:28:45,280
Speaker 3: Yeah, Like it says it's like pretty dangerous and like

538
00:28:45,360 --> 00:28:48,160
Speaker 3: they don't want to be bothered, and a lot of

539
00:28:48,200 --> 00:28:50,040
Speaker 3: these things are very important. And then it's hard to

540
00:28:50,080 --> 00:28:54,240
Speaker 3: study hibernation and captive bears like at the zoo because again,

541
00:28:54,280 --> 00:28:56,959
Speaker 3: their food source doesn't go away in the wintertime, and

542
00:28:57,040 --> 00:28:59,920
Speaker 3: so they often don't hibernate because they're like I'm I'm cool,

543
00:29:00,000 --> 00:29:03,480
Speaker 3: I'm chilling. I have like a heater and a you know,

544
00:29:03,480 --> 00:29:05,600
Speaker 3: a person who brings me food. So there aren't a

545
00:29:05,600 --> 00:29:07,320
Speaker 3: lot of studies on this, but what we found is

546
00:29:07,360 --> 00:29:11,920
Speaker 3: that in this metabolic state that they enter, they recycle

547
00:29:12,000 --> 00:29:14,520
Speaker 3: all of their waste and urine, so that's why they

548
00:29:14,520 --> 00:29:18,520
Speaker 3: don't drink anything, and there the liquid in their body

549
00:29:18,560 --> 00:29:21,840
Speaker 3: is being recycled like over and over. It's fascinating and

550
00:29:21,880 --> 00:29:25,000
Speaker 3: there's a lot that we can learn about human health

551
00:29:25,320 --> 00:29:30,560
Speaker 3: and you know, biomedicine from studying hibernating bears. In fact,

552
00:29:31,080 --> 00:29:35,280
Speaker 3: there are some hypotheses that they're plasma changes, so we

553
00:29:35,320 --> 00:29:37,880
Speaker 3: can detect the chemical changes down to the blood and

554
00:29:37,920 --> 00:29:42,800
Speaker 3: the plasma level, and their organs are actually preserved because

555
00:29:42,960 --> 00:29:47,760
Speaker 3: the like just from recycling molecular like components of their

556
00:29:47,760 --> 00:29:52,200
Speaker 3: plasma changes. I've had a researcher come to the field

557
00:29:52,200 --> 00:29:57,200
Speaker 3: with me in Minnesota who was a cardiologist and was

558
00:29:57,240 --> 00:30:00,800
Speaker 3: studying you know, human hearts, and the idea was that

559
00:30:00,800 --> 00:30:03,280
Speaker 3: they want to take a blood sample from a hibernating bear,

560
00:30:03,560 --> 00:30:06,200
Speaker 3: which we were able to do, not without drama, but

561
00:30:06,200 --> 00:30:09,560
Speaker 3: we were able to do it, and they wanted to

562
00:30:09,600 --> 00:30:13,840
Speaker 3: see if the blood of a hibernating bear could preserve

563
00:30:14,080 --> 00:30:19,120
Speaker 3: human organs because we need a way to make organ donors.

564
00:30:19,800 --> 00:30:24,760
Speaker 3: Organs oh last longer. When there's an organ donor and

565
00:30:24,800 --> 00:30:27,600
Speaker 3: there's a recipient somewhere in a hospital waiting for a

566
00:30:27,720 --> 00:30:31,640
Speaker 3: lung or a heart or a kidney, often the organ

567
00:30:31,720 --> 00:30:34,840
Speaker 3: will die in transport because we don't have a good

568
00:30:34,840 --> 00:30:37,959
Speaker 3: way to keep them alive. But apparently bear blood, hibernating

569
00:30:38,000 --> 00:30:41,719
Speaker 3: bear blood might be the thing we need to, like

570
00:30:41,760 --> 00:30:44,280
Speaker 3: if we can replicate it to figure out how to

571
00:30:44,320 --> 00:30:47,000
Speaker 3: preserve organs for double the amount of time so that

572
00:30:47,040 --> 00:30:49,560
Speaker 3: more lives can be saved by organ donors.

573
00:30:49,680 --> 00:30:53,640
Speaker 2: Right. See, this has been learning new stuff too. I'm

574
00:30:53,640 --> 00:30:55,640
Speaker 2: going to start going poop and pee in the recycling can.

575
00:30:55,960 --> 00:30:58,800
Speaker 3: Yeah right, I mean that's what I'm saying.

576
00:30:58,960 --> 00:31:01,400
Speaker 2: That is, I think we got what you recycle your way.

577
00:31:02,200 --> 00:31:04,800
Speaker 1: I mean, you know, talking about the vaccine and you

578
00:31:04,840 --> 00:31:07,200
Speaker 1: know the like, there's a lot of people who had

579
00:31:07,200 --> 00:31:10,680
Speaker 1: some ideas about how you could recycle your own you're

580
00:31:10,880 --> 00:31:14,960
Speaker 1: help protect you from Jack. I think you just endorsed that, right,

581
00:31:15,080 --> 00:31:16,200
Speaker 1: so we can just move along.

582
00:31:16,760 --> 00:31:19,200
Speaker 2: Let's get past the joke stuff. Why don't you want

583
00:31:19,200 --> 00:31:20,720
Speaker 2: to ask a serious question? Yeah?

584
00:31:20,760 --> 00:31:25,720
Speaker 1: Okay, So you wake up and you're a bear. I

585
00:31:26,040 --> 00:31:27,840
Speaker 1: have an answer to this that I'll get first, But like,

586
00:31:27,880 --> 00:31:31,840
Speaker 1: what's the first thing you're doing? Like, I personally feel

587
00:31:31,880 --> 00:31:37,600
Speaker 1: like showing the other bears water slides would be high

588
00:31:37,600 --> 00:31:40,680
Speaker 1: on my I feel like bears would love water slides.

589
00:31:41,040 --> 00:31:43,200
Speaker 1: And I don't think i've seen a bear like I've

590
00:31:43,200 --> 00:31:46,760
Speaker 1: seen them enjoy a pool. I've seen them enjoy hammocks.

591
00:31:47,680 --> 00:31:51,480
Speaker 1: Love a hammock, but like water slide park, Like me

592
00:31:51,520 --> 00:31:54,640
Speaker 1: and my bear friends go right on water slide park.

593
00:31:55,080 --> 00:31:57,840
Speaker 2: Yeah, that sounds pretty fun. What would what would yours be?

594
00:31:57,960 --> 00:31:59,960
Speaker 2: Other than that obvious? First?

595
00:32:00,040 --> 00:32:03,600
Speaker 3: I guess realistically, Yeah, sure that I do as a bear.

596
00:32:03,920 --> 00:32:06,920
Speaker 3: I mean, you know, they're just so motivated by hunger

597
00:32:07,320 --> 00:32:11,120
Speaker 3: as am I. So I think the first thing I

598
00:32:11,200 --> 00:32:15,080
Speaker 3: might do is like hit up like a buffet, you know,

599
00:32:15,600 --> 00:32:18,000
Speaker 3: like like a good Like what's a good buffet? I mean,

600
00:32:18,080 --> 00:32:19,640
Speaker 3: Sizzler is classic?

601
00:32:20,040 --> 00:32:23,560
Speaker 2: Yea based in my family pizza hut salad bar oh.

602
00:32:23,440 --> 00:32:26,520
Speaker 3: From the nineties. Yeah, pizza hut salad bar I think

603
00:32:26,800 --> 00:32:30,600
Speaker 3: Tuesdays used to have one. Yeah, okay, machine, you know,

604
00:32:30,680 --> 00:32:34,440
Speaker 3: like a solid buffet I think would be what I do.

