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This is Evolutionary Psychology the Podcast.

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Actual Evolutionary Psychology by Actual Evolutionary Psychologists.

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David, today we are talking to Chris Smith.

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Chris Smith with a K.

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That's right.

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Um, and we had a really fun conversation with Chris.

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Uh we talked all about uh his fieldwork with both uh the Hadza

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and another another community he was working with with and and Pizer.

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We spoke to our previous episode.

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Both are in Tanzania um yes, and I don't I I couldn't pr pronounce

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correctly.

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You'll have to listen to the episode to hear the correct pronunciation.

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That's a nice incentive for you to listen.

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Uh so that you can get the the name of of this uh fishing community.

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But yeah, we talked about partner choice, cooperation, um norms,

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the uh the methodological difficulties of doing anthropological field work, the

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collision of theory with reality.

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It was a really fun conversation.

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Did I did I miss anything there, Dave?

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Uh mosquitoes and um I think mosquitoes.

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Oh and climate change we talked about.

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Yeah how yeah how communities are adapting to climate change.

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Um yeah it was it was super fun and interesting.

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Chris is always a great hang.

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Yeah.

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And uh it's really nice to have uh anthropologists on and you uh thanked him for his

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service several times as is appropriate.

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That's true.

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And if you are an anthropologist listening, thank you for your service.

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Uh wonderful.

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So uh without further ado, here is Chris Smith, David and I talking about um what Chris has

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learned in the field and uh what it might mean for for all of us.

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Yep, enjoy.

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Chris, thank you for being here.

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How are you doing today?

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I'm doing great.

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Thank you for having me.

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Uh happy to chat with you all and uh yeah.

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All right, great.

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Um we just saw you in person at HBus.

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Um we were all talking before we started about um how some of us uh fell ill and some of us

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didn't and maybe we'll get to illness um in in later in the conversation.

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You do um field work.

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Um can you tell us a little bit about where you do your field work?

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I feel like we we had a long stretch of anthropologists on.

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We've lately had psychologists and we're we psychologists are boring folks because you know

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we don't do fieldwork.

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So can you tell us a little bit about where you have done or currently do field work?

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Um and maybe that'll start us off.

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And if not, you could just talk about the wonderful drawing behind you.

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Yeah.

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Uh well it's funny because I I straddle psychology and anthropology, right?

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Uh exactly.

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Yeah.

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I think of you, yes.

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I think of you um uh I I'm a psychologist, so I think it's great to be

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a psychologist.

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So for better or worse, I think of you as a psychologist too.

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So yes, exactly.

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Uh well, I try to tell my department I'm an anthropologist now.

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Okay.

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Uh well I said out.

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Well, I said two, so it's both.

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Yeah.

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Yeah.

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Um, so I work uh in East Africa.

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So I started working in 2016 in Tanzania, working with Hadza

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hunter-gatherers.

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Um, I moved towards the coast of Tanzania in 2021 on a more recent project

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working with uh fishermen and fishing villages along the coast of Tanzania.

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And most recently I started working in Kenya, collaborating with some veterinarians and

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epidemiologists, um, primarily in northern Kenya and Marsebit, working with uh

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pastoralists, so Gabra and Rendile.

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Um, so I've uh had a chance to really explore quite a bit of East Africa now over the

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years.

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Wow.

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And was are those locations especially for us psychologists, um,

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or those of us who don't do any of any of this, uh, how does one get a field site or how

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what's the how do you get there and then why do you go to a different one?

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Is it convenience?

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Is it that the question you're asking is well suited to being answered in in that place?

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Is it you know people, all the above?

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Yeah, so I think I think you'd like to say, well, it's you know, new research questions,

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and this was you know uh intentionally chosen for this reason.

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Uh I think the reality for many of us, including me, is that it's often sort of convenience

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and happenstance.

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So I started working with uh Hadza um because my one of my advisors, Kirin

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Apicella, she's an anthropologist in uh psychology at Penn.

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Um She worked with Hadza with her advisor, Frank Marlowe.

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And so at one point we were collaborating on a project and she sent me out there to start

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collecting data.

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And so, you know, the first field experience, there's there's some stories there, but

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started going back out and sort of building, you know, importantly, linguistic skills and

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sort of knowing how to navigate the country and its uh all its administrative and

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bureaucratic stuff.

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And so after um during COVID, uh my postdoc at Penn was running

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out, and this opportunity came up to work with Ann Paiser, who was at Washington State, is

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now at uh Penn State, uh, looking at between community cooperation um among

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fisheries uh along the coast.

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And so I was hired to do that um in part again because I had that experience in Tanzania

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working um with Hadza, uh knew my Key Swahili.

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Um, and then it just sort of starts, you know, the the Kenya site came up from a

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collaboration.

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So here at uh WSU in our School for Global Health, we have an NGO situated in

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Kenya with a lot of infrastructure.

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They have like permanent staff.

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And so collaborating with them to access some of the communities that they've worked with,

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you know, they have this huge like surveillance project for like MERS uh and camels up

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there.

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And so, you know, part of it's like said, sort of happenstance.

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Some of it, you know, is the question makes more sense in these communities.

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You know, the challenge, I don't think, is starting up the field site.

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I mean, you know, connections help.

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It's often maintaining the field site.

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So I wouldn't be working at all these different field sites if I didn't have collaborators

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who are helping maintain these relationships.

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So I haven't been back to Hadza Land since 2019, but I still collaborate with folks like

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Duncan Stibbard Hawks.

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Right.

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And so he's actively working there.

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My colleagues in vetmed working with uh populations in Kenya makes it easier for me to have

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you know these different opportunities.

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Um, but right now I'm hoping, anyways, my main focus will be the the fishery communities uh

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in Tanzania.

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Cool.

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Well, thank you for your service.

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Um exactly.

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Thank you for yeah.

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Um for me, I feel like your your research has um

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changed my mind about a few things in the evolutionary psychology of cooperation.

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And I feel like that's one of the virtues of doing fieldwork is that you know we have our

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our abstract theories and then we try to see if they work in the real world uh in a real

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setting that you know hopefully resembles some aspect of our uh evolutionary history or the

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ancestral environment.

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And our theories just kind of collide with reality and and we are forced to rethink things.

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So what are some of the things that you have had to rethink uh as a result of your work

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with with the Hadza and and with with other communities?

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Yeah, I that's a great question.

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So, you know, originally I wanted to be a pretty standard experimental psychologist.

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I was running my uh experiments in the lab, surveys online.

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Um, and this opportunity to work with uh Hadza came up from uh, you know, Corinne and I

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collaborating on a project together.

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Um and I thought, you know, I should do this.

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I'll uh I I didn't think I would do it forever or make it a core part, but I thought, you

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know, I gotta take this opportunity.

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Um and what ended up changing my mind was some of the findings from that.

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So I was working on we have this finding, Corinne has this finding uh in one of her classic

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papers where if you play a public goods game with Hadza Hunter Gatherers, that is um you

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give them some honey sticks, they can contribute some to uh a public good, and that's

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tripled and then shared with everyone that's living with them in their camp.

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Um, right, classic game to measure cooperation.

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Uh, in two different uh years, she got this finding where uh camps,

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uh, there are significant differences in how much camps cooperated.

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So if you uh look at like how it clusters within camps, some camps are cooperating more,

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some are cooperating less.

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Um, these camps move different locations and different times, they're different people are

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also living these camps.

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These aren't permanent social units.

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And so it doesn't seem like that's easily explained by ecology because it varied from year

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to year or from people.

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And so sort of the thing we wanted to investigate was what explains this clustering.

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And so there's a couple of mechanisms you can think about.

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You could think like reputation and partner choice or people selecting to live with people

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who are more cooperative.

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And that's why you get that clustering in camps.

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Or is it something like norms and punishment, right?

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People, uh, some camps have stronger norms, and so you have more uh sharing in these games.

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And I very much went in expecting partner choice to be like the really important

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mechanism here.

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And um, from the games, that doesn't seem to be the case.

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Uh, we didn't find any sort of uh stable willingness to cooperate across the years

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when we played this game with multiple uh multiple years with the same people.

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Uh, we didn't see people were ending up in more cooperative camps that they were previously

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more cooperative.

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And then we did this task where we asked people to rank their campmates.

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So we go in, we take Polaroid photos of each member of the camp.

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And then privately we we put out all the photos in front of them.

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We ask who's the most generous big person.

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And they repeat this until they rank everyone.

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We do this for things like generosity, uh, productivity.

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So how good of a hunter you are, um, and who do you want to live with, right?

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And so choosing who you want to live with is choosing who you're cooperating with in these

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camps where you have these strong uh inset uh norms to share food, right?

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So we use this as a measure of partner choice.

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And what we found, what I found that first year was that they didn't really care about who

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jet how generous the people they were living with were.

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Instead, they cared about, you know, who were good hunters, who were good gatherers.

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Um, and so that sort of, I I will say that I really did not like my first field season.

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I swore I would never do it again.

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But like digging through that data and having to sort of adjust, you know, what I thought

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was driving cooperation in this population uh really made me excited for it, right?

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In a way that I didn't get from lab experiments.

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So to your point, yeah, that that experience of theories meeting reality.

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Um and you know, doing the field work, you're right there to see it happen, right?

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It's it's sort of happening in real time for you.

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Yeah.

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Uh makes the field work fun and and exciting.

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Wow.

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So interesting.

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So I I want kind of wanna unpack this this result in these findings.

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So um people members of the Hadza are more

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interested in hunting and foraging ability more than uh generosity.

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So really, do you have the skills uh is more important that question is more important than

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are you willing to share the fruits of your labor?

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Uh do you think what might be going on there is that there's just kind of sharing by

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default?

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And so individual variation in sharing willingness just isn't a factor.

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It isn't really important because you're going to get some of the kill uh regardless.

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Or is it or is something else going on?

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Yeah, so that that's a really great way to put put it, right?

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So Hadza, like uh almost every hunter-gatherer that we have data from, really strong food

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sharing norms, especially with meat.

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Any meat that they bring back to camp is something they're expected to share.

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Now they do try to get around it.

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There's some famous stories of Hadza like asking uh researchers to hide like a kill

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underneath their uh truck and come back later for it.

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So it it's not automatic, but in that context where most things are going to be shared

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anyways, then yeah, it makes sense to focus on foraging ability instead, right?

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What what are you going to bring back to the camp?

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And if you look at partner choice models, you see this more formally, right, that the

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variance of traits matter.

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So if there's very little variance on a trait, then the marginal benefit of choosing

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someone higher on that trait is lower.

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And so one thing we find actually is that this effects uh reversed when I came back in

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2019.

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So in 2019, they did place more of an emphasis on generosity than productivity.

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And what we found was that this was really driven by people who had more experience outside

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of Hazeland.

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So if they had worked jobs for cash, if they had uh lived in a village at some point.

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And so now what we find, and Duncan, uh my Duncan Stibbard Hawks has data on this as well.

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A lot of HODs are now moving between uh the bush and villages.

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And when they're in the village, there's less uh sharing norms, there's less uh incentive

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and pressure to share as much.

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Um, in fact, uh, Duncan has pictures, they they have houses that they just store all their

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grain and they don't share any of their grain with anyone.

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Um, and so now when we're asking people who do you want to live with, the reality is

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their social world includes all these people who are also living in villages without these

238
00:13:29,090 --> 00:13:29,490
norms.

239
00:13:29,650 --> 00:13:33,890
And so what's happening is that, at least what we think, I never was able to follow up on

240
00:13:33,890 --> 00:13:39,330
this, is that the variance in sharing, willingness to share, is increasing as they have

241
00:13:39,330 --> 00:13:42,370
more experience moving between these two different social worlds.

242
00:13:42,530 --> 00:13:46,530
And so once you have more variance there, now that becomes more important when choosing a

243
00:13:46,530 --> 00:13:47,570
cooperative partner.

244
00:13:48,940 --> 00:13:49,580
Interesting.

245
00:13:49,820 --> 00:13:55,580
So could it be that when you earn wealth outside of Hadza Land, that

246
00:13:55,580 --> 00:13:59,660
wealth is easier to conceal from your fellow groupmates?

247
00:13:59,820 --> 00:14:04,780
And whether or not the groupmates get some of that depends more on the person's generosity

248
00:14:04,940 --> 00:14:08,540
because they can they can hide what whatever they gain, they can hide their cash, they can

249
00:14:08,540 --> 00:14:09,500
hide their grain.