605
00:32:35,120 --> 00:32:38,000
Speaker 3: But I might also, like, you know, what's funny is

606
00:32:38,000 --> 00:32:40,520
Speaker 3: that what people talk to me about bears all the time, right,

607
00:32:40,600 --> 00:32:43,680
Speaker 3: And so often they'll bring up like Yogi Bear, right,

608
00:32:43,720 --> 00:32:47,480
Speaker 3: the cartoon, and they'll talk about like picnic baskets and

609
00:32:47,640 --> 00:32:49,920
Speaker 3: like going for a picnic and all that kind of stuff,

610
00:32:49,920 --> 00:32:51,440
Speaker 3: And I'm like, maybe that would be cute. Maybe if

611
00:32:51,440 --> 00:32:53,000
Speaker 3: I woke up as a bear, I might be like, hey,

612
00:32:53,040 --> 00:32:56,240
Speaker 3: let's let's like let's actualize this. Let's like go for

613
00:32:56,280 --> 00:32:59,200
Speaker 3: a picnic at a picnic table in a public park

614
00:32:59,280 --> 00:33:02,120
Speaker 3: and blow people minds. You know, let's just like screw

615
00:33:02,200 --> 00:33:05,840
Speaker 3: with people and make this whole Yogi Bear story real. Yeah,

616
00:33:05,840 --> 00:33:07,760
Speaker 3: and you know, do that play the part?

617
00:33:08,240 --> 00:33:08,800
Speaker 2: I like that.

618
00:33:09,120 --> 00:33:12,440
Speaker 1: Sorry, we're just furiously crossing off the five Yogi Bear questions.

619
00:33:12,680 --> 00:33:15,800
Speaker 2: Yeah, but not that one. Those might come off as hack.

620
00:33:16,000 --> 00:33:20,880
Speaker 2: Now that's another one. Oh okay, So to that point

621
00:33:21,080 --> 00:33:24,280
Speaker 2: right about you know, bears taking a pie off a

622
00:33:24,320 --> 00:33:28,400
Speaker 2: window sill and things like this. So we constantly read stories,

623
00:33:28,520 --> 00:33:30,760
Speaker 2: or I'm constant seeing stories of like, you know, black

624
00:33:30,800 --> 00:33:33,600
Speaker 2: bear shows up in a backyard and you know, the

625
00:33:34,040 --> 00:33:37,760
Speaker 2: species are increasing. The BBC over the summer was like

626
00:33:38,240 --> 00:33:41,360
Speaker 2: bears are returning to the Alps. Here's what you need

627
00:33:41,400 --> 00:33:44,840
Speaker 2: to do to avoid, you know, having a horrible encounter.

628
00:33:45,000 --> 00:33:48,120
Speaker 2: We're in how to stay safe in bear territory. Some

629
00:33:48,200 --> 00:33:50,200
Speaker 2: things feel and then other things I've read about how

630
00:33:50,200 --> 00:33:52,960
Speaker 2: I think Louisiana may have a bear hunting season for

631
00:33:53,000 --> 00:33:55,240
Speaker 2: the first time in a long time, and that like

632
00:33:55,360 --> 00:33:59,000
Speaker 2: populations are are rising to levels where before it seemed

633
00:33:59,000 --> 00:34:02,120
Speaker 2: like it was pretty rought with potential of like you know, extinction.

634
00:34:02,920 --> 00:34:05,560
Speaker 2: Are these stories like are they part of a bigger picture?

635
00:34:05,640 --> 00:34:08,160
Speaker 2: Are there people who are just looking at these bear

636
00:34:08,200 --> 00:34:12,040
Speaker 2: communities being like trying to other the bears and make

637
00:34:12,120 --> 00:34:14,080
Speaker 2: them feel like a threat, and how we have to

638
00:34:14,080 --> 00:34:17,560
Speaker 2: control them or is it something that has to be hunted.

639
00:34:17,640 --> 00:34:20,800
Speaker 2: That's one thing I'm seeing constantly, aside from also locally,

640
00:34:20,880 --> 00:34:22,920
Speaker 2: especially in like La, people who live near the Angelus

641
00:34:23,000 --> 00:34:27,560
Speaker 2: National Forest, increased anecdotes and like local news about bears

642
00:34:27,600 --> 00:34:31,200
Speaker 2: like showing up. And I'm curious from your perspective, is

643
00:34:31,239 --> 00:34:33,680
Speaker 2: it like this is a good thing, like right, like

644
00:34:33,680 --> 00:34:37,399
Speaker 2: like conservations working and we're able to like help repopulate

645
00:34:38,120 --> 00:34:42,240
Speaker 2: or this is or it's it's it's fine lines. Where

646
00:34:42,239 --> 00:34:43,160
Speaker 2: are we at the bear?

647
00:34:43,560 --> 00:34:45,840
Speaker 3: So much to say about this. I'm gonna save the

648
00:34:45,960 --> 00:34:50,239
Speaker 3: hunting stuff okay, because I have a personal opinion about

649
00:34:50,320 --> 00:34:53,120
Speaker 3: hunting and I have a professional opinion and they're different. Okay,

650
00:34:53,560 --> 00:34:55,359
Speaker 3: But to answer your first question, I just want here's

651
00:34:55,360 --> 00:34:58,360
Speaker 3: a little anecdote. When I was in grad school, my

652
00:34:58,760 --> 00:35:01,840
Speaker 3: advisor said to me he had been studying carnivores for

653
00:35:02,040 --> 00:35:04,239
Speaker 3: his whole professional career, and he said to me, when

654
00:35:04,280 --> 00:35:07,920
Speaker 3: it comes to carnivores, people think there's either too few

655
00:35:08,640 --> 00:35:11,920
Speaker 3: or too many. They never think there's the right number.

656
00:35:13,040 --> 00:35:17,120
Speaker 3: And man, oh man, does that ring true? Because when

657
00:35:17,320 --> 00:35:20,640
Speaker 3: bears are on the endangered species list, like people are like,

658
00:35:20,880 --> 00:35:23,000
Speaker 3: save the bears. We love bears. We got to get

659
00:35:23,000 --> 00:35:25,920
Speaker 3: more bears, bring them back by any means necessary. And

660
00:35:26,280 --> 00:35:28,920
Speaker 3: once we get like a good number of bears around,

661
00:35:28,960 --> 00:35:31,799
Speaker 3: and they're like, oh, look, my ancestors used to live here.

662
00:35:31,840 --> 00:35:34,239
Speaker 3: I'm going to come back to this space all of

663
00:35:34,239 --> 00:35:36,759
Speaker 3: a sudden, right like people are ringing the alarm, like

664
00:35:36,840 --> 00:35:39,880
Speaker 3: bears are everywhere they've returned, Like what are you going

665
00:35:39,920 --> 00:35:43,839
Speaker 3: to do? They're eating your puppies. So that's like my thing.

666
00:35:43,880 --> 00:35:49,040
Speaker 3: I would actually I would call on everyone listening to

667
00:35:49,120 --> 00:35:53,960
Speaker 3: really think about, like where do you fit in this?

668
00:35:54,239 --> 00:35:57,319
Speaker 3: Like you do care about wild animals? And you care

669
00:35:57,360 --> 00:35:59,400
Speaker 3: when there's not enough of them, but when there's like

670
00:35:59,520 --> 00:36:02,359
Speaker 3: plenty or when they're doing well, and when you see them,

671
00:36:02,640 --> 00:36:04,600
Speaker 3: does that mean there's too many or does that mean

672
00:36:04,640 --> 00:36:08,440
Speaker 3: you're uncomfortable? Because I think that's a huge, huge difference

673
00:36:08,880 --> 00:36:11,840
Speaker 3: because like, on one hand, when it comes to black bears,

674
00:36:11,840 --> 00:36:14,520
Speaker 3: like we've been doing conservation on them for several decades,

675
00:36:14,560 --> 00:36:18,319
Speaker 3: it's been working pretty well, and black bear populations are rebounding,

676
00:36:18,640 --> 00:36:22,160
Speaker 3: But there's not like so many black bears, right, I mean,

677
00:36:23,000 --> 00:36:27,000
Speaker 3: considering how many there used to be before, like you know,

678
00:36:27,040 --> 00:36:31,200
Speaker 3: the colonization of North America, there's a fraction of that

679
00:36:31,320 --> 00:36:34,520
Speaker 3: number here today. Right, there's no habitat for them. I mean,

680
00:36:34,560 --> 00:36:36,120
Speaker 3: like you know, you look at New York City. New

681
00:36:36,160 --> 00:36:37,759
Speaker 3: York City used to have bears before it was New

682
00:36:37,840 --> 00:36:39,200
Speaker 3: York City, and now you're not going to find a

683
00:36:39,239 --> 00:36:43,120
Speaker 3: bear anywhere near there. So you know, like San Francisco,

684
00:36:43,280 --> 00:36:47,120
Speaker 3: Los Angeles, grizzly bears like walked in those spaces. You're

685
00:36:47,120 --> 00:36:51,000
Speaker 3: not going to find grizzly bears in California. So I

686
00:36:51,160 --> 00:36:55,359
Speaker 3: have such a strong like pushback on people who are

687
00:36:55,400 --> 00:36:57,880
Speaker 3: like there's so many, they're everywhere, They're in my backyard,

688
00:36:57,920 --> 00:37:00,360
Speaker 3: cause it's like, well, it's their backyard. Actually, that's like

689
00:37:00,400 --> 00:37:03,600
Speaker 3: they're in their backyard, like they're at their house. It's

690
00:37:04,360 --> 00:37:08,120
Speaker 3: like they came first. Bears existed in North America from

691
00:37:08,160 --> 00:37:11,080
Speaker 3: what we can tell from like the evolutionary timeline. They

692
00:37:11,120 --> 00:37:15,080
Speaker 3: were here before people, before indigenous people, before any human

693
00:37:15,120 --> 00:37:17,399
Speaker 3: beings walked on the continent of North America. As far

694
00:37:17,400 --> 00:37:21,400
Speaker 3: as we know, black bears were here first. And so

695
00:37:21,680 --> 00:37:24,600
Speaker 3: this is their land and we need them right Like

696
00:37:24,640 --> 00:37:28,520
Speaker 3: they helped to control the herbivore population. That helps control

697
00:37:28,600 --> 00:37:31,560
Speaker 3: the vegetation community, and that gives us deeper roots in

698
00:37:31,640 --> 00:37:34,239
Speaker 3: the soil, and that prevents erosion. And that's a really

699
00:37:34,239 --> 00:37:36,120
Speaker 3: big issue. I mean, there's a lot of reasons we

700
00:37:36,160 --> 00:37:39,560
Speaker 3: need these predators. Okay, the next thing I'll say is

701
00:37:39,600 --> 00:37:44,319
Speaker 3: that COVID, man oh man, COVID actually plays into this

702
00:37:44,760 --> 00:37:47,640
Speaker 3: because when the world shut down and everyone had to

703
00:37:47,640 --> 00:37:51,600
Speaker 3: start working from home in twenty twenty, we started like

704
00:37:51,800 --> 00:37:55,319
Speaker 3: noticing shit. Like people started like looking out their window

705
00:37:55,360 --> 00:37:57,640
Speaker 3: and be like, oh my gosh, there's a coyote out there.

706
00:37:57,920 --> 00:38:00,440
Speaker 3: Oh my gosh, have you seen how many wrecks boons

707
00:38:00,520 --> 00:38:03,520
Speaker 3: are in the trash? Oh my gosh, the combination of

708
00:38:03,560 --> 00:38:07,320
Speaker 3: people being home and being able to notice what happens

709
00:38:07,480 --> 00:38:09,680
Speaker 3: in and around their home, and also like not going

710
00:38:09,680 --> 00:38:11,399
Speaker 3: out at night, right like we're not going to the club,

711
00:38:11,440 --> 00:38:14,399
Speaker 3: We're not like going to places where just like we're

712
00:38:14,440 --> 00:38:16,920
Speaker 3: on bear watch, we can hear. We can notice people

713
00:38:17,160 --> 00:38:20,319
Speaker 3: spending more time in wild places, right like when we

714
00:38:20,320 --> 00:38:22,440
Speaker 3: were able to travel again in COVID, it was safer

715
00:38:22,440 --> 00:38:26,919
Speaker 3: to be in nature than other places. And then technology,

716
00:38:26,960 --> 00:38:30,319
Speaker 3: everyone has like a ring camera, right Like you used

717
00:38:30,360 --> 00:38:32,400
Speaker 3: to have a doorbell, and now you have a camera

718
00:38:32,560 --> 00:38:34,719
Speaker 3: at your door. Everyone is ape and they have a

719
00:38:34,719 --> 00:38:36,279
Speaker 3: camera at the front door, at the back door, all

720
00:38:36,280 --> 00:38:39,640
Speaker 3: around the house. Door came, the doorbells have cameras. Like

721
00:38:39,800 --> 00:38:44,799
Speaker 3: there's so much monitoring. There's also like I'm flashing my

722
00:38:45,000 --> 00:38:50,680
Speaker 3: iPhone at y'all because when I first started studying bears,

723
00:38:51,120 --> 00:38:54,839
Speaker 3: we didn't have cameras with phones or phones with camera.

724
00:38:54,880 --> 00:38:59,000
Speaker 3: You know what I'm trying to say, camera phones, and

725
00:38:59,080 --> 00:39:02,200
Speaker 3: now we do so like the amount of bears that

726
00:39:02,239 --> 00:39:05,040
Speaker 3: I can show that I'm working on today when I

727
00:39:05,040 --> 00:39:08,920
Speaker 3: do field work is an order of magnitude bigger than before.

728
00:39:09,480 --> 00:39:12,959
Speaker 3: So anyone who interacts with a bear in twenty twenty three,

729
00:39:13,120 --> 00:39:15,480
Speaker 3: can prove it, can show it and put it on

730
00:39:15,520 --> 00:39:19,200
Speaker 3: the internet, can spread this information. Whereas ten years ago,

731
00:39:19,520 --> 00:39:22,000
Speaker 3: fifteen years ago, you just had the story to tell

732
00:39:22,040 --> 00:39:23,120
Speaker 3: and it didn't get very far.

733
00:39:23,200 --> 00:39:25,320
Speaker 2: I didn't believe so existed. It was like Bigfoot.

734
00:39:25,360 --> 00:39:28,920
Speaker 3: To me, it was yoking bear, and I was like, yeah.

735
00:39:28,920 --> 00:39:31,080
Speaker 1: That's that's a cartoon, you fools.

736
00:39:31,880 --> 00:39:35,560
Speaker 2: Sure enough. And then I got a cat, sure enough,

737
00:39:35,560 --> 00:39:36,800
Speaker 2: feels one of those real ones.

738
00:39:38,360 --> 00:39:42,880
Speaker 3: So it's like talking to There's like this combination of things, right,

739
00:39:42,920 --> 00:39:45,279
Speaker 3: there's just a combination of things like, yes, there are

740
00:39:45,320 --> 00:39:48,719
Speaker 3: more bears, there's not very many more bears. Like it's going, well,

741
00:39:49,120 --> 00:39:52,520
Speaker 3: it's going, well, there's more coyotes. There's not that many

742
00:39:52,600 --> 00:39:57,239
Speaker 3: more coyotes. There's more coyotes caught on your nest camera. Right,

743
00:39:57,320 --> 00:39:59,279
Speaker 3: that's what it is like. You just didn't know the

744
00:39:59,400 --> 00:40:02,440
Speaker 3: coyotes are finding their own business on your property, you know,

745
00:40:02,560 --> 00:40:04,719
Speaker 3: five years ago, But now you know, and now you

746
00:40:04,760 --> 00:40:07,120
Speaker 3: have a feeling about it. And so there are so

747
00:40:07,200 --> 00:40:09,920
Speaker 3: many scientists, a lot of folks especially I have to

748
00:40:10,000 --> 00:40:13,080
Speaker 3: highlight like UC Berkeley has this incredible lab, the Shell

749
00:40:13,200 --> 00:40:16,920
Speaker 3: Lab sh e L run by a black man who's

750
00:40:16,960 --> 00:40:22,600
Speaker 3: a wonderful wildlife ecologist and they primarily study like urban carnivores,

751
00:40:22,840 --> 00:40:27,120
Speaker 3: and they are actually using data from next door you

752
00:40:27,160 --> 00:40:29,680
Speaker 3: know that terrible like app people on therasist.