250
00:14:09,580 --> 00:14:13,420
Uh and it really depends on how nice or generous that person is.

251
00:14:13,660 --> 00:14:19,370
Um whereas if you hunt a a a a zebra, it's gonna be pretty hard to hide that

252
00:14:19,370 --> 00:14:23,930
zebra from the rest of the people in your group and they're gonna uh, you know, pressure

253
00:14:23,930 --> 00:14:25,530
you uh to get some of that.

254
00:14:25,690 --> 00:14:30,330
And so could it be that it's the concealability of the resource that might be driving this?

255
00:14:30,810 --> 00:14:33,690
I I I think uh most likely that's part of it.

256
00:14:33,850 --> 00:14:38,880
It's easier to to your point, it's easier to hide what you have in terms of wealth, uh,

257
00:14:39,040 --> 00:14:42,320
you're more able to uh accumulate wealth to begin with, right?

258
00:14:42,400 --> 00:14:46,640
So if you're in these mobile camps, it's really hard to have a lot of property if you have

259
00:14:46,640 --> 00:14:47,920
to move every few weeks.

260
00:14:48,080 --> 00:14:52,320
Um, and then of course, uh again, what what we see is that when they're in these villages,

261
00:14:52,480 --> 00:14:54,160
they're relying a lot more on grain.

262
00:14:54,240 --> 00:14:56,720
They they rely on grain in the camps now too.

263
00:14:56,880 --> 00:15:01,440
Um, but they're relying more on grain, which is also easier to store than meat.

264
00:15:01,550 --> 00:15:06,990
So I think it's a a combination of these different sort of ecological factors that changing

265
00:15:06,990 --> 00:15:11,550
how they're able to store food and changing sort of the sharing norms, right?

266
00:15:11,630 --> 00:15:14,030
And so I think that's sort of the mediating.

267
00:15:14,110 --> 00:15:18,350
Like we could measure their uh sort of perceived norms.

268
00:15:18,510 --> 00:15:21,790
I imagine they differ between the camps and the villages.

269
00:15:21,870 --> 00:15:26,660
And like that would be the mediating factor, is that they're tracking, you know, how how

270
00:15:26,660 --> 00:15:31,380
much variance is there out in the world in generosity, and that's impacting how much they

271
00:15:31,540 --> 00:15:36,420
at least emphasis on generosity versus productivity when choosing cooperative partners.

272
00:15:36,740 --> 00:15:36,980
Yeah.

273
00:15:37,220 --> 00:15:42,260
One question is so we've been talking about it as sort of the emphasis on productivity as

274
00:15:42,260 --> 00:15:43,620
opposed to generosity.

275
00:15:43,860 --> 00:15:48,260
And we've been think talking about it from the perspective of why is generosity not being

276
00:15:48,260 --> 00:15:48,660
used.

277
00:15:48,820 --> 00:15:52,660
I'd like to invert it because that's been very interesting, but I'd also like to invert it

278
00:15:52,660 --> 00:15:58,650
and say, what is it in the um you sorry use the word village and then

279
00:15:58,650 --> 00:15:59,450
what's the other term?

280
00:15:59,770 --> 00:16:00,170
Bush.

281
00:16:00,410 --> 00:16:00,650
Bush.

282
00:16:00,890 --> 00:16:01,050
Okay.

283
00:16:01,130 --> 00:16:01,290
Yeah.

284
00:16:01,370 --> 00:16:05,770
So when they're in the bush, or people to the extent that in the prior calibration of being

285
00:16:05,770 --> 00:16:08,490
in the bush, you're going on productivity.

286
00:16:09,130 --> 00:16:14,490
It that is that is also in is that the only other positive attribute, or is that actually

287
00:16:14,490 --> 00:16:20,010
interesting in the sense of that is a sensical, rational allocation

288
00:16:20,220 --> 00:16:23,820
of resources, what does that mean in the context of the bush?

289
00:16:23,980 --> 00:16:27,500
And then what does it mean that it's not happening in the village?

290
00:16:27,660 --> 00:16:32,860
Like, for example, is it that um you're not you're you're

291
00:16:32,860 --> 00:16:38,620
abandoning what had previously been uh a dimension of status, or is it

292
00:16:38,860 --> 00:16:40,700
is that reading too much into it?

293
00:16:41,340 --> 00:16:45,190
That I I I um that might be reading a little too much into it.

294
00:16:45,270 --> 00:16:47,670
Dun Duncan has done the work of actually visiting.

295
00:16:47,750 --> 00:16:49,750
I didn't get a chance to visit the villages.

296
00:16:49,830 --> 00:16:52,310
It was a planned follow-up before COVID.

297
00:16:52,550 --> 00:16:57,990
Um and so he he would know more, but my understanding is that they're still hunting there.

298
00:16:58,230 --> 00:17:02,550
Um and so so another way to look at it right here is that the benefits you get from a

299
00:17:02,550 --> 00:17:06,630
cooperative partner is both their willingness to actually help you and their their ability,

300
00:17:06,710 --> 00:17:06,950
right?

301
00:17:07,190 --> 00:17:10,950
Someone who's a total klutz but is really generous is as helpful as someone who's really

302
00:17:10,950 --> 00:17:12,520
selfish and and really effective, right?

303
00:17:12,600 --> 00:17:13,640
You need kind of both.

304
00:17:13,880 --> 00:17:16,280
The question is, you know, how much emphasis to place.

305
00:17:16,440 --> 00:17:21,640
And so uh another possibility is that there's also less variance in productivity or

306
00:17:21,640 --> 00:17:25,160
competence in the uh villages than the camps.

307
00:17:25,320 --> 00:17:29,160
Hunting's a really uh high risk uh activity.

308
00:17:29,400 --> 00:17:34,040
I think they have like a 3% uh hunting uh success rate, is the classic statistic.

309
00:17:34,280 --> 00:17:39,450
So, you know, being a little bit better can have a massive effect on productivity there in

310
00:17:39,450 --> 00:17:43,130
the villages where they're hunting a little bit, but they're also farming a little and

311
00:17:43,130 --> 00:17:43,930
keeping gardens.

312
00:17:44,090 --> 00:17:49,770
There might be less variance in um competence there or productivity.

313
00:17:50,010 --> 00:17:55,130
Gathering's another example where there's still skills involved in gathering and an ability

314
00:17:55,130 --> 00:18:00,250
to uh endure, but probably less so than um what we find with hunters.

315
00:18:00,330 --> 00:18:05,000
And there was some kind of a suggestive effect that women placed a little less emphasis on

316
00:18:05,000 --> 00:18:06,680
other women's uh productivity.

317
00:18:06,760 --> 00:18:08,520
So that that would also be consistent.

318
00:18:08,680 --> 00:18:13,400
That again, what they're trying to track is really what's the benefit of switching to a new

319
00:18:13,400 --> 00:18:14,200
partner here.

320
00:18:14,360 --> 00:18:17,880
And really there's got to be enough variance for that to really make sense because there's

321
00:18:17,880 --> 00:18:21,560
costs and moving and and you know trying out new uh cooperative partners.

322
00:18:21,870 --> 00:18:22,110
Yeah.

323
00:18:22,270 --> 00:18:24,590
The the variance point is really uh deep.

324
00:18:24,670 --> 00:18:27,070
And I think we've talked about David and I have talked about that a bunch.

325
00:18:27,150 --> 00:18:30,830
That, you know, because as you said, Chris, lots of things are skill dependent.

326
00:18:30,910 --> 00:18:34,110
I mean, even walking is skill dependent, but there's not much variance in that.

327
00:18:34,270 --> 00:18:39,870
And so I think for a lot of status things, what I'm hearing you say is that for dimensions

328
00:18:39,870 --> 00:18:45,870
of status, the variance, especially within a market, uh competitive market

329
00:18:46,030 --> 00:18:51,150
of uh who you're gonna choose as a partner, partner choice, um, variance is really

330
00:18:51,150 --> 00:18:51,470
important.

331
00:18:52,120 --> 00:18:52,920
Yeah, I think so.

332
00:18:53,000 --> 00:18:56,280
And to your point, right, if you then start thinking about different domains and where

333
00:18:56,280 --> 00:18:58,760
where that variance is, that's gonna impact it.

334
00:18:58,840 --> 00:19:03,080
And I think folks like Adar uh Eisenberg has some modeling work trying to show how that

335
00:19:03,080 --> 00:19:06,920
impacts the evolution of cooperation, having these different domains and how much they

336
00:19:06,920 --> 00:19:09,720
correlate across uh these different domains as well.

337
00:19:10,200 --> 00:19:10,440
Yeah.

338
00:19:10,680 --> 00:19:11,800
That's super interesting stuff.

339
00:19:11,960 --> 00:19:17,160
I mean, uh in some ways it suggests a more nuanced picture of how people are choosing

340
00:19:17,170 --> 00:19:18,290
cooperative partners.

341
00:19:18,450 --> 00:19:23,890
And they're not just saying, oh, uh, I I want the the kindest, most uh competent partners.

342
00:19:24,050 --> 00:19:28,690
It's I'm tracking the variation in these trait attributes.

343
00:19:28,850 --> 00:19:34,850
And I am strategically uh being choosy on the on the traits that vary in my local ecology.

344
00:19:35,010 --> 00:19:38,610
And the traits that don't vary as much, I'm going to be less choosy about those traits.

345
00:19:38,770 --> 00:19:44,530
And that suggests a uh a more sensitive uh uh mind that is uh really picking up on these

346
00:19:44,530 --> 00:19:47,240
cues of how variable different traits are.

347
00:19:47,560 --> 00:19:52,440
Um and and also in the in the aspects of the resources themselves, whether they can be

348
00:19:52,440 --> 00:19:56,360
stored or concealed, or whether they're conspicuous and out in the open.

349
00:19:57,160 --> 00:20:00,120
All of these factors that you know the mind is sensitive to.

350
00:20:00,280 --> 00:20:01,800
And I think that's really cool.

351
00:20:02,360 --> 00:20:08,280
I I want to go back to this uh finding you mentioned about differences in

352
00:20:08,650 --> 00:20:12,010
um cooperation in a public goods game.

353
00:20:12,330 --> 00:20:17,050
So you have different sorry, was it different camps that had different cooperation rates?

354
00:20:17,370 --> 00:20:17,610
Yeah.

355
00:20:17,770 --> 00:20:22,330
So uh we play the game within the the camp and they're making these decisions in private.

356
00:20:22,490 --> 00:20:22,810
But yeah.

357
00:20:23,130 --> 00:20:23,290
Right.

358
00:20:23,530 --> 00:20:28,410
And so basically they're deciding um whether to uh put a resource, and so in this case a

359
00:20:28,410 --> 00:20:33,210
honey stick, into the pot to be multiplied and distributed uh among the group.

360
00:20:33,370 --> 00:20:35,850
So it's basically acting for the good of the group.

361
00:20:36,170 --> 00:20:36,490
Right.

362
00:20:37,210 --> 00:20:42,760
Um and with this game, there is the classic free rider problem where everyone is better off

363
00:20:42,760 --> 00:20:46,920
if everyone else contributes to the pot, but I selfishly free ride off of everyone's

364
00:20:46,920 --> 00:20:47,160
effort.

365
00:20:47,240 --> 00:20:50,680
But if everyone thinks that way, then everyone free rides and there's no there's nothing in

366
00:20:50,680 --> 00:20:51,240
the pot.

367
00:20:51,400 --> 00:20:56,920
Um and so what you're seeing is in some camps, uh people are contributing uh a lot to the

368
00:20:56,920 --> 00:21:00,280
pot, and in some they're not contributing much of anything at all.

369
00:21:01,050 --> 00:21:06,810
And it seems like ecology can't really explain this because there's so much variation

370
00:21:06,810 --> 00:21:09,610
in the ecology from season to season, from year to year.

371
00:21:09,690 --> 00:21:13,850
Uh and people are, you know, it's a fission-fusion society, so people are, you know, ending

372
00:21:13,850 --> 00:21:17,210
up in constantly sort of wandering around to different places.

373
00:21:17,290 --> 00:21:21,130
So it seems like ecology is not really going to explain this difference.

374
00:21:21,370 --> 00:21:25,000
So do you have any thoughts about what is explaining this?