753
00:40:30,120 --> 00:40:34,760
Speaker 2: Yeah, yeah, data are they getting? Yeah, how those people

754
00:40:34,880 --> 00:40:38,719
Speaker 2: are selling stuff outside on their corner, So like filter.

755
00:40:38,520 --> 00:40:42,480
Speaker 3: Out all of the discriminatory like posts on racism and

756
00:40:42,800 --> 00:40:46,440
Speaker 3: anti homeless rhetoric, and you get people talking about animals

757
00:40:46,840 --> 00:40:50,879
Speaker 3: and they're actually using data from next door to kind

758
00:40:50,920 --> 00:40:56,840
Speaker 3: of measure like are people reporting seeing wildlife more often

759
00:40:56,920 --> 00:40:59,000
Speaker 3: than before? And the answer is yes, So we have

760
00:40:59,080 --> 00:41:01,480
Speaker 3: like a few more animal but a lot more reporting,

761
00:41:01,520 --> 00:41:04,040
Speaker 3: a lot more discussions, a lot of people sharing it

762
00:41:04,120 --> 00:41:06,799
Speaker 3: and seeing it. And I think that's good. I think

763
00:41:06,840 --> 00:41:10,279
Speaker 3: it normalizes wildlife being around. But people got to like

764
00:41:10,480 --> 00:41:13,239
Speaker 3: stop worrying that they're not going to be okay because

765
00:41:13,239 --> 00:41:15,400
Speaker 3: it's like when was the last time a coyote like

766
00:41:15,560 --> 00:41:18,279
Speaker 3: killed somebody? We don't have that, Like that doesn't happen

767
00:41:18,320 --> 00:41:19,520
Speaker 3: a bearing.

768
00:41:19,360 --> 00:41:20,200
Speaker 2: My baby, you know.

769
00:41:20,360 --> 00:41:22,800
Speaker 3: Yeah, Like it's not like you're okay, like you're safe.

770
00:41:23,000 --> 00:41:25,200
Speaker 3: You just might not feel comfortable.

771
00:41:25,200 --> 00:41:28,360
Speaker 2: Right, Yeah. I mean it gets to your point about awareness,

772
00:41:28,360 --> 00:41:29,920
Speaker 2: Like the more I see it, the more. I'm like,

773
00:41:30,440 --> 00:41:33,240
Speaker 2: I actually see more videos of bear encounters where people

774
00:41:33,520 --> 00:41:36,280
Speaker 2: like successfully are just like who know what they're doing,

775
00:41:36,400 --> 00:41:39,000
Speaker 2: and like the bear leaves, and that's actually given me

776
00:41:39,080 --> 00:41:41,359
Speaker 2: a little bit more of being like, Okay, they're not

777
00:41:41,400 --> 00:41:43,640
Speaker 2: out here to fucking eat our pies. You know, They're

778
00:41:43,680 --> 00:41:45,960
Speaker 2: just doing their thing. And if you if you happen

779
00:41:46,000 --> 00:41:48,000
Speaker 2: to have an encounter, there is a way to exit

780
00:41:48,080 --> 00:41:50,960
Speaker 2: about being like, get your fucking gun tall.

781
00:41:51,000 --> 00:41:55,040
Speaker 1: This bear all this bear pie fear mongering is getting

782
00:41:55,080 --> 00:41:57,040
Speaker 1: out of hand and it's unbearable.

783
00:41:57,080 --> 00:41:59,600
Speaker 3: I actually, okay, we need to wage your campaign.

784
00:42:00,120 --> 00:42:02,960
Speaker 1: Yeah, we need to take a quick break, and then

785
00:42:03,000 --> 00:42:04,759
Speaker 1: we're going to come back. And I want to ask

786
00:42:04,800 --> 00:42:09,640
Speaker 1: about bear videos just generally, because I think you've mentioned

787
00:42:09,680 --> 00:42:11,799
Speaker 1: it a couple of times, but bear videos rule, they

788
00:42:11,840 --> 00:42:14,360
Speaker 1: probably make your job a little bit easier.

789
00:42:14,680 --> 00:42:15,680
Speaker 2: So we're going to talk.

790
00:42:15,719 --> 00:42:29,920
Speaker 1: We'll be right back, and we're back, And so I guess.

791
00:42:30,120 --> 00:42:34,279
Speaker 1: October sixteenth, two days ago, was the one hundredth anniversary

792
00:42:34,280 --> 00:42:37,080
Speaker 1: of the founding of the Walt Disney Company.

793
00:42:37,400 --> 00:42:43,719
Speaker 2: Yeah we did it. Hell yeah, time past.

794
00:42:43,760 --> 00:42:50,200
Speaker 1: Speaking of racist caricatures. So you know, it is good

795
00:42:50,200 --> 00:42:52,239
Speaker 1: to see that there are people pushing back on this

796
00:42:52,360 --> 00:42:55,640
Speaker 1: monoculture of Disney. Oh wait, sorry, it's people who are

797
00:42:55,800 --> 00:42:57,600
Speaker 1: like it should be more racist.

798
00:42:58,080 --> 00:42:59,160
Speaker 2: Oh right right.

799
00:42:59,239 --> 00:43:04,000
Speaker 1: Daily Wire co CEO Jeremy Boring. Yes, the man behind

800
00:43:04,120 --> 00:43:08,000
Speaker 1: this terrible entertainment platform literally named Boring, kicked off a

801
00:43:08,120 --> 00:43:13,279
Speaker 1: video announcing his new company called bent Key, with a

802
00:43:13,360 --> 00:43:16,520
Speaker 1: rant about how Disney is trying to indoctrinate our kids,

803
00:43:17,120 --> 00:43:21,040
Speaker 1: adding that while Disney still uses Walt's name, he's like

804
00:43:21,040 --> 00:43:23,640
Speaker 1: on a nickname basis with Walt Disney, they have all

805
00:43:23,680 --> 00:43:27,840
Speaker 1: been abandoned his legacy, presumably meaning his legacy of racism

806
00:43:27,920 --> 00:43:28,920
Speaker 1: and anti semitism.

807
00:43:29,480 --> 00:43:33,120
Speaker 2: But they come back. Yeah.

808
00:43:33,200 --> 00:43:35,799
Speaker 1: So they go on to announce a new app which

809
00:43:35,840 --> 00:43:40,520
Speaker 1: will feature license program and also original children's shows, including

810
00:43:40,719 --> 00:43:44,439
Speaker 1: Chip Chin Chip Chilla'.

811
00:43:43,560 --> 00:43:46,600
Speaker 2: That's a mouthful. Yeah, so it's just chip Chilla.

812
00:43:46,920 --> 00:43:49,560
Speaker 1: It's about a it's just a blue rip off with

813
00:43:49,719 --> 00:43:51,360
Speaker 1: chinchillas instead of dogs.

814
00:43:51,719 --> 00:43:57,200
Speaker 10: Fucking terrible blue ripoff. Just a terrible blue rip off.

815
00:43:57,239 --> 00:43:59,040
Speaker 10: Featuring the voice of Rob Schneider.