375
00:21:25,080 --> 00:21:29,000
I mean you mentioned norms, but I feel like that just begs the question of why do these

376
00:21:29,000 --> 00:21:29,960
norms differ.

377
00:21:30,520 --> 00:21:32,360
Yeah, it's a really good question.

378
00:21:32,520 --> 00:21:38,360
And, you know, we tried uh to rule out as much as we could things like ecology or had they

379
00:21:38,360 --> 00:21:38,680
just eaten.

380
00:21:38,920 --> 00:21:43,160
So I think in one year uh we had asked, you know, when was the last time someone brought in

381
00:21:43,160 --> 00:21:44,120
a kill or something?

382
00:21:44,200 --> 00:21:49,150
And uh we couldn't find anything that could explain um these differences in cooperation,

383
00:21:49,230 --> 00:21:55,230
how much like can you have, or um things like that didn't seem to really predict

384
00:21:55,230 --> 00:21:56,510
how much people were cooperating.

385
00:21:56,590 --> 00:22:01,630
It just uh the only reliable predictor was how much everyone else is giving.

386
00:22:02,030 --> 00:22:07,070
And so the the question rises, you know, I I think to your point, it's easy to invoke norms

387
00:22:07,070 --> 00:22:07,310
here.

388
00:22:07,550 --> 00:22:12,480
And so sort of what we kind of suspect happens is that someone moves in and I remember

389
00:22:12,480 --> 00:22:18,400
those classic uh there's a classic psychology study of the autokinetic effect, uh, where

390
00:22:18,400 --> 00:22:22,320
you that you shine a light in a dark uh room and it looks like it's moving.

391
00:22:22,400 --> 00:22:26,080
And so they have a group of people and they shine this light and they ask them, and someone

392
00:22:26,080 --> 00:22:30,080
says, Oh, it's two inches to the right, and everyone else in the group answers that.

393
00:22:30,160 --> 00:22:35,760
And then if you take each person out of that group one by one and add a new person in, even

394
00:22:35,760 --> 00:22:41,330
once there's an entirely new group, they s they're still answering the same uh uh biased

395
00:22:41,330 --> 00:22:43,010
answer that was originally answered, right?

396
00:22:43,250 --> 00:22:45,330
They're sort of adopting the norm as they come in.

397
00:22:45,490 --> 00:22:50,050
We think that's probably something that's happening here is that as they move into this

398
00:22:50,050 --> 00:22:55,010
camp and they see how much people are sort of uh willing to give uh in day-to-day life, how

399
00:22:55,090 --> 00:22:59,650
much you know, how hard is it to get them to actually share, that this is uh impacting sort

400
00:22:59,650 --> 00:23:04,290
of what they believe everyone else's behavior will be, um, and that this is carrying over

401
00:23:04,290 --> 00:23:05,010
to the game.

402
00:23:05,340 --> 00:23:07,740
That's the assumption we're looking for.

403
00:23:08,220 --> 00:23:11,340
We did try to measure those normative expectations.

404
00:23:11,500 --> 00:23:15,020
So we did try to ask people, this was with Christina Biggier.

405
00:23:15,180 --> 00:23:18,060
So we tried to ask, you know, what do you think everyone else in your camp will do?

406
00:23:18,460 --> 00:23:22,300
And what do you think everyone else in your camp thinks other people should do?

407
00:23:23,020 --> 00:23:25,500
But we couldn't we couldn't get the the method to work.

408
00:23:25,580 --> 00:23:29,900
It was it's too complex for they couldn't just wrap they couldn't wrap their head around

409
00:23:29,900 --> 00:23:30,620
the question.

410
00:23:30,860 --> 00:23:32,810
They couldn't wrap their head around their question the question.

411
00:23:32,890 --> 00:23:37,210
And even when you do those questions with like US undergrads, it can actually often be

412
00:23:37,210 --> 00:23:37,610
challenging.

413
00:23:37,690 --> 00:23:40,570
So that it's kind of a hard question to ask.

414
00:23:41,370 --> 00:23:46,650
So we'd expect norms, you'd expect there would be some sort of punishment to reinforce

415
00:23:46,650 --> 00:23:47,130
those norms.

416
00:23:47,210 --> 00:23:48,410
That's usually the model.

417
00:23:49,450 --> 00:23:55,130
There's very few examples in the ethnographic literature of any sort of physical punishment

418
00:23:55,130 --> 00:23:56,010
between the Hadza.

419
00:23:56,170 --> 00:23:57,450
You'll see scolding.

420
00:23:57,820 --> 00:24:03,180
And, you know, we often assume scolding has reputational costs that uh influence

421
00:24:03,180 --> 00:24:04,060
punishment.

422
00:24:04,780 --> 00:24:09,500
But, you know, my concern there is that there's such strong sharing norms, anyways, that

423
00:24:09,500 --> 00:24:15,020
even if, you know, there's one guy I was talking with who everyone knew he had murdered his

424
00:24:15,020 --> 00:24:18,220
wife, like this was common knowledge, no one disputed it.

425
00:24:18,380 --> 00:24:19,740
But people would still share with him.

426
00:24:19,820 --> 00:24:22,540
And they would say, like, that's that's what it is to be Hadza is.

427
00:24:22,620 --> 00:24:23,740
You share with other Hadza.

428
00:24:23,980 --> 00:24:29,830
And so it's not clear if those scoldings and the reputation actually, you know, translate

429
00:24:29,830 --> 00:24:31,030
into any real costs.

430
00:24:31,270 --> 00:24:35,830
So honestly it's a shoulder shrug at like what's actually maintaining this still.

431
00:24:35,910 --> 00:24:39,990
Uh again, the went in thinking it'd be partner choice and reputation.

432
00:24:40,310 --> 00:24:43,590
Um and now not so sure about that.

433
00:24:43,990 --> 00:24:44,310
Wow.

434
00:24:45,110 --> 00:24:49,750
I love that that anecdote of the guy who everyone knows that he murdered his wife and

435
00:24:49,750 --> 00:24:51,270
everyone knows that everyone knows that.

436
00:24:51,430 --> 00:24:56,220
And yet he's still a a member of the community in good standing who gets an equal share of

437
00:24:56,220 --> 00:24:58,220
the spoils or of the resources.

438
00:24:58,380 --> 00:25:04,220
Um that is a very alien idea to to to my Western mind, you know, where you know if someone

439
00:25:04,220 --> 00:25:06,140
murders their wife, they they get imprisoned for life.

440
00:25:06,300 --> 00:25:08,540
In some cases they'll get sentenced to death.

441
00:25:08,940 --> 00:25:12,860
And yet in this case they're still a member of the group in in good standing.

442
00:25:13,580 --> 00:25:19,210
Yeah, I I mean s we think that he was excluded from some camps uh

443
00:25:19,370 --> 00:25:19,930
initially.

444
00:25:20,090 --> 00:25:23,370
He was in uh a couple of years after that, he was in some smaller camps.

445
00:25:23,610 --> 00:25:26,250
Though that could also just be a personal choice of his.

446
00:25:26,330 --> 00:25:27,450
It's it's hard to tell.

447
00:25:27,610 --> 00:25:32,170
Um but by the time I was working with him in 2016 and then especially twenty nineteen, so

448
00:25:32,170 --> 00:25:35,530
that would been I I think it happened in twenty thirteen, so it was like five or six years

449
00:25:35,530 --> 00:25:36,090
later.

450
00:25:36,410 --> 00:25:40,650
The aunt of the woman he killed uh was in that camp and really disliked him.

451
00:25:40,730 --> 00:25:45,820
But everyone else was again, they would talk about it, but they were still willing to share

452
00:25:45,820 --> 00:25:50,460
with him and still also emphasized his good traits as well, that he was a good hunter, um,

453
00:25:50,540 --> 00:25:51,660
that he was a funny guy.

454
00:25:51,820 --> 00:25:57,820
So, you know, uh it it doesn't necessarily mean the stor what I take away

455
00:25:57,820 --> 00:26:01,820
from that story is that again, reputational costs, we have to be careful and actually see

456
00:26:01,820 --> 00:26:05,660
what what do those costs really translate to, because there's other mechanisms that could

457
00:26:05,660 --> 00:26:09,420
be interfering with how that translates into you know real costs for the actors.

458
00:26:09,740 --> 00:26:09,900
Yeah.

459
00:26:10,060 --> 00:26:13,550
What does it mean to not share in that community.

460
00:26:13,790 --> 00:26:14,990
Like, what are the consequences?

461
00:26:15,070 --> 00:26:16,430
If somebody doesn't share with me, do I die?

462
00:26:16,590 --> 00:26:18,030
Like, what what are the consequences?

463
00:26:18,190 --> 00:26:18,430
Yeah.

464
00:26:18,910 --> 00:26:21,230
If someone doesn't share with you or if you don't share with someone.

465
00:26:21,470 --> 00:26:23,870
So let's uh if if somebody doesn't share with me.

466
00:26:23,950 --> 00:26:27,870
So like if everybody decided for this guy we weren't gonna share with him, what would

467
00:26:27,870 --> 00:26:28,830
happen to him?

468
00:26:29,630 --> 00:26:32,110
Um that's a good question.

469
00:26:32,190 --> 00:26:35,920
I I I mean again, so the hunting success rates are really low for Hadza.

470
00:26:36,160 --> 00:26:40,640
So a single hunter will bring in a kill once a month, about um, and that's probably not

471
00:26:40,640 --> 00:26:41,760
enough calories.

472
00:26:41,920 --> 00:26:47,360
Um could probably get by on and this guy was a particularly good hunter, so maybe he would

473
00:26:47,360 --> 00:26:49,040
have been somewhat fine.

474
00:26:49,280 --> 00:26:54,160
I think eventually you would he would probably have to move from the bush to maybe one of

475
00:26:54,160 --> 00:26:54,880
the villages.

476
00:26:55,040 --> 00:26:58,630
But again, he might actually do better in that village ultimately, right?

477
00:26:58,710 --> 00:27:02,710
Like we're not even sure if banishment or excluding would necessarily be costly.

478
00:27:02,870 --> 00:27:06,390
Because another thing that would happen is that he would be expected to share less as well,

479
00:27:06,470 --> 00:27:06,710
right?

480
00:27:06,870 --> 00:27:11,190
So he might actually benefit from not having those obligations.

481
00:27:11,350 --> 00:27:17,350
So again, I I I m the thing I took away from this is that we want to be we don't want to

482
00:27:17,350 --> 00:27:22,740
assume reputation necessarily has a cost without actually Yeah.

483
00:27:22,900 --> 00:27:28,900
I mean what what I'm hearing you say, maybe one interpretation is the making a living

484
00:27:28,900 --> 00:27:34,900
in a particular ecology really sets up like costs and benefits that

485
00:27:34,900 --> 00:27:37,300
are have a lot of momentum.

486
00:27:37,380 --> 00:27:43,380
Um and like the variability between people, it's important, but you you know, you really

487
00:27:43,380 --> 00:27:49,070
have to understand the um the the way of making a living and if sharing is

488
00:27:49,070 --> 00:27:49,710
really important.

489
00:27:49,950 --> 00:27:52,990
I mean I mean it sounds like in this particular case, like yeah, the guy would probably

490
00:27:52,990 --> 00:27:54,030
have been fine or better.

491
00:27:54,190 --> 00:27:59,630
But like if it was like, you know, a mom whose partner died or a kid, you know, like they

492
00:27:59,630 --> 00:28:00,030
would probably die.

493
00:28:00,190 --> 00:28:00,670
You know, I don't know.

494
00:28:00,910 --> 00:28:06,190
Maybe I'm putting words in your mouth, but like yeah, it's it's it's the if thinking about

495
00:28:06,190 --> 00:28:10,030
all the phenotypes that would be affected by this blanket policy, it sounds like some of

496
00:28:10,030 --> 00:28:11,870
them it would be a really bad situation.

497
00:28:12,030 --> 00:28:12,350
Yeah.

498
00:28:12,820 --> 00:28:12,980
Yeah.

499
00:28:13,140 --> 00:28:14,740
I I think that's the the right way to put it.

500
00:28:14,820 --> 00:28:19,540
So we can think about like between populations, what's the variation in ecology,

501
00:28:19,700 --> 00:28:24,260
subsistence, and norms and institutions that fit that particular an environment.

502
00:28:24,660 --> 00:28:27,780
But then also to your point, variation within those populations, right?