816
00:43:59,480 --> 00:44:03,640
Speaker 2: Yes, you gotta have the canceled, the voice of the

817
00:44:03,719 --> 00:44:07,440
Speaker 2: canceled to power this kind of creative endeavor and like,

818
00:44:07,520 --> 00:44:10,440
Speaker 2: it's wild when you look at this. The pictures of

819
00:44:10,760 --> 00:44:15,319
Speaker 2: chip Chilla are So it's just like so blatant that

820
00:44:15,320 --> 00:44:17,600
Speaker 2: it's a rip off with Blue. Don't they understand how kids'

821
00:44:17,640 --> 00:44:20,960
Speaker 2: minds work. As a kid, I rejected anything that I

822
00:44:21,080 --> 00:44:24,080
Speaker 2: suspected of being not the genuine article, you know what

823
00:44:24,120 --> 00:44:28,120
Speaker 2: I mean. If it's like you're too good for gobots? Yeah, absolutely,

824
00:44:28,440 --> 00:44:31,200
Speaker 2: Like you know if your my mom be like, oh,

825
00:44:31,200 --> 00:44:33,279
Speaker 2: we got that at home, and I'm like, we don't

826
00:44:33,320 --> 00:44:35,399
Speaker 2: have that at home. It's in the store. The thing

827
00:44:35,440 --> 00:44:37,360
Speaker 2: you have at home is like this other version, or

828
00:44:37,400 --> 00:44:39,200
Speaker 2: it's like there's this other toy that's like the thing

829
00:44:39,200 --> 00:44:41,239
Speaker 2: I like, it's like, it's not the thing. So I

830
00:44:41,280 --> 00:44:43,279
Speaker 2: can't imagine there'd be kids who are like seeing this

831
00:44:43,360 --> 00:44:47,640
Speaker 2: and they're like I want Blue. Ye, Like right, unless

832
00:44:47,800 --> 00:44:49,680
Speaker 2: you're able to start them off on this early, you know,

833
00:44:50,040 --> 00:44:50,560
Speaker 2: don't you think the.

834
00:44:50,600 --> 00:44:56,160
Speaker 1: Kids will inherently respond well to chip Chilla's inherently more

835
00:44:56,239 --> 00:45:01,200
Speaker 1: heteronormative household roles. Where Rob Schneider his father character, is

836
00:45:01,239 --> 00:45:04,400
Speaker 1: a distinctly alpha father named chum Chump.

837
00:45:04,640 --> 00:45:09,080
Speaker 10: Chip Chilla is also homeschooled because his family doesn't trust

838
00:45:09,120 --> 00:45:10,080
Speaker 10: the school system.

839
00:45:10,280 --> 00:45:15,279
Speaker 2: I'm sure when are those ones gonna come out to

840
00:45:15,480 --> 00:45:17,600
Speaker 2: like where it's like the teacher at school said I

841
00:45:17,640 --> 00:45:20,320
Speaker 2: needed to get a shot to keep the other kids safe,

842
00:45:20,680 --> 00:45:22,440
Speaker 2: right inevitably, Right.

843
00:45:22,640 --> 00:45:24,799
Speaker 10: That's actually I'm kind of okay. So, like I write

844
00:45:24,920 --> 00:45:26,879
Speaker 10: a lot of I write for kids TV a lot. Yeah,

845
00:45:26,920 --> 00:45:30,040
Speaker 10: and I've seen this new story. I'm obsessed with it.

846
00:45:30,200 --> 00:45:33,279
Speaker 10: Like me thinks like, oh yeah, this is insane, But

847
00:45:33,320 --> 00:45:35,719
Speaker 10: part of me is also thinking, like what sort of

848
00:45:35,840 --> 00:45:38,440
Speaker 10: crazy bullshit could I pitch to them to get them

849
00:45:38,480 --> 00:45:42,480
Speaker 10: to buy, Like if I like teenage mutant ninja firearms,

850
00:45:42,560 --> 00:45:45,520
Speaker 10: or instead of turning into turtles, they turn into guns, yeah, right,

851
00:45:45,800 --> 00:45:48,759
Speaker 10: like sol sold or just like Garfield, but instead of

852
00:45:48,880 --> 00:45:52,600
Speaker 10: hating Mondays, he hates being woke. He's always that ban

853
00:45:53,760 --> 00:45:56,239
Speaker 10: or like instead Thomas the tank engine, it's just like

854
00:45:56,280 --> 00:45:59,360
Speaker 10: Thomas the tank cannon or something pro military.

855
00:45:59,400 --> 00:46:04,680
Speaker 2: Would they be like Thomas Thomas the crowd dispersement vehicle.

856
00:46:06,920 --> 00:46:09,920
Speaker 2: Oh no, the people are complaining. Go Thomas is the.

857
00:46:09,920 --> 00:46:13,920
Speaker 1: Trend that broke up that union protest with like machine

858
00:46:13,920 --> 00:46:14,919
Speaker 1: guns on the back.

859
00:46:15,360 --> 00:46:18,080
Speaker 2: Yeah, Or he's the thing that like yeah, crashed in

860
00:46:18,400 --> 00:46:23,000
Speaker 2: like East Palestine, that horrible trained derailment. It's like they're

861
00:46:23,080 --> 00:46:25,319
Speaker 2: just they're they're they're mischaracterizing me.

862
00:46:25,680 --> 00:46:28,440
Speaker 10: Wait, can I put you all my dream Daily Wire

863
00:46:28,520 --> 00:46:29,800
Speaker 10: project please?

864
00:46:30,360 --> 00:46:30,800
Speaker 2: Okay.

865
00:46:30,880 --> 00:46:34,319
Speaker 10: So it's about a vampire who, instead of drinking your

866
00:46:34,320 --> 00:46:37,640
Speaker 10: blood with fangs, he injects vaccines into you with than

867
00:46:39,040 --> 00:46:44,440
Speaker 10: His name is his get this, His name is Vacula Vcula.

868
00:46:44,840 --> 00:46:48,240
Speaker 10: I think that it stars Scott BeO, canceled actor Scott

869
00:46:48,239 --> 00:46:49,200
Speaker 10: bo is.

870
00:46:49,200 --> 00:46:52,240
Speaker 2: Like a cop who got canceled just for doing what's

871
00:46:52,400 --> 00:46:54,320
Speaker 2: right or something like that exactly.

872
00:46:54,360 --> 00:46:56,920
Speaker 10: I think that it's revealed halfway through the Vacula is

873
00:46:57,000 --> 00:46:59,600
Speaker 10: Hunter Biden, and also Joe Biden's a villain too.

874
00:47:00,120 --> 00:47:00,760
Speaker 2: Yes, of course.

875
00:47:00,920 --> 00:47:02,840
Speaker 10: And there's definitely gonna be a line of dialogue in

876
00:47:02,880 --> 00:47:06,440
Speaker 10: this movie where the Scott bo penciled cop is holding

877
00:47:06,440 --> 00:47:09,440
Speaker 10: a shotgun and a scientist is telling him, like, you

878
00:47:09,560 --> 00:47:11,960
Speaker 10: just got to trust the science on this, h Why

879
00:47:12,000 --> 00:47:14,040
Speaker 10: don't you just like look at our research and appreciate it.

880
00:47:14,080 --> 00:47:16,560
Speaker 10: And then Scott Bayo will say, I do my own

881
00:47:16,640 --> 00:47:18,239
Speaker 10: research and then caca shotgun.

882
00:47:18,440 --> 00:47:22,600
Speaker 2: Yes? Who hell? Yeah? Now is there room for Dean

883
00:47:22,719 --> 00:47:24,719
Speaker 2: Kine and Kevin Sorbo in this?

884
00:47:24,840 --> 00:47:24,960
Speaker 1: Oh?

885
00:47:25,040 --> 00:47:26,920
Speaker 10: Yeah, yeah, Look, there's got to be a lot of uh,

886
00:47:27,040 --> 00:47:29,680
Speaker 10: there's gonna be a lot of heroes in this movie. Yeah, yeah,

887
00:47:29,840 --> 00:47:32,560
Speaker 10: James Woods Daily Wire. If you're listening to this, hit

888
00:47:32,640 --> 00:47:34,879
Speaker 10: me up. I think we could have you know, Rob

889
00:47:34,920 --> 00:47:38,240
Speaker 10: Schneider could play Vacula or like who's that former SNL

890
00:47:38,320 --> 00:47:41,719
Speaker 10: guy who's like who was goat Boy? Yeah, Jim Brewer,

891
00:47:42,600 --> 00:47:44,160
Speaker 10: I'd be great, he.

892
00:47:44,120 --> 00:47:46,200
Speaker 2: Would be He's a mess, dude. Have you seen his

893
00:47:46,360 --> 00:47:47,240
Speaker 2: stand up recently?

894
00:47:47,280 --> 00:47:47,360
Speaker 10: Oh?

895
00:47:47,440 --> 00:47:53,480
Speaker 2: It's insane. It's fucking it's morbidly bad. Like it's like

896
00:47:53,560 --> 00:47:55,319
Speaker 2: not even it's bad to a point where you're like

897
00:47:55,400 --> 00:47:59,000
Speaker 2: if that movie The Wrestler, we're about a stand up,

898
00:47:59,320 --> 00:48:01,919
Speaker 2: Like it's like we're seeing that version, like Mickey Rourke

899
00:48:02,080 --> 00:48:04,160
Speaker 2: is just like a down and out. It's just it's

900
00:48:04,200 --> 00:48:05,839
Speaker 2: so that's so distressing.

901
00:48:06,040 --> 00:48:08,160
Speaker 10: But what's okay. So what's wild about it is the

902
00:48:08,200 --> 00:48:11,240
Speaker 10: stand up. The jokes are bad, but he's performing largely

903
00:48:11,280 --> 00:48:14,240
Speaker 10: in front of churches and like very right wing friendly audiences,

904
00:48:14,480 --> 00:48:17,640
Speaker 10: and if you if you listen to the audience, it's

905
00:48:17,800 --> 00:48:21,239
Speaker 10: like they're watching like Eddie Murphy's raw, Like it's just

906
00:48:21,480 --> 00:48:23,799
Speaker 10: they're like eating it up right.

907
00:48:23,960 --> 00:48:26,719
Speaker 2: It's because like he does like this thing where he'll

908
00:48:26,760 --> 00:48:31,879
Speaker 2: be like and then you got like these democrats are Democrats. Yeah, yeah,

909
00:48:30,920 --> 00:48:35,200
Speaker 2: we like he just's like just over the top, like

910
00:48:35,360 --> 00:48:37,400
Speaker 2: just like Garl sounds and stuff.

911
00:48:37,400 --> 00:48:40,919
Speaker 10: You're like exactly, Yeah, yeah, I think there's something where

912
00:48:40,920 --> 00:48:43,279
Speaker 10: it's just like the Democrats sound like parakeets.

913
00:48:43,320 --> 00:48:45,680
Speaker 2: They're always like trust the science booker.

914
00:48:46,480 --> 00:48:52,120
Speaker 10: Yeah, that's his, that's his closer, right, Thank you so much.

915
00:48:52,160 --> 00:48:52,839
Speaker 2: I'm Jim Bury.

916
00:48:54,200 --> 00:48:56,920
Speaker 10: All right, you could hear me on the coming upside

917
00:48:56,920 --> 00:49:04,560
Speaker 10: of chip Chilla playing a racist cop, yeah.

918
00:49:02,239 --> 00:49:05,239
Speaker 1: Who actually saves the day it turns out. Yeah, it's

919
00:49:05,280 --> 00:49:07,200
Speaker 1: got some interesting things to say.

920
00:49:07,160 --> 00:49:11,200
Speaker 10: Racist cop who has some some real truths or whatever.

921
00:49:11,600 --> 00:49:14,319
Speaker 2: But they're also doing like live action right like on

922
00:49:14,360 --> 00:49:17,239
Speaker 2: this bench. Oh yeah, platform have.

923
00:49:17,200 --> 00:49:20,759
Speaker 1: We got one kid Explore a show called Kid Explorer

924
00:49:21,239 --> 00:49:24,360
Speaker 1: that appears to be like a recruitment tool for the

925
00:49:24,480 --> 00:49:25,960
Speaker 1: US military.

926
00:49:25,760 --> 00:49:28,239
Speaker 10: They all, they all appear to be a room tool

927
00:49:28,280 --> 00:49:29,200
Speaker 10: for the US military.

928
00:49:29,400 --> 00:49:31,880
Speaker 2: Yeah right, yeah. Even chip Chilla is about being like, hey,

929
00:49:31,920 --> 00:49:34,239
Speaker 2: and if you're too weak bodied, we can still use

930
00:49:34,280 --> 00:49:37,759
Speaker 2: you in like a drone operating trailer. Who knows, you know.

931
00:49:37,800 --> 00:49:41,680
Speaker 10: There's also apparently other Daily Wire movies they released. They

932
00:49:41,680 --> 00:49:43,720
Speaker 10: came up with a movie called Terror on the Prairie

933
00:49:43,840 --> 00:49:46,520
Speaker 10: in two and part of me is like, party wants

934
00:49:46,520 --> 00:49:48,000
Speaker 10: to watch the trailer, and then another part of me

935
00:49:48,080 --> 00:49:49,480
Speaker 10: is like, oh, I know that's going to be racist.

936
00:49:49,480 --> 00:49:54,239
Speaker 2: Advanced error on the Prairie sounds like it could be

937
00:49:54,400 --> 00:49:58,120
Speaker 2: something that's poignant, right, but it's just gonna go the

938
00:49:58,160 --> 00:50:01,279
Speaker 2: other way. Oh yeah, it it did go the other way.

939
00:50:01,360 --> 00:50:04,200
Speaker 1: Also, in terms of box office, it made a total

940
00:50:04,239 --> 00:50:06,560
Speaker 1: of eight hundred and four dollars at the bottom.

941
00:50:07,080 --> 00:50:09,839
Speaker 2: I'm just saying that they like fucking hurt my throat last.

942
00:50:10,280 --> 00:50:12,840
Speaker 10: I'm sorry, I'm just saying if they would green light Vacula,

943
00:50:12,920 --> 00:50:13,759
Speaker 10: that would make twice that.

944
00:50:14,400 --> 00:50:16,239
Speaker 2: Oh yeah, that would kill.

945
00:50:16,480 --> 00:50:19,840
Speaker 1: By the way, it does reflect our Like we've talked

946
00:50:20,160 --> 00:50:26,319
Speaker 1: before about something in my childhood made me think that

947
00:50:26,480 --> 00:50:30,360
Speaker 1: Dracula had hollow fangs that sucked the blood through the fangs.

948
00:50:30,600 --> 00:50:32,680
Speaker 10: Oh yeah, yeah yeah, like a like yeah, like a

949
00:50:32,760 --> 00:50:34,040
Speaker 10: reverse Cobra or something.

950
00:50:34,160 --> 00:50:34,359
Speaker 2: Yeah.

951
00:50:34,440 --> 00:50:39,360
Speaker 1: Yeah, And people, I don't think that was an assumption

952
00:50:39,440 --> 00:50:41,920
Speaker 1: made by everyone, but no, we kind of mentioned it

953
00:50:41,960 --> 00:50:42,840
Speaker 1: that it proves it.

954
00:50:43,120 --> 00:50:45,680
Speaker 2: Yeah. Yeah, we're team hollow. We've been hollow for We're

955
00:50:45,680 --> 00:50:48,439
Speaker 2: team hollow fangs. Yeah, I'm team hollow. I'm for that,

956
00:50:48,520 --> 00:50:52,759
Speaker 2: all right? Cool? Like yeah, update the update. The reesis commercial.

957
00:50:52,880 --> 00:50:56,120
Speaker 2: So there's like two holes, you know what. Yeah, so

958
00:50:56,160 --> 00:50:58,920
Speaker 2: you can see, oh there were I think I think

959
00:50:59,200 --> 00:51:02,120
Speaker 2: Reces is team Halo Fang.