503
00:28:27,860 --> 00:28:31,620
That some people are going to be more affected or less affected.

504
00:28:31,780 --> 00:28:33,940
Um and so tending to that variation.

505
00:28:34,020 --> 00:28:37,860
And and really that's what I've come to love about field work is understanding that

506
00:28:37,860 --> 00:28:38,420
variation.

507
00:28:38,580 --> 00:28:42,650
So, you know, I think the first time I started working with Hadza, I I I did emphasize,

508
00:28:42,730 --> 00:28:46,570
like, oh, sort of the ancestral relevance that you know they're hunter-gatherers.

509
00:28:46,810 --> 00:28:48,730
Now I've sort of moved away from that.

510
00:28:48,810 --> 00:28:53,290
And uh many anthropologists where I I think the emphasis instead is like this is one way

511
00:28:53,290 --> 00:28:54,010
humans have lived.

512
00:28:54,090 --> 00:28:58,250
There are other ways, and we need to understand that that full variation rather than

513
00:28:58,250 --> 00:29:02,810
necessarily assuming you know, hunter-gatherers are some sort of you know stand-in for

514
00:29:02,810 --> 00:29:04,170
ancestral hunter-gatherers.

515
00:29:04,410 --> 00:29:04,570
Right.

516
00:29:04,730 --> 00:29:04,970
Right.

517
00:29:05,210 --> 00:29:09,420
Yeah, no, I think that's an increasingly important insight that anthropologists have made

518
00:29:09,500 --> 00:29:14,700
that we're in some ways we are overstating the importance of the few remaining

519
00:29:14,700 --> 00:29:19,020
hunter-gatherer populations that still exist as a window into the ancestral past.

520
00:29:19,660 --> 00:29:24,140
In all likelihood, the ancestral past was extremely variable with extremely many different

521
00:29:24,140 --> 00:29:26,620
ways of making a living, many different ecologies.

522
00:29:27,500 --> 00:29:32,940
And it's it's important not to, you know, overgeneralize from a

523
00:29:32,940 --> 00:29:37,330
particular culture or a particular ecology to humanity in general.

524
00:29:37,410 --> 00:29:41,330
And to see this as one of many possible ways that humans can live.

525
00:29:41,810 --> 00:29:42,050
Yeah.

526
00:29:42,290 --> 00:29:42,450
Yeah.

527
00:29:42,530 --> 00:29:47,410
And I think one way to put it is it's just like you would treat an undergrad population,

528
00:29:47,570 --> 00:29:53,250
which is any outcome is a result of contingency in the

529
00:29:53,250 --> 00:29:53,970
phenotype.

530
00:29:54,130 --> 00:29:59,980
And so even for a hunter-gatherer community or sample, you don't want to

531
00:29:59,980 --> 00:30:03,100
say, well, then this is just the essence of humanity, right?

532
00:30:03,180 --> 00:30:09,020
Like this level of conflict or this level of extra pair uh copulations

533
00:30:09,100 --> 00:30:13,500
or anything, you know, like that's that's humanity, like that's essentializing, right?

534
00:30:13,580 --> 00:30:19,100
I think the point is any sample of any human behavior is the result of the evolved

535
00:30:19,100 --> 00:30:21,990
phenotype interacting with the local circumstances.

536
00:30:22,070 --> 00:30:27,190
And so you you have to think about like this: what's the design underlying this outcome,

537
00:30:27,350 --> 00:30:30,870
not just that this outcome is sort of the essence of human nature?

538
00:30:31,350 --> 00:30:32,790
Yeah, I I couldn't put it better.

539
00:30:32,870 --> 00:30:34,230
Uh I totally agree with that, right?

540
00:30:34,390 --> 00:30:37,270
Thinking again about how those mechanisms are interacting.

541
00:30:37,590 --> 00:30:41,670
We know, right, on the surface of it, you just look around and we know humans vary, right?

542
00:30:41,750 --> 00:30:46,020
We can look from different countries, even within countries, we see all this variation uh

543
00:30:46,100 --> 00:30:50,820
in human phenotype, which I always point out to my bioanthro students is amazing because

544
00:30:50,820 --> 00:30:55,140
when we compare genetic diversity, we're leaf less genetically diverse than all the other

545
00:30:55,140 --> 00:30:55,940
great apes, right?

546
00:30:56,500 --> 00:31:01,700
Um and so thinking about how do we build a human science that accounts for that variation

547
00:31:01,860 --> 00:31:06,290
and essentializing uh in any aspect is probably gonna be the wrong way, right?

548
00:31:06,370 --> 00:31:10,610
Instead of thinking about those interacting mechanisms between mind, culture, and ecology.

549
00:31:10,850 --> 00:31:15,490
Yeah, I love Brett Beheim had uh in his in our long format episode with him, had a great

550
00:31:15,490 --> 00:31:19,090
saying it was that um genes are smooth, culture's crunchy.

551
00:31:19,410 --> 00:31:21,330
Oh, like the variability, yeah, exactly.

552
00:31:21,650 --> 00:31:22,450
Yeah, exactly.

553
00:31:22,690 --> 00:31:27,650
It's like a nice slogan for exactly that point that we're genetically so similar, uh, but

554
00:31:27,650 --> 00:31:28,610
we're just so different.

555
00:31:28,770 --> 00:31:33,620
And you just you it an alien looking at us would be like, oh yeah, no, no, like the effect

556
00:31:33,620 --> 00:31:35,940
of culture is very big.

557
00:31:36,020 --> 00:31:40,820
Um, even very close by people are acting differently, as you're finding even in different

558
00:31:40,980 --> 00:31:43,860
uh um collectives, basically in the bush.

559
00:31:44,020 --> 00:31:44,260
You know.

560
00:31:44,660 --> 00:31:45,700
Yeah, exactly.

561
00:31:46,100 --> 00:31:51,620
So I'm I'm curious, have you witnessed any kind of social cost being

562
00:31:51,620 --> 00:31:56,260
inflicted on someone in in your field work, whether it's punishment or exclusion or

563
00:31:56,260 --> 00:32:02,130
ostracism or collective um I I I I know you know Richard

564
00:32:02,130 --> 00:32:06,050
Rangham has work arguing that you know occasionally people will gang up on someone and and

565
00:32:06,050 --> 00:32:09,250
kill them in you know a a small scale society.

566
00:32:09,410 --> 00:32:15,330
Um have you witnessed any kind of social costs being inflicted on anyone for any reason?

567
00:32:16,690 --> 00:32:18,690
Not with the Hadza really.

568
00:32:18,770 --> 00:32:23,250
Uh part of that is is how I was doing my field work with them, going you know, going to a

569
00:32:23,250 --> 00:32:26,930
bunch of different camps means you're not staying there for a long time and and getting

570
00:32:26,930 --> 00:32:28,440
into you know the meat of it.

571
00:32:28,600 --> 00:32:28,840
Yeah.

572
00:32:28,920 --> 00:32:32,360
You know, they have a guess they're gonna be on better behavior, right?

573
00:32:32,520 --> 00:32:38,200
Um I have in some of the villages, in the fishing villages, uh I've worked with where I I

574
00:32:38,200 --> 00:32:40,120
would spend more time in each village.

575
00:32:40,200 --> 00:32:44,040
And so you get more into like the thread of the the fabric of the community.

576
00:32:44,200 --> 00:32:49,000
And you know, you'll see things, uh I I think probably the biggest blow up I saw was a

577
00:32:49,350 --> 00:32:55,110
woman, really really a girl refusing to marry a particular older man.

578
00:32:55,350 --> 00:33:00,950
Um, and there was some conflict between uh, you know, the parents wanted her to marry him,

579
00:33:01,110 --> 00:33:06,950
she didn't want to, and so there was and this comes up in like uh Zach and Manveer

580
00:33:07,030 --> 00:33:10,310
and Leo have talked about like really don't see a lot of punishment, which you see is

581
00:33:10,310 --> 00:33:10,710
mediation.

582
00:33:10,790 --> 00:33:16,300
And so they got the imam involved, uh the village executive officer, and they weren't

583
00:33:16,300 --> 00:33:20,140
trying to punish the but they were trying to sort of negotiate, try to convince her, or you

584
00:33:20,140 --> 00:33:22,780
know, try try to smooth over the situation.

585
00:33:23,180 --> 00:33:28,780
Um I, you know, I suspect imposing social costs are costly, and so the

586
00:33:28,780 --> 00:33:33,580
mediation is probably easier and the the more desired outcome usually.

587
00:33:33,660 --> 00:33:39,660
So I think I I I haven't seen a lot of like just clear cut cases of here here's a social

588
00:33:39,660 --> 00:33:40,620
cost being imposed.

589
00:33:40,780 --> 00:33:43,900
But again, that that just might be how I'm doing my field work.

590
00:33:44,750 --> 00:33:45,150
Interesting.

591
00:33:45,310 --> 00:33:50,750
I mean, could it be that, you know, each member of the community is so valuable and they're

592
00:33:50,750 --> 00:33:52,030
so interdependent with each other?

593
00:33:52,110 --> 00:33:56,750
So such that, you know, excluding anyone really inflicts a huge cost on the rest of us.

594
00:33:56,910 --> 00:34:01,310
Because if we have like a 3% hunting return, having an extra hunter in the group who's a

595
00:34:01,310 --> 00:34:03,710
good hunter is like a huge benefit to all of us.

596
00:34:03,870 --> 00:34:06,510
And excluding that person is a huge cost to all of us.

597
00:34:06,670 --> 00:34:10,510
And so it may be that the you know each member is just so integral to the community and so

598
00:34:10,510 --> 00:34:15,720
interdependent that the costs of inflicting any kind of exclusion or punishment on a person

599
00:34:15,720 --> 00:34:19,800
that could put you know break up the community or break up a cooperative relationship, that

600
00:34:19,800 --> 00:34:23,320
that's just too too big of a cost to experience.

601
00:34:24,200 --> 00:34:26,280
Could that be part of what's going on?

602
00:34:26,600 --> 00:34:30,920
Yeah, I I think that's uh that's a perfectly reasonable thing to think about as as you

603
00:34:30,920 --> 00:34:33,560
mentioned and an idea that he he was a good hunter, right?

604
00:34:33,640 --> 00:34:36,600
So uh losing him could be particularly costly.

605
00:34:36,760 --> 00:34:39,480
And we talk about this in like partner choice models all the time, right?

606
00:34:39,560 --> 00:34:43,510
Like the value, your value that you're bringing to the table uh predicts like your

607
00:34:43,510 --> 00:34:45,030
willingness to leave relationships, right?

608
00:34:45,190 --> 00:34:49,990
So if uh it's less costly to end a relationship because there are other options available,

609
00:34:50,230 --> 00:34:54,470
because um, you know, you're a high-value partner and you'll have access to those options,

610
00:34:54,630 --> 00:34:56,870
then it's easier to cut that relationship off.

611
00:34:57,030 --> 00:35:01,510
But yeah, maybe if it's so small that there's not enough other folks, or this person's

612
00:35:01,510 --> 00:35:06,420
particularly valuable because he's a good hunter, then it's just it's even costlier to

613
00:35:06,420 --> 00:35:07,380
impose those costs.

614
00:35:07,460 --> 00:35:12,660
And so again, maybe you try to negotiate uh through other means ways for them to improve

615
00:35:12,660 --> 00:35:16,820
their behavior so you can still get the benefits that they're bringing to the group.

616
00:35:17,300 --> 00:35:17,700
Interesting.

617
00:35:17,860 --> 00:35:22,820
I mean it it suggests, you know, a possible explanation for the extreme differences we see

618
00:35:22,820 --> 00:35:26,180
between Western societies uh and the Hadza, for example.

619
00:35:26,340 --> 00:35:31,690
So in a Western society, we live in these huge, massive populations, and we have these huge

620
00:35:31,690 --> 00:35:36,570
social networks, so many people we could potentially form cooperative relationships with.

621
00:35:36,810 --> 00:35:42,010
And the cost of excluding someone from my social network to me is extremely low.

622
00:35:42,170 --> 00:35:44,250
I could easily replace them with someone else.

623
00:35:44,650 --> 00:35:50,170
There's a huge social marketplace and many different people for me for me to choose from.

624
00:35:50,490 --> 00:35:56,410
And it doesn't hurt me at all if I, you know, say goodbye to a friend or a colleague or

625
00:35:57,290 --> 00:35:58,090
whatever.

626
00:35:58,480 --> 00:36:04,240
So in that case, if someone say murders their wife, I could say fine, put them away in

627
00:36:04,240 --> 00:36:04,720
prison forever.

628
00:36:04,800 --> 00:36:05,360
What do I care?

629
00:36:05,440 --> 00:36:08,080
You know, like I'll I'll find someone else to cooperate with.

630
00:36:08,240 --> 00:36:11,520
But in the Hadza, that's gonna be a much costlier thing to do.

631
00:36:11,760 --> 00:36:15,280
And so do you buy this this kind of relational mobility, the size of the social

632
00:36:15,280 --> 00:36:19,200
marketplace, that this might be an important factor regulating to what extent different

633
00:36:19,200 --> 00:36:21,440
transgressions are punished?

634
00:36:22,430 --> 00:36:24,830
Yeah, I I I think it definitely matters.

635
00:36:24,990 --> 00:36:28,430
I think the story gets complicated if you look at so there's uh you mentioned relational

636
00:36:28,430 --> 00:36:29,070
mobility, right?

637
00:36:29,230 --> 00:36:33,950
So there's ecological psychologists who have sort of their different uh measurements have

638
00:36:33,950 --> 00:36:38,590
sort of uh calculated for each country sort of their relational mobility level.

639
00:36:38,990 --> 00:36:41,310
And there's some cross-cultural analyses.

640
00:36:41,390 --> 00:36:45,470
Um I but I think when you dig into that literature, there's some contradictions where

641
00:36:45,470 --> 00:36:51,440
sometimes having more relational mobility increases cooperation because you have

642
00:36:51,440 --> 00:36:55,680
to compete more because people can leave you, but other times it seems to decrease

643
00:36:55,680 --> 00:36:59,360
cooperation because uh uh there's less incentive to.

644
00:36:59,520 --> 00:37:02,720
And so I I'm a little skeptical of some of those analyses.

645
00:37:03,440 --> 00:37:08,560
And there's folks who have redone the analyses trying to you know control for uh distance

646
00:37:08,560 --> 00:37:13,280
and and other uh confounds, and you know these effects seem to be um

647
00:37:14,690 --> 00:37:17,490
It's sort of difficult to wrap your head around, I think.

648
00:37:17,570 --> 00:37:23,010
Um, but uh more generally the idea that like uh yeah, who's in your network, how large your

649
00:37:23,010 --> 00:37:26,770
network is, uh, I think matters also what other institutions you have.

650
00:37:26,930 --> 00:37:31,010
I mean, the reality is if I need help, I don't usually go to a friend, right?

651
00:37:31,090 --> 00:37:33,970
I might go to my bank, my credit card, insurance, right?

652
00:37:34,050 --> 00:37:39,410
We have all these other institutions that also reduce our interdependence in some ways.

653
00:37:39,570 --> 00:37:43,250
And so we can think about what impacts that might also have, though, on our, you know,

654
00:37:43,330 --> 00:37:48,800
friendship uh psychologies um you know having these other uh institutions to buffer

655
00:37:48,960 --> 00:37:49,360
risk.

656
00:37:49,760 --> 00:37:50,000
Right.

657
00:37:50,160 --> 00:37:53,360
It seems like everyone is very replaceable in in the Western world.

658
00:37:53,600 --> 00:37:58,000
Whereas in the in the in the Hadza, you know, basically everyone is irreplaceable.

659
00:37:58,160 --> 00:38:02,400
Um or maybe I'm I'm I'm oversimplifying there, but I that seems to be one difference that

660
00:38:02,400 --> 00:38:03,440
might might matter.

661
00:38:03,920 --> 00:38:06,230
Yeah, I I think that's that's that's a good way to put it.

662
00:38:06,390 --> 00:38:06,630
Yeah.

663
00:38:06,710 --> 00:38:09,270
The people are are more replaceable here.

664
00:38:09,350 --> 00:38:12,870
Um and so that's gonna impact how we cooperate with one another.

665
00:38:13,190 --> 00:38:16,550
Does that I mean just could we'll and we'll move on, but I'm just curious like per

666
00:38:16,710 --> 00:38:22,070
interpersonally or anecdotally, when you go to Hadza Land or you have that impression, and

667
00:38:22,070 --> 00:38:26,790
that's a big difference between your your here here meaning like where you are right now

668
00:38:26,950 --> 00:38:28,240
and when you're there.

669
00:38:28,400 --> 00:38:33,600
Uh, do you notice uh what effect that has um

670
00:38:34,240 --> 00:38:35,440
on life?

671
00:38:35,680 --> 00:38:40,160
That the replaceable I mean, obviously there's other there's many other confounding things,

672
00:38:40,240 --> 00:38:45,680
but I'm just curious like if you have some anecdotal impression of that difference or yeah,

673
00:38:45,760 --> 00:38:50,960
I I mean the the the other surface differences are so big that it would be hard.

674
00:38:51,040 --> 00:38:53,760
But I think David Lawson put this in a nice way.

675
00:38:54,160 --> 00:38:59,570
Um struggle new student new anthropology students sometimes have in the the first time

676
00:38:59,570 --> 00:39:02,850
they're in the field uh is that they don't do enough.

677
00:39:03,010 --> 00:39:06,210
So when you're in the field, you have to also be cooperating.

678
00:39:06,290 --> 00:39:11,250
So whether that's contributing by like cleaning dishes or whatever, and it be it becomes

679
00:39:11,250 --> 00:39:15,810
really clear how important it is to contribute in that situation.

680
00:39:16,050 --> 00:39:20,290
Um where even even, you know, if I'm paying research assistants where, you know, here in

681
00:39:20,290 --> 00:39:23,180
the US, if I'm paying you, you know, that means that's your job.

682
00:39:23,260 --> 00:39:25,020
I'm not supposed to to help.

683
00:39:25,180 --> 00:39:27,820
Um you know, if I did that, that that wouldn't work, right?

684
00:39:27,900 --> 00:39:29,820
That would that would start fraying relationships.

685
00:39:29,900 --> 00:39:32,540
Um and so you feel it doing the actual work.

686
00:39:32,620 --> 00:39:37,260
It's like, oh, I have to be a member of this community and I have to really make sure that

687
00:39:37,260 --> 00:39:39,500
I'm contributing, that I'm I'm not replaceable.

688
00:39:39,660 --> 00:39:45,180
So that's how that's how I would say I I'd feel uh that difference really um you know it's

689
00:39:45,260 --> 00:39:48,430
it's never I I don't want to paint a picture of like a utopia.

690
00:39:48,510 --> 00:39:51,150
I mean Hadza have a very hard life.

691
00:39:51,230 --> 00:39:53,790
Um, you know, there's lots of dangers.

692
00:39:53,950 --> 00:39:58,990
Um, so it it's not like again a social utopia and there's all sorts of conflicts still that

693
00:39:58,990 --> 00:40:03,150
pop up, but uh there's definitely a difference in how you approach those relationships.

694
00:40:04,430 --> 00:40:04,670
Yeah.

695
00:40:06,110 --> 00:40:06,430
Cool.

696
00:40:06,560 --> 00:40:06,880
Yeah.

697
00:40:06,960 --> 00:40:11,040
I wonder, well, yeah, that's another I'll I'll leave it at that.

698
00:40:11,120 --> 00:40:16,240
It's just it's curious, it's an interesting thing to uh because uh obviously there's like a

699
00:40:16,240 --> 00:40:21,520
lot of advertising or sort of cultural um uh history of sort of

700
00:40:22,240 --> 00:40:26,880
uh you don't have to do the manual labor because you're higher class, right?

701
00:40:27,040 --> 00:40:32,880
Um and I think I even even sort of from working class to like working to uh white

702
00:40:33,040 --> 00:40:35,770
collar, that's a there's a difference there as well.

703
00:40:35,930 --> 00:40:41,690
Um and there's even ethnographies um like of just social class that sound very similar even

704
00:40:41,690 --> 00:40:42,170
within the West.

705
00:40:42,410 --> 00:40:46,810
So it's just an interesting it's interesting to kind of think about that similarity even if

706
00:40:46,810 --> 00:40:48,010
you even within the West.

707
00:40:48,170 --> 00:40:48,410
Yeah.

708
00:40:48,730 --> 00:40:49,290
Yeah, yeah.

709
00:40:49,370 --> 00:40:49,850
I agree.

710
00:40:50,010 --> 00:40:50,650
Yeah.

711
00:40:51,210 --> 00:40:55,930
Um I wanna there's another thing that that stuck with me that you mentioned, which is that

712
00:40:55,930 --> 00:41:01,860
people's cooperation levels um aren't really stable and that I might

713
00:41:01,860 --> 00:41:03,940
cooperate in one context, but not another context.

714
00:41:04,020 --> 00:41:08,900
And there's not like enduring character traits that you might have otherwise expected.

715
00:41:09,540 --> 00:41:14,740
You know, in the Western world, we really care a lot about character and like whether

716
00:41:14,740 --> 00:41:16,020
someone is a good person or not.

717
00:41:16,180 --> 00:41:20,820
And we view that as kind of an essence that's internal to that person and endures over

718
00:41:20,820 --> 00:41:21,140
time.

719
00:41:21,860 --> 00:41:26,190
And and what you're what you seem to be finding among the Hadza is that that's not really

720
00:41:26,190 --> 00:41:30,030
the case, that there aren't these enduring differences in in cooperativeness.

721
00:41:30,270 --> 00:41:33,630
Is that is that an oversimplification or is there more to it than that?

722
00:41:34,190 --> 00:41:36,510
It it gets a little more complicated.

723
00:41:36,670 --> 00:41:40,270
So uh with a public good game, we find no correlation across time.

724
00:41:40,510 --> 00:41:43,870
We do find a a moderate one when we play like a dictator game.

725
00:41:43,950 --> 00:41:46,670
So in that game, we've discovered that later.

726
00:41:46,830 --> 00:41:49,950
Um so it it part depends on how you measure.

727
00:41:50,030 --> 00:41:53,120
I mean, these are one-shot games, so there's al always a question like, what are they

728
00:41:53,120 --> 00:41:53,920
really measuring?

729
00:41:54,080 --> 00:41:58,560
We've also asked, so like when we rank people on, ask people to rank each other on

730
00:41:58,560 --> 00:42:02,400
something like generosity, you can also look at the agreement between judges.

731
00:42:02,480 --> 00:42:07,440
And so this is a method from personality psychology that if you get more agreement between

732
00:42:07,440 --> 00:42:10,960
people, that means they're behaving consistently across situations.

733
00:42:11,120 --> 00:42:13,520
And so we get really low consensus as well.

734
00:42:13,680 --> 00:42:18,480
So that that at least sort of triangulates that we do think that um cooperation, at least

735
00:42:18,640 --> 00:42:20,720
how they perceive it, might not be very stable.

736
00:42:20,990 --> 00:42:25,710
And so I did run a study, because you can think about interesting questions that that might

737
00:42:25,710 --> 00:42:30,430
raise, that if you don't have this belief that character is essential, how that might

738
00:42:30,430 --> 00:42:30,990
impact things.

739
00:42:31,150 --> 00:42:33,230
I mean, maybe punishment doesn't make sense, right?

740
00:42:33,390 --> 00:42:37,310
If you think uh people behave relative to the situation.

741
00:42:37,390 --> 00:42:42,110
And maybe some of the things again, like what Man Vier and Leo are arguing about uh sort of

742
00:42:42,110 --> 00:42:48,100
third party compensation and and uh sort of uh uh right reconciliation rather

743
00:42:48,100 --> 00:42:48,900
than punishment.

744
00:42:49,380 --> 00:42:55,140
Um and so I did run a study uh wanted to follow this up, where we

745
00:42:55,140 --> 00:43:00,900
asked folks, we gave them a situation, so something like um someone has a

746
00:43:01,300 --> 00:43:05,060
uh pot of honey and they walk away because they had to go take care of something.

747
00:43:05,220 --> 00:43:09,630
And when they come back, their honey's gone, and it's either two people took the honey.

748
00:43:09,710 --> 00:43:14,910
It was someone who's never stolen before but is really hungry, or someone who has stolen

749
00:43:14,910 --> 00:43:16,430
before but is very satiated.

750
00:43:16,510 --> 00:43:21,310
And we also had uh a flip side of like someone dropped, you know, gave he was really

751
00:43:21,310 --> 00:43:24,190
hungry, someone gave him honey and was someone who shared before.