960
00:51:02,320 --> 00:51:04,480
Speaker 10: Yeah, I think, okay, but I'm just saying, what if

961
00:51:04,520 --> 00:51:06,799
Speaker 10: instead of having Holo fangs, he had fangs that had

962
00:51:06,880 --> 00:51:11,960
Speaker 10: little syringes that came out absolutely hard selling vacula.

963
00:51:12,360 --> 00:51:13,600
Speaker 2: Those fangs go two ways?

964
00:51:13,880 --> 00:51:14,080
Speaker 1: Yeah?

965
00:51:14,200 --> 00:51:16,719
Speaker 2: Yeah, oh, I think we're saying the logic of the

966
00:51:16,800 --> 00:51:19,320
Speaker 2: Reces being team Hollo Fang wasn't because of the indents,

967
00:51:19,400 --> 00:51:23,600
Speaker 2: but because what the indents represented was yeah, the peanut butter.

968
00:51:23,680 --> 00:51:26,480
Speaker 2: Yeah yeah, so put but I was talking about, like

969
00:51:26,520 --> 00:51:31,000
Speaker 2: how you represent it doesn't matter because I don't understand.

970
00:51:31,320 --> 00:51:33,799
Speaker 10: Okay, so I guess okay, so my my, so my

971
00:51:33,920 --> 00:51:37,360
Speaker 10: bump there is that I'm also very much team Hollow Fang.

972
00:51:37,840 --> 00:51:40,399
Speaker 10: But like blood is a liquid, I feel like if

973
00:51:40,400 --> 00:51:44,560
Speaker 10: you drank peanut butter, like you drank blood, you'd like choke, right.

974
00:51:44,520 --> 00:51:47,400
Speaker 2: Total mess. Yeah oh yeah, it would just clog up

975
00:51:47,400 --> 00:51:50,240
Speaker 2: your fangs. Yeah, clog up your fangs. Yeah. The dentist

976
00:51:50,320 --> 00:51:52,319
Speaker 2: would be like, oh man, you're doing the peanut butter

977
00:51:52,360 --> 00:51:54,360
Speaker 2: thing again. I told you it's hard to get out.

978
00:51:54,200 --> 00:51:55,919
Speaker 10: Also, I feel like that would be like a real

979
00:51:55,960 --> 00:51:57,920
Speaker 10: pain to clean inside your fangs.

980
00:51:58,280 --> 00:52:02,600
Speaker 1: Oh yeah, oh yeah, said nobody said this Dracula stuff

981
00:52:02,680 --> 00:52:06,399
Speaker 1: was going to be easy. Man, it's yere right, you're

982
00:52:06,480 --> 00:52:08,239
Speaker 1: you've been turned by him, Like what the fuck?

983
00:52:08,360 --> 00:52:10,640
Speaker 2: Man? Like the maintenance and ship on the fangs, you

984
00:52:10,680 --> 00:52:13,320
Speaker 2: never told me. It's like, hey man, no, yeah.

985
00:52:13,160 --> 00:52:17,120
Speaker 10: I gotta buy Yeah it was, yeah, I got so

986
00:52:17,200 --> 00:52:21,960
Speaker 10: that sounds as you're sadly cleaning your fangs with pipe cleaners, my.

987
00:52:22,200 --> 00:52:25,160
Speaker 1: Little pipe cleaners going in the points of your fangs.

988
00:52:25,400 --> 00:52:28,720
Speaker 2: This this like a New Explorer though. These images from

989
00:52:28,800 --> 00:52:32,799
Speaker 2: the New Explorer show are fucking like you can already tell, right,

990
00:52:32,840 --> 00:52:35,640
Speaker 2: Like there's a kid in like a fucking bomber jacket

991
00:52:35,680 --> 00:52:38,960
Speaker 2: in front of like a dream from Yeah man, this

992
00:52:39,040 --> 00:52:41,040
Speaker 2: is how we this is how we make it rain.

993
00:52:41,520 --> 00:52:44,439
Speaker 2: And then another one that seems like a Revolutionary War

994
00:52:44,640 --> 00:52:47,520
Speaker 2: soldier but with a Thompson gun. I don't know, I

995
00:52:47,560 --> 00:52:49,120
Speaker 2: don't know. I don't know what they're going to say here.

996
00:52:49,160 --> 00:52:50,480
Speaker 2: I don't know what kind of cool stuff they're going

997
00:52:50,520 --> 00:52:50,799
Speaker 2: to be saying.

998
00:52:50,880 --> 00:52:53,440
Speaker 1: This facial expression suggests he's in the middle of murdering

999
00:52:53,480 --> 00:52:57,839
Speaker 1: someone of the Revolutionary War Kid is like this or.

1000
00:52:57,840 --> 00:53:01,919
Speaker 2: Yeah, it has the feeling of like a nineties toy commercial. Yes, yeah,

1001
00:53:02,040 --> 00:53:06,520
Speaker 2: like the Red Coats, Yeah, like that kind of shit. Yeah.

1002
00:53:06,520 --> 00:53:09,720
Speaker 10: They're also on that note. They're making a Ryle snow

1003
00:53:09,760 --> 00:53:13,319
Speaker 10: White movie. Where get this snow Whites played by a

1004
00:53:13,360 --> 00:53:17,399
Speaker 10: white woman. Yes, well that's a big change. Yeah, yeah

1005
00:53:17,440 --> 00:53:17,759
Speaker 10: it is.

1006
00:53:18,160 --> 00:53:20,800
Speaker 1: They've been really upset about the snow Like. It seems

1007
00:53:20,840 --> 00:53:24,920
Speaker 1: like the snow white thing is the whole impetus behind this, right,

1008
00:53:25,400 --> 00:53:29,520
Speaker 1: just they've been so mad that the star of Disney's

1009
00:53:29,560 --> 00:53:31,840
Speaker 1: Actual Snow White, which they might have to change the

1010
00:53:31,920 --> 00:53:35,799
Speaker 1: title to Disney's Actual snow White. Rachel Ziggler had the

1011
00:53:35,800 --> 00:53:39,480
Speaker 1: goal to call the original movie dated. It came out

1012
00:53:39,520 --> 00:53:44,000
Speaker 1: in nineteen thirty seven. I actually rewatched it for the

1013
00:53:44,040 --> 00:53:47,480
Speaker 1: Bechdel cast, And it's not just it is like the

1014
00:53:47,520 --> 00:53:52,160
Speaker 1: most profoundly sexist, Like if you do a close reading

1015
00:53:52,200 --> 00:53:56,920
Speaker 1: of the movie, like what it's saying about snow White.

1016
00:53:57,760 --> 00:54:00,320
Speaker 10: It's like, if you kiss a lady while she's a sleep,

1017
00:54:00,400 --> 00:54:01,359
Speaker 10: she has to love you.

1018
00:54:01,600 --> 00:54:06,080
Speaker 1: Yes, and if she only like every time she does

1019
00:54:06,160 --> 00:54:09,560
Speaker 1: something she is putting herself in dates, she's just like

1020
00:54:09,719 --> 00:54:14,480
Speaker 1: dizzily wandering into life threatening situations. The entire movie, she

1021
00:54:14,560 --> 00:54:18,200
Speaker 1: like runs away from the hunter and like runs into

1022
00:54:18,239 --> 00:54:21,759
Speaker 1: the woods and passes out and is like surrounded by

1023
00:54:21,800 --> 00:54:23,920
Speaker 1: a bunch of wild animals and the only reason the

1024
00:54:23,920 --> 00:54:26,719
Speaker 1: wild animals don't like eat her is because she's like

1025
00:54:26,800 --> 00:54:30,240
Speaker 1: really pretty when she's asleep. And then she also almost

1026
00:54:30,239 --> 00:54:33,640
Speaker 1: gets murdered. She like break breaks into the seven Dwarfs

1027
00:54:33,640 --> 00:54:36,520
Speaker 1: home and like falls asleep in their bed. They almost

1028
00:54:36,640 --> 00:54:37,200
Speaker 1: murder with.