752
00:43:24,350 --> 00:43:26,590
Um, you know, so we we sort of crossed that.

753
00:43:26,750 --> 00:43:32,620
And what we found was that for positive traits, so things like sharing, helping out, people

754
00:43:32,620 --> 00:43:34,780
did seem to have essentialist beliefs.

755
00:43:34,860 --> 00:43:38,060
So if we asked them who did it, they would say it was the person who has previously been

756
00:43:38,060 --> 00:43:38,780
helpful.

757
00:43:39,100 --> 00:43:45,100
For the negative behaviors, uh, it flips where people were more willing to attribute it to

758
00:43:45,100 --> 00:43:45,660
the situation.

759
00:43:45,740 --> 00:43:49,820
They were more likely to say it was this person who hasn't stolen before but is very

760
00:43:49,820 --> 00:43:50,460
hungry.

761
00:43:50,620 --> 00:43:54,810
Um, so it's sort of interesting that it really depends on, you know, sort of the polarity

762
00:43:54,810 --> 00:43:56,250
that you're asking about.

763
00:43:56,410 --> 00:44:00,250
Um, and and always wanted to follow that up to see, you know, what are the downstream

764
00:44:00,250 --> 00:44:04,890
effects of that on sort of willingness to punish or or willing to, you know, reconciliate

765
00:44:04,890 --> 00:44:05,450
with folks.

766
00:44:05,770 --> 00:44:09,610
That's that's really cool because I mean because I'm doing the free will stuff right now,

767
00:44:09,770 --> 00:44:10,810
going through the literature.

768
00:44:10,890 --> 00:44:16,010
And in a Western uh context, um it's the it's the opposite, right?

769
00:44:16,250 --> 00:44:20,520
Where um if somebody does something negative, it's it's attributed to their personality.

770
00:44:20,600 --> 00:44:25,720
And I mean, I I would view all of this the the underlying consistency is it's all about

771
00:44:25,720 --> 00:44:28,200
intervention and the practicality of intervention, right?

772
00:44:28,280 --> 00:44:33,640
So, like if you can, as David said, everybody's replaceable, you can like sort of leverage

773
00:44:33,640 --> 00:44:36,440
costs to be like, David, you really should do that differently.

774
00:44:36,520 --> 00:44:42,190
I can't change the circumstances, but if you can't do that, um, or if the b better way to

775
00:44:42,190 --> 00:44:47,870
change the situation is the the kind of context in which they were in, um, then that would

776
00:44:47,870 --> 00:44:49,550
be the the other pattern.

777
00:44:50,110 --> 00:44:50,270
Right.

778
00:44:50,510 --> 00:44:50,590
Right.

779
00:44:50,830 --> 00:44:55,630
So I I thought about those classic like the fundamental attribution uh misattribution

780
00:44:55,630 --> 00:44:56,190
error, right?

781
00:44:56,270 --> 00:44:58,670
Or uh right, uh it's the flip.

782
00:44:58,750 --> 00:45:01,870
People are attribute uh bad behaviors to to the personality.

783
00:45:02,110 --> 00:45:06,270
I wonder if you could do something like a cross-cultural study with relational mobility

784
00:45:06,350 --> 00:45:12,020
where maybe you can see the strength of that ref effect or the whether it reverses based on

785
00:45:12,020 --> 00:45:14,900
how replaceable folks are using that relational mobility measure.

786
00:45:15,220 --> 00:45:16,660
Yeah, or just any cost benefit.

787
00:45:16,900 --> 00:45:20,660
I mean, it's a little bit hand wavy, but I mean I would think that the argument would be

788
00:45:20,660 --> 00:45:25,060
that there's in the ecology, there's sort of every agent is doing this cost benefit

789
00:45:25,060 --> 00:45:30,470
analysis of say, if somebody cheats, what are the costs and benefits of doing something

790
00:45:30,470 --> 00:45:35,910
about that by trying to recalibrate them and saying, You're a bad person, you should have

791
00:45:35,990 --> 00:45:41,990
you should do differently in the future, versus in this situation, this person did this.

792
00:45:42,150 --> 00:45:44,950
The thing that needs to change is the situation.

793
00:45:45,110 --> 00:45:49,670
Um, you know, like and I think yeah, I think that's even true for us too.

794
00:45:49,830 --> 00:45:52,950
Like there's just certain situations where you look at somebody and you're like, I'm not

795
00:45:52,950 --> 00:45:54,950
gonna be able to change that person's decision.

796
00:45:55,140 --> 00:45:58,900
we're gonna have to change the context versus we're gonna change the con, you know, so um,

797
00:45:59,060 --> 00:46:00,660
or I can change their their mind.

798
00:46:00,740 --> 00:46:05,940
And I think there's just costs and benefits uh cross-culturally, cross uh with the across

799
00:46:05,940 --> 00:46:07,060
people, like even in our lives.

800
00:46:07,140 --> 00:46:10,180
There's probably people you're like, Well, I'm not gonna change their mind, I'm gonna

801
00:46:10,180 --> 00:46:12,580
change the situation, you know, even for us.

802
00:46:12,660 --> 00:46:12,980
Yeah.

803
00:46:13,540 --> 00:46:13,700
Yeah.

804
00:46:14,100 --> 00:46:14,340
Yeah.

805
00:46:14,420 --> 00:46:16,660
I mean, it makes me think of some of the anger work, right?

806
00:46:16,740 --> 00:46:22,730
Uh, the idea that like the more uh the the higher expected WTR rate uh you

807
00:46:22,730 --> 00:46:26,410
have that you expect people to treat you better, you get angrier when you don't.

808
00:46:26,570 --> 00:46:30,330
I do wonder if that also means you'll get differences in like expressions of anger, right?

809
00:46:30,410 --> 00:46:35,370
If people have different methods to calibrate in different ecologies based on

810
00:46:35,370 --> 00:46:39,290
replaceability, then you might see differences in how anger is expressed towards these

811
00:46:39,290 --> 00:46:43,460
things as well, because you know, they're not going to recalibrate by imposing costs, but

812
00:46:43,460 --> 00:46:44,340
by doing something else.

813
00:46:44,420 --> 00:46:48,340
And so you might see differences even in how anger is expressed.

814
00:46:48,660 --> 00:46:51,300
But again, via these sort of universal mechanisms, right?

815
00:46:51,380 --> 00:46:54,260
That uh are just interacting with their local ecology.

816
00:46:54,580 --> 00:46:55,460
Yeah, that's super interesting.

817
00:46:55,700 --> 00:46:58,420
It's a great, yeah, it's a great example of the contingency point, right?

818
00:46:58,500 --> 00:46:58,820
Yeah.

819
00:46:59,220 --> 00:46:59,460
Right.

820
00:46:59,620 --> 00:47:00,980
I mean, uh, it's interesting.

821
00:47:01,060 --> 00:47:05,790
I I interpreted this um slightly differently, I mean this probably comes from my

822
00:47:05,790 --> 00:47:09,230
background, but um there's there's a lot of literature showing that people have

823
00:47:09,230 --> 00:47:13,470
attributional biases uh contingent on group membership or or alliances.

824
00:47:13,710 --> 00:47:18,750
So um if a fellow group member or ally uh does something bad, I'm going to attribute it to

825
00:47:18,750 --> 00:47:19,230
the situation.

826
00:47:19,310 --> 00:47:23,470
But if an outgroup or a rival does something bad, I'm going to attribute it to their

827
00:47:23,470 --> 00:47:24,430
personality, right?

828
00:47:24,510 --> 00:47:28,350
And you could see that as a kind of strategic bias where I want to, you know, mobilize

829
00:47:28,350 --> 00:47:31,310
opposition to my enemies and support for my allies.

830
00:47:31,470 --> 00:47:36,560
And it could be that in a tight knit community like the Hadza, everyone views uh every

831
00:47:36,560 --> 00:47:40,960
other member as a kind of, you know, crucial ally or at least highly interdependent.

832
00:47:41,040 --> 00:47:44,640
And that might cause these strategic biases to come into play where they're willing to

833
00:47:44,640 --> 00:47:47,840
discount or um uh minimize the transgression.

834
00:47:48,000 --> 00:47:51,280
At least that's that's where my mind went in in in hearing about this stuff.

835
00:47:51,520 --> 00:47:55,750
It would be interesting to see if they have similar attributional biases about, say, um a

836
00:47:55,830 --> 00:47:59,190
an outgroup or or a view that they've a group that they view negatively.

837
00:47:59,270 --> 00:48:03,430
I don't know if that exists on in in Hadza land, but it would be an interesting question to

838
00:48:03,430 --> 00:48:03,910
ask.

839
00:48:04,230 --> 00:48:07,030
Yeah, uh I I think that's a good point, right?

840
00:48:07,110 --> 00:48:09,910
And you can think of sort of the different mediating mechanisms here, right?

841
00:48:09,990 --> 00:48:14,070
So like first comes like group uh membership and identification and then you're making

842
00:48:14,150 --> 00:48:15,910
making your uh attributions that way.

843
00:48:15,990 --> 00:48:20,710
And and to your point, like I think all Hadza see all other Hadza as in group members, even

844
00:48:20,950 --> 00:48:21,830
if they're in different camps.

845
00:48:21,910 --> 00:48:26,400
These aren't really important social groupings, but maybe some of their neighboring

846
00:48:26,400 --> 00:48:28,320
populations, we could we could test that, right?

847
00:48:28,400 --> 00:48:32,960
And see if they're uh switching those biases, which would be super fascinating.

848
00:48:33,360 --> 00:48:35,120
Yeah, for sure.

849
00:48:35,440 --> 00:48:40,640
You also mentioned the WTR, the the this idea of the welfare trade-off ratio where the

850
00:48:40,640 --> 00:48:45,680
amount of costs I'm willing to inflict on you to get a benefit for myself is this this

851
00:48:45,680 --> 00:48:50,800
variable, and anger is a response to a low welfare trade-off ratio where you inflict a

852
00:48:50,800 --> 00:48:55,670
really big cost on me to get a really small benefit for you, like say I have a really fancy

853
00:48:55,670 --> 00:48:59,750
tie uh uh and you take my tie and you wipe the ketchup off your face with it.

854
00:48:59,910 --> 00:49:02,870
Like you're getting a really small benefit for yourself and you're ruining my tie.

855
00:49:02,950 --> 00:49:04,870
I would get really pissed off, right?

856
00:49:05,190 --> 00:49:10,470
Um at least that's my favorite example of of a of an anger-inducing situation.

857
00:49:10,710 --> 00:49:16,480
Um but i has anyone tried to measure uh welfare trade-off ratios

858
00:49:16,480 --> 00:49:21,120
in uh either either you know the Hadza or small scale society or any any place outside the

859
00:49:21,120 --> 00:49:21,600
Western world?

860
00:49:21,760 --> 00:49:25,600
Because I know this method has become increasingly common in evolutionary psychology of

861
00:49:25,600 --> 00:49:27,120
measuring these WTRs.

862
00:49:27,200 --> 00:49:30,800
Has anyone l tried to extend this to to different cultures and ecologies?

863
00:49:31,280 --> 00:49:37,230
I think Andy Delton has a paper with um I

864
00:49:37,230 --> 00:49:38,350
think it's among the Schwar.

865
00:49:38,670 --> 00:49:40,830
He's it's an anthropologist that works.

866
00:49:41,470 --> 00:49:44,590
It's in the 2020 uh weird special issue of EHB.

867
00:49:44,830 --> 00:49:47,230
Oh you I've also seen it.

868
00:49:47,310 --> 00:49:50,030
It's not, you know, it that uh task.

869
00:49:50,190 --> 00:49:53,790
So usually the the task used to measure welfare trade off ratio, right, is to ask like,

870
00:49:53,950 --> 00:49:58,430
would you rather have X amount of dollars yourself or Y amount of dollars for this other

871
00:49:58,430 --> 00:49:58,750
person?

872
00:49:58,910 --> 00:50:03,060
You know, that's also known as other things in the literature, so like social discounting.

873
00:50:03,140 --> 00:50:07,060
So, like Dan Harushka has done social discounting, I know, in Bangladesh.

874
00:50:07,300 --> 00:50:10,820
Um, and I remember he had challenges adapting that protocol.

875
00:50:10,980 --> 00:50:16,180
He has a couple of papers talking about that that challenge of adapting the protocol um and

876
00:50:16,180 --> 00:50:17,860
how people were understanding it.

877
00:50:17,940 --> 00:50:21,060
And I think he doesn't find the usual effect.

878
00:50:21,220 --> 00:50:25,060
So usually what you find is that people have the highest welfare trade-off ratios for

879
00:50:25,060 --> 00:50:26,790
people that they feel closest to.

880
00:50:27,030 --> 00:50:29,030
Um, I think he doesn't actually find that.

881
00:50:29,110 --> 00:50:32,790
I think need uh overrides the effect in those communities.

882
00:50:32,950 --> 00:50:34,950
So people are more willing to help those.

883
00:50:35,110 --> 00:50:39,830
And so again, I think the way to think about that is that the method, the measurement is

884
00:50:39,830 --> 00:50:41,590
interacting with the ecology as well.

885
00:50:41,830 --> 00:50:46,550
And has some of this too with some of the parochial altruism stuff, finding that in some

886
00:50:46,550 --> 00:50:52,360
communities, because there are the stereotypes of some uh communities being more or less

887
00:50:52,440 --> 00:50:58,440
uh high higher or lower SES or more need, that you'll get people sharing more cross-group

888
00:50:58,440 --> 00:51:01,960
boundaries, but really what's driving it is this perception of of need.

889
00:51:02,120 --> 00:51:06,920
Um so yeah, again, thinking that there's a lot of care that has to go into adapting these

890
00:51:06,920 --> 00:51:11,800
methods to make sure that they're understood the same way we think they're understanding

891
00:51:11,800 --> 00:51:12,120
it.

892
00:51:12,690 --> 00:51:13,170
Yeah.

893
00:51:13,410 --> 00:51:15,250
Why does why do things have to be so complicated?

894
00:51:17,490 --> 00:51:19,650
Well that that's what makes humans so interesting, right?

895
00:51:19,970 --> 00:51:20,370
I know.

896
00:51:20,690 --> 00:51:21,330
I know.

897
00:51:21,810 --> 00:51:23,330
Yeah, no, I mean it makes sense.

898
00:51:33,020 --> 00:51:36,940
pretty easy to think about, you know, I'm going to give up some money for my friend to get

899
00:51:36,940 --> 00:51:37,420
some money.

900
00:51:37,660 --> 00:51:41,900
Whereas if you're living at subsistence, you know, and you're talking about a critical

901
00:51:41,900 --> 00:51:45,340
resource, uh, the the game is is just totally different, right?

902
00:51:45,820 --> 00:51:49,820
Yeah, well I I think if there's there's even more to that even within so one of my first

903
00:51:49,820 --> 00:51:54,940
research research experiences was working with Dan Harushka on this social discounting task

904
00:51:55,020 --> 00:52:01,020
and he wanted to test it in community members uh in Phoenix and Tempe uh as sort of just

905
00:52:01,020 --> 00:52:01,890
to get a feel for it.

906
00:52:01,970 --> 00:52:06,770
So I'd go out to do these surveys where you give them these welfare trade-off ratio tasks.

907
00:52:06,850 --> 00:52:11,650
So they they rank who they feel like first, second, fifth, and tenth closest, I think,

908
00:52:11,730 --> 00:52:13,010
maybe went out further.

909
00:52:13,170 --> 00:52:16,290
They do this welfare trade-off ratio task.

910
00:52:16,930 --> 00:52:21,570
And I remember interviewing one woman who was pregnant and she had a young child with her

911
00:52:21,570 --> 00:52:22,130
as well.

912
00:52:22,450 --> 00:52:26,980
The person she felt closest to was her fetus, which makes total sense.

913
00:52:27,060 --> 00:52:30,340
She's like literally physically closest to this person.

914
00:52:30,740 --> 00:52:34,100
Um, and of course, she gives nothing to the fetus because that would be silly and

915
00:52:34,100 --> 00:52:35,620
ridiculous to do.

916
00:52:35,860 --> 00:52:40,340
Um, and so she doesn't have she didn't have this really clean social discounting line

917
00:52:40,500 --> 00:52:43,540
because uh, you know, she's considering other variables here.

918
00:52:43,700 --> 00:52:48,820
I remember one uh guy I interviewed, he ranked his cat as the twentieth closest person.

919
00:52:49,060 --> 00:52:50,870
Um it's very specific.

920
00:52:51,190 --> 00:52:54,790
Well, I I and and you know, I I thought about it and I was like, I'd probably put my pets

921
00:52:54,790 --> 00:52:57,110
around there too, maybe maybe even a little closer.

922
00:52:57,270 --> 00:53:00,470
And again, he gave nothing to his cat because that would be.

923
00:53:00,870 --> 00:53:02,390
Yeah, what's the cat gonna do with the money?

924
00:53:02,550 --> 00:53:02,710
Yeah.

925
00:53:02,950 --> 00:53:03,190
Yeah.

926
00:53:03,350 --> 00:53:05,910
Um opposable, no opposable thumbs.

927
00:53:06,630 --> 00:53:11,830
Uh uh, maybe you could operate the keyboard and order something off Amazon, but uh right,

928
00:53:11,900 --> 00:53:12,140
right.

929
00:53:12,300 --> 00:53:17,020
So even you don't have to go to another culture, even when we, you know, we're so used, I

930
00:53:17,020 --> 00:53:22,300
think, to interacting with undergraduates and participants online who in some ways are

931
00:53:22,300 --> 00:53:25,180
professional participants who are used to doing all these tasks.

932
00:53:25,340 --> 00:53:28,060
Um, that I think it impacts how they're interpreting that.

933
00:53:28,140 --> 00:53:33,260
And I again taking the time to see how are people understanding that task, even when you're

934
00:53:33,260 --> 00:53:36,780
working within your own cultures, I I think really key.

935
00:53:37,310 --> 00:53:37,550
Yeah.

936
00:53:37,630 --> 00:53:42,670
I mean, do you think it's uh has something to do with the level of abstraction and

937
00:53:42,670 --> 00:53:47,710
hypotheticality that we're accustomed to in in the Western world, where we have this

938
00:53:47,710 --> 00:53:52,190
education system that we're put through where we're we're forced to sort of decouple things

939
00:53:52,190 --> 00:53:57,230
from their concrete reality and think about, you know, abstractions and hypothetical

940
00:53:57,230 --> 00:54:01,480
arrangements of different things, And all of our questionnaires sort of rely on this to

941
00:54:01,560 --> 00:54:06,840
like entertain this hypothetical situation that may not ever happen in in real life and to

942
00:54:06,840 --> 00:54:11,720
sort of uh extrapolate, you know, what you would do in this hypothetical situation.

943
00:54:11,880 --> 00:54:15,560
And when you try to bring that into the Hadza land, they they're they're thinking about the

944
00:54:15,560 --> 00:54:17,960
concrete realities that they have to deal with.

945
00:54:18,120 --> 00:54:21,550
And you know if you ask them, you know, how much money are you going to give to your fetus?

946
00:54:21,630 --> 00:54:22,830
They're like, what are you talking about?

947
00:54:22,910 --> 00:54:24,910
Like my fetus, you can't spend any money.

948
00:54:25,150 --> 00:54:28,910
Like, whereas in the Western world, be like, oh yeah, in a hypothetical world, I would give

949
00:54:28,910 --> 00:54:29,790
the most to my fetus.

950
00:54:29,950 --> 00:54:34,030
But no, like they're thinking about you know their concrete realities and taking the the

951
00:54:34,030 --> 00:54:36,830
measures that you're giving them at face value and taking them literally.

952
00:54:36,990 --> 00:54:42,830
Um could that you know um explain potentially some of these difficulties

953
00:54:42,910 --> 00:54:47,390
and and just the the the level of comfort with these kind of abstract hypothetical

954
00:54:47,390 --> 00:54:48,030
questions?

955
00:54:48,640 --> 00:54:53,120
Yeah, or or putting numbers to fillings, which I think is actually really weird and we do

956
00:54:53,120 --> 00:54:54,080
it all the time.

957
00:54:54,320 --> 00:54:59,520
Uh yeah, I I think there are folks who are working on this problem of like how education is

958
00:54:59,520 --> 00:55:03,440
impacting cog obviously there are people working on that, but I think there's evolutionary

959
00:55:03,440 --> 00:55:06,800
anthropologists who are trying to think about like what what does this really mean?

960
00:55:06,960 --> 00:55:08,880
What what does the impact of schooling have?

961
00:55:09,120 --> 00:55:14,470
I'll say that it is so easy to know who has had some schooling in Hadza Land and who

962
00:55:14,630 --> 00:55:17,030
doesn't based on how they interact with the tasks.

963
00:55:17,190 --> 00:55:22,630
And some of it's not just abstraction, it's the very idea of sitting down to do a task that

964
00:55:22,630 --> 00:55:27,190
doesn't have any real impact uh you know in their lives.

965
00:55:27,510 --> 00:55:30,710
Um so I I definitely think that's that's part of it.

966
00:55:30,870 --> 00:55:35,110
Uh I've heard I've heard stories from so many folks uh in the field when they've tried to

967
00:55:35,110 --> 00:55:40,640
do tasks and they totally get an unexpected result because they they just understood it

968
00:55:40,640 --> 00:55:46,480
differently or they were thinking about a very specific context um from you know folks who

969
00:55:46,480 --> 00:55:48,640
are asked to give money to like friends.

970
00:55:48,880 --> 00:55:54,640
Uh and this was another interview at ASU where uh two people came in, they they and

971
00:55:54,640 --> 00:55:56,480
one person was completely selfish.

972
00:55:56,640 --> 00:56:00,960
But then immediately after, like we overheard him saying, like, Oh, I'm gonna pay for your

973
00:56:00,960 --> 00:56:01,360
lunch.

974
00:56:01,440 --> 00:56:03,280
Uh let's let's go grab lunch together.

975
00:56:03,520 --> 00:56:07,710
And it it's, you know, is I I think a lot of evolutionary psychologists are like, well,

976
00:56:07,790 --> 00:56:08,910
there's some status signaling, right?

977
00:56:08,990 --> 00:56:12,190
They want to be able to like control where those those resources are going.

978
00:56:12,350 --> 00:56:15,630
But also it does seem kind of generous, uh, on the other hand.

979
00:56:15,790 --> 00:56:17,390
So uh interesting.

980
00:56:17,630 --> 00:56:21,950
Yeah, again, I I just rather than giving the money to his friend directly, he took it for

981
00:56:21,950 --> 00:56:23,790
himself and then took his friend out to lunch.

982
00:56:24,110 --> 00:56:24,510
Exactly.

983
00:56:24,590 --> 00:56:24,830
Yeah.

984
00:56:25,150 --> 00:56:25,710
Interesting.

985
00:56:26,020 --> 00:56:29,780
Um which, you know, again, probably, you know, you get some control over what food you get,

986
00:56:29,860 --> 00:56:32,180
you get some of the reputation benefit you might not get.

987
00:56:32,340 --> 00:56:37,700
But um yeah, just that that people are are complicated, right?

988
00:56:37,780 --> 00:56:39,540
Uh as they think about these tasks.

989
00:56:39,700 --> 00:56:44,580
And um I I find it fun to hear these stories and think about how people are thinking about

990
00:56:44,580 --> 00:56:47,460
these different uh you know experiments that they're doing.

991
00:56:47,850 --> 00:56:48,810
Yeah, for sure.

992
00:56:48,970 --> 00:56:52,650
As if people, yeah, as if the the challenge of understanding complicated humans weren't

993
00:56:52,650 --> 00:56:53,290
challenging enough.

994
00:56:53,610 --> 00:56:57,130
We also have this problem of measurement and like how we measure the things that we're

995
00:56:57,130 --> 00:57:01,610
actually trying to measure, uh, particularly in a very different culture that isn't used to

996
00:57:01,610 --> 00:57:06,090
being uh to sitting down and doing a task that doesn't have any immediate practical

997
00:57:06,090 --> 00:57:06,650
benefit.

998
00:57:06,730 --> 00:57:08,010
Um it's it's a huge challenge.

999
00:57:08,090 --> 00:57:11,690
It's amazing that you know we've we've gotten stuff done at all and we've learned anything

1000
00:57:11,690 --> 00:57:11,930
at all.

1001
00:57:12,090 --> 00:57:15,770
Like it's uh it's a real credit to the to the work that you and others have have been

1002
00:57:15,770 --> 00:57:16,410
doing.

1003
00:57:17,260 --> 00:57:21,260
Yeah, and I think it's a benefit of taking an evolutionary approach and doing anthropology

1004
00:57:21,340 --> 00:57:21,580
too.

1005
00:57:21,660 --> 00:57:25,580
I mean, that's just to follow up on what David is saying is that I think there's a lot of

1006
00:57:25,580 --> 00:57:30,620
areas in psychology where the measure becomes the data, becomes the theory.

1007
00:57:31,020 --> 00:57:36,380
And so you just sort of you just say, like this number as a result of this method is the

1008
00:57:36,380 --> 00:57:37,420
psychology.

1009
00:57:37,570 --> 00:57:41,970
Um, and if you don't have an idea of, well, we're trying to figure out the evolved

1010
00:57:41,970 --> 00:57:45,730
psychology, or you don't have this idea of I'm gonna go to the field and see, you know, I

1011
00:57:45,730 --> 00:57:49,890
can't just assign this a number, like the kids gotta eat, the person's gotta live, they

1012
00:57:50,050 --> 00:57:50,610
gotta move.

1013
00:57:50,690 --> 00:57:53,650
Um, you know, like what are the what does the measure actually mean?

1014
00:57:53,730 --> 00:57:55,490
Um, it kind of keeps you honest.

1015
00:57:55,650 --> 00:58:01,090
Um and yeah, I think a lot of the history of psychology has been codifying

1016
00:58:01,090 --> 00:58:06,930
measures as uh as like real things as opposed to um, you

1017
00:58:06,980 --> 00:58:10,500
know, guesses or clues about the underlying psychology.

1018
00:58:10,580 --> 00:58:15,380
And it's really bad just to like just to just to like because a lot of times people will

1019
00:58:15,380 --> 00:58:16,420
will operationalize.

1020
00:58:16,580 --> 00:58:20,580
I operationalize a construct of like selfishness with like, do they cooperate in this like

1021
00:58:20,580 --> 00:58:21,540
prisoner's dilemma?

1022
00:58:21,700 --> 00:58:25,460
And then they'll report the studies like people are more selfish here than this, and then

1023
00:58:25,460 --> 00:58:29,780
that's what people pick up on, as opposed to no, it's that in this game among these

1024
00:58:29,780 --> 00:58:30,660
participants.

1025
00:58:30,900 --> 00:58:35,300
So, like, even just like the the the labels or the inference, it's like a game of

1026
00:58:35,300 --> 00:58:36,260
telephone.

1027
00:58:37,310 --> 00:58:37,550
Yeah.

1028
00:58:37,710 --> 00:58:38,590
Uh and to your point.

1029
00:58:38,670 --> 00:58:42,510
And right, we'll cite it later, like, oh, people cooperate X and then as you go through the

1030
00:58:42,510 --> 00:58:47,310
citations and then you go back and read it and you're like, oh, that this was not like and

1031
00:58:47,390 --> 00:58:51,470
maybe you don't even think it's a measurement of cooperation now where the theory's taken

1032
00:58:51,470 --> 00:58:51,630
us.

1033
00:58:51,870 --> 00:58:54,510
And and yeah, to your point, I I I think that's important.

1034
00:58:54,830 --> 00:59:00,510
Um I I'm less interested in theory development right now myself compared to where I was in

1035
00:59:00,510 --> 00:59:05,280
grad school, but it's still really important in thinking about this research, uh, because

1036
00:59:05,520 --> 00:59:08,000
you could also easily get lost in the field, right?

1037
00:59:08,080 --> 00:59:12,400
If you have all these different observations, still having a strong theoretical background,

1038
00:59:12,480 --> 00:59:13,760
especially in evolution.

1039
00:59:13,840 --> 00:59:18,800
I guess we're preaching to the choir here, um, is really important for helping to organize

1040
00:59:18,800 --> 00:59:19,120
that.

1041
00:59:19,280 --> 00:59:23,200
Um, you know, I still want to be open to discovery while I'm doing field work.

1042
00:59:23,280 --> 00:59:27,870
And, you know, I I've had have this chapter in the Oxford handbook where I make the case

1043
00:59:27,870 --> 00:59:33,070
that we don't want to have theory blind us and not just realize that there might be domains

1044
00:59:33,070 --> 00:59:36,830
of psychology that we're just not even thinking about because we're only thinking about

1045
00:59:36,830 --> 00:59:38,830
undergrads and and hunter-gatherers.

1046
00:59:39,070 --> 00:59:43,870
Um, but uh still keeping in mind that, you know, psychology is functional.

1047
00:59:44,030 --> 00:59:47,870
It has a very particular kind of function, and thinking about what that function is is is

1048
00:59:47,950 --> 00:59:51,310
still helpful for organizing all those different observations.

1049
00:59:51,640 --> 00:59:52,680
Yeah, I like that a lot.

1050
00:59:52,760 --> 00:59:57,320
I also would put it as like there's a difference between theory as tradition versus theory

1051
00:59:57,320 --> 01:00:01,560
as the ability to say, hey, hang on, we haven't looked at X or Y or Z.

1052
01:00:01,960 --> 01:00:05,880
And I think that those are very different uh kinds of theorizing.

1053
01:00:06,040 --> 01:00:11,560
And I think especially psychology has not done a good job of accepting

1054
01:00:11,560 --> 01:00:17,310
speculation or like people saying, look, we haven't accounted for X, Y, or Z because

1055
01:00:17,310 --> 01:00:18,590
there's no data for it, right?

1056
01:00:18,910 --> 01:00:19,070
Right.

1057
01:00:19,230 --> 01:00:20,590
There's no fancy data.

1058
01:00:21,150 --> 01:00:26,910
And so this is another one of my soapboxes, which is that if theory is the stuff

1059
01:00:26,910 --> 01:00:32,030
that has data and lots of evidence, then you're never going to actually look at the missing

1060
01:00:32,030 --> 01:00:32,430
pieces.

1061
01:00:32,510 --> 01:00:32,990
Yeah.

1062
01:00:33,390 --> 01:00:33,630
Yeah.

1063
01:00:33,710 --> 01:00:37,710
I I think there's formal modeling work in like philosophy of science trying to show like

1064
01:00:37,710 --> 01:00:40,700
it's it's um uh streetlight effect, right?

1065
01:00:40,780 --> 01:00:42,220
Like exactly your theory, your theory.

1066
01:00:42,620 --> 01:00:43,340
Yeah, that's great.

1067
01:00:43,420 --> 01:00:47,660
I actually knew after this episode, you have to like please send me that reference because

1068
01:00:47,820 --> 01:00:49,820
uh uh yeah, that would be great.

1069
01:00:50,060 --> 01:00:50,780
Yeah, of course.

1070
01:00:50,860 --> 01:00:51,100
Yeah.

1071
01:00:51,260 --> 01:00:55,340
Um it it's that old joke like uh the the drunk looking for their keys under the

1072
01:00:55,340 --> 01:00:55,980
streetlight, right?

1073
01:00:56,140 --> 01:01:01,650
So if theory focuses too quickly, then you're not uh open to sort of the

1074
01:01:01,650 --> 01:01:03,490
possibilities about other observations.

1075
01:01:03,890 --> 01:01:04,210
Exactly.

1076
01:01:04,370 --> 01:01:07,970
And so to your point, is like if you're in the field and you're like, look, our theories

1077
01:01:07,970 --> 01:01:09,570
are blinding us to this whole other thing.

1078
01:01:09,730 --> 01:01:14,130
I would argue like that's a kind of theory, but it's a very different kind of theory than

1079
01:01:14,130 --> 01:01:15,570
the theory that was blinding you.

1080
01:01:15,730 --> 01:01:15,810
Right.

1081
01:01:16,130 --> 01:01:16,290
Right.

1082
01:01:16,610 --> 01:01:17,890
Yeah, I think that's a good way to put it.

1083
01:01:18,290 --> 01:01:18,370
Right.

1084
01:01:18,610 --> 01:01:22,690
And uh the similar problem with, you know, we're only looking at the stuff that is easy to

1085
01:01:22,690 --> 01:01:27,180
measure or convenient to measure rather than the full range of stuff that we're interested

1086
01:01:27,180 --> 01:01:27,340
in.

1087
01:01:27,420 --> 01:01:29,900
You know, we're looking at the stuff that we can put a number on.

1088
01:01:30,060 --> 01:01:34,460
Um, but not everything of interest uh is that easily measurable.

1089
01:01:34,620 --> 01:01:39,820
And the stuff that we have, you know, well-tested measures for is not the full range of of

1090
01:01:39,820 --> 01:01:42,140
stuff that exists in the world.

1091
01:01:43,180 --> 01:01:46,780
So yeah, I think to that point, like I think just the value of just straight-up

1092
01:01:46,780 --> 01:01:51,750
ethnography, just people living in a community and just writing qualitatively about their

1093
01:01:51,750 --> 01:01:55,590
experiences and reporting on anecdotes like the anecdotes that you shared with us.

1094
01:01:55,750 --> 01:01:59,190
I think that is uh tremendously valuable and underrated, I think.

1095
01:01:59,670 --> 01:02:03,590
Yeah, it's it's definitely uh something I I'm trying to push in that chapter I mentioned

1096
01:02:03,670 --> 01:02:09,190
that we should ha be more open to uh ethnographic approaches in cross-cultural

1097
01:02:09,190 --> 01:02:11,990
psychology, especially cross-cultural evolutionary psychology.

1098
01:02:12,150 --> 01:02:15,740
And again, you don't want to fall into the trap of cultural anthropologists who will only

1099
01:02:15,740 --> 01:02:17,500
do thick description, right?

1100
01:02:17,580 --> 01:02:22,860
You still want to eventually move this to a frame, a generalizable theoretical framework.

1101
01:02:23,180 --> 01:02:27,900
But yeah, I mean, I've I've got a couple of projects in the pipeline right now that are

1102
01:02:28,140 --> 01:02:31,820
it's crazy for me to think about this that are just completely qualitative, that it was

1103
01:02:31,820 --> 01:02:33,420
interviews and focus groups.

1104
01:02:33,500 --> 01:02:37,820
Um, especially as someone who like has prided himself on some of my statistics.

1105
01:02:37,980 --> 01:02:41,500
Uh, it's really weird to be writing these papers where, because again, to your point, like

1106
01:02:41,580 --> 01:02:46,070
sometimes you can't get an accurate measurement, and sometimes the observation itself can

1107
01:02:46,070 --> 01:02:51,270
be a value and you know maybe we'll develop that measurement later maybe you know uh

1108
01:02:51,590 --> 01:02:56,230
whatever but uh at least having those observations out there uh in the first place can be

1109
01:02:56,230 --> 01:02:56,950
really helpful.

1110
01:02:57,270 --> 01:03:01,590
Yeah I feel like I've learned more from just the anecdotes that anthropologists have told

1111
01:03:01,590 --> 01:03:04,150
me about you know life in the field and with these people.

1112
01:03:04,310 --> 01:03:08,140
I've just learned more and and developed better intuitions about it than with any

1113
01:03:08,140 --> 01:03:09,100
particular data point.

1114
01:03:09,420 --> 01:03:13,260
Not to say the data isn't valuable, but I think it ought to be balanced with, you know,

1115
01:03:13,420 --> 01:03:15,100
real life experience as well.

1116
01:03:15,500 --> 01:03:15,740
Yeah.

1117
01:03:16,060 --> 01:03:19,660
Well, I've I've had the experience uh on the fisheries work.

1118
01:03:19,820 --> 01:03:25,740
I visited, I did, I think like 200 interviews down south in Tanzania

1119
01:03:25,820 --> 01:03:27,020
as like pilot work.

1120
01:03:27,180 --> 01:03:31,370
And then we did like 1400 surveys and another 200 interviews.

1121
01:03:31,850 --> 01:03:36,570
And what we were testing was whether or not having more friendships in villages that access

1122
01:03:36,570 --> 01:03:40,250
the same fisheries, if you're more likely to participate in fishery management.

1123
01:03:40,330 --> 01:03:45,610
The idea being that you create stake both in your friend and in the resource you share.

1124
01:03:45,770 --> 01:03:48,970
And so you're more willing to protect it was the basic idea.

1125
01:03:49,210 --> 01:03:54,580
And I remember we did all these interviews, and I wasn