1029
00:54:37,120 --> 00:54:40,080
Speaker 2: A pick axe. She rolls over it in her sleep.

1030
00:54:39,840 --> 00:54:42,560
Speaker 1: And they're like, ah, she's so pretty. And then like

1031
00:54:42,880 --> 00:54:46,160
Speaker 1: when she eats a poisoned apple, like that is clearly

1032
00:54:46,320 --> 00:54:47,640
Speaker 1: put like the person giving it.

1033
00:54:47,640 --> 00:54:53,759
Speaker 2: To her is given snake exactly.

1034
00:54:54,160 --> 00:54:56,759
Speaker 1: And then the only thing that saves her there is

1035
00:54:56,840 --> 00:54:59,400
Speaker 1: again when she's asleep, Like she has to be asleep

1036
00:54:59,600 --> 00:55:04,040
Speaker 1: for good things to happen, be beautiful and passive to succeed.

1037
00:55:04,600 --> 00:55:08,440
Speaker 1: Be beautiful and passed out is literally the message of

1038
00:55:08,480 --> 00:55:09,720
Speaker 1: the It's fucked.

1039
00:55:10,160 --> 00:55:11,520
Speaker 2: So what do you think the message will be with

1040
00:55:11,560 --> 00:55:12,200
Speaker 2: this one? Huh?

1041
00:55:12,440 --> 00:55:15,279
Speaker 1: Probably the same, Like I don't know, like I don't

1042
00:55:15,320 --> 00:55:18,000
Speaker 1: know if they could even do it, but I'm sure

1043
00:55:18,000 --> 00:55:20,839
Speaker 1: they could, Like it feels like they'll find it.

1044
00:55:21,000 --> 00:55:24,160
Speaker 2: Updating it for modern times. Yeah, are you? Yeah?

1045
00:55:24,239 --> 00:55:27,600
Speaker 10: Yeah, the Daily Wire will find a way, Yeah, as

1046
00:55:27,640 --> 00:55:28,239
Speaker 10: they always do.

1047
00:55:28,600 --> 00:55:28,799
Speaker 2: Yeah.

1048
00:55:28,840 --> 00:55:32,560
Speaker 1: The teaser trailer suggests the movie has not been shot yet,

1049
00:55:32,600 --> 00:55:36,480
Speaker 1: but does reveal that they cast a white actress of

1050
00:55:36,560 --> 00:55:40,839
Speaker 1: snow white and also have access to stock footage of

1051
00:55:40,880 --> 00:55:45,399
Speaker 1: a national park. Okay, okay, but yeah, but yeah, there

1052
00:55:45,600 --> 00:55:50,120
Speaker 1: are movies up to this point have averaged two hundred

1053
00:55:50,120 --> 00:55:53,720
Speaker 1: and thirty six thousand dollars at the worldwide box office.

1054
00:55:54,320 --> 00:55:58,760
Speaker 1: Oh and this is These are movies produced by Ben Shapiro,

1055
00:55:59,239 --> 00:56:02,839
Speaker 1: person who like went to see Barbie on opening day

1056
00:56:03,160 --> 00:56:07,040
Speaker 1: and like did created like seven hours of content just

1057
00:56:07,360 --> 00:56:08,279
Speaker 1: railing about like.

1058
00:56:08,320 --> 00:56:13,359
Speaker 10: How destroys Barbie for three hours or whatever that videos called.

1059
00:56:13,760 --> 00:56:16,239
Speaker 1: Yeah, and it tanked the box office for Barbie, but

1060
00:56:16,400 --> 00:56:17,600
Speaker 1: nobody wants to see it after.

1061
00:56:17,719 --> 00:56:22,320
Speaker 2: Yeah, yeah, he really got his way. So that's really funny.

1062
00:56:22,400 --> 00:56:25,239
Speaker 10: Like how heavily the Go Woke, Go Broke Brigade was

1063
00:56:25,320 --> 00:56:28,239
Speaker 10: like really attacking the Barbie movie only for it to

1064
00:56:28,320 --> 00:56:32,000
Speaker 10: make one one to make one point five billion dollars

1065
00:56:32,080 --> 00:56:33,160
Speaker 10: of profit, like.

1066
00:56:34,840 --> 00:56:40,480
Speaker 2: Just the most successful movie. Yeah, yeah, yep, go broke. Yeah,

1067
00:56:40,480 --> 00:56:44,000
Speaker 2: too bad, they went broke. Uh huh uh huh. Ours,

1068
00:56:44,239 --> 00:56:45,919
Speaker 2: that's why you really want to be shooting for around

1069
00:56:45,920 --> 00:56:49,239
Speaker 2: two hundred and thirty k Yeah that's the real or

1070
00:56:49,280 --> 00:56:51,560
Speaker 2: like eight hundred dollars five weeks. Yeah.

1071
00:56:51,600 --> 00:56:53,880
Speaker 10: Yeah, it's like, Okay, it made two hundred billion dollars,

1072
00:56:53,920 --> 00:56:56,239
Speaker 10: but did it make eight hundred dollars? Check meate whoa

1073
00:56:56,440 --> 00:56:57,200
Speaker 10: whoa brigade.

1074
00:56:57,239 --> 00:56:57,879
Speaker 2: And they have been.

1075
00:56:57,800 --> 00:57:01,080
Speaker 1: Defending the movie's performance, being like we didn't even like

1076
00:57:01,160 --> 00:57:04,040
Speaker 1: put it out in wide release, like they wouldn't have

1077
00:57:04,360 --> 00:57:07,920
Speaker 1: if they have, like the choice that they made.

1078
00:57:08,360 --> 00:57:10,560
Speaker 2: Actually, we don't even want people to see this movie.

1079
00:57:10,760 --> 00:57:12,400
Speaker 2: That's like the whole point, dude, And that's why you

1080
00:57:12,440 --> 00:57:13,800
Speaker 2: don't get it. That's why you're like a part of

1081
00:57:13,840 --> 00:57:16,760
Speaker 2: the mainstream like fucking echo chamber broke idea, but no legit.

1082
00:57:16,840 --> 00:57:18,600
Speaker 10: Like that's something that I'm kind of thinking about with

1083
00:57:18,640 --> 00:57:21,680
Speaker 10: like all of this stuff is like specifically Daily Wire

1084
00:57:21,720 --> 00:57:24,720
Speaker 10: stuff is like is this just Ben Shapiro trying to

1085
00:57:24,760 --> 00:57:28,680
Speaker 10: steal money from VC funders like because oh yeah, yeah,

1086
00:57:28,720 --> 00:57:30,800
Speaker 10: you know it's like this feels like a tax scheme.

1087
00:57:31,520 --> 00:57:38,040
Speaker 2: Yeah totally. Man, damn took huge losses on all those movies. Yeah, yeah,

1088
00:57:38,080 --> 00:57:39,919
Speaker 2: like what are the budgets because that's what you're really

1089
00:57:39,920 --> 00:57:42,400
Speaker 2: going to see. The magic in the in the accounting happen.

1090
00:57:44,000 --> 00:57:48,680
Speaker 1: All Right, that's gonna do it for this week's weekly Zeitgeist.

1091
00:57:48,720 --> 00:57:52,200
Speaker 1: Please like and review the show if you like, The

1092
00:57:52,280 --> 00:57:57,040
Speaker 1: show means the world to Miles. He he needs your validation.

1093
00:57:57,200 --> 00:57:57,560
Speaker 2: Folks.

1094
00:57:58,160 --> 00:58:01,000
Speaker 1: I hope you're having a great week end and I

1095
00:58:01,040 --> 00:58:49,520
Speaker 1: will talk to you Monday. Bye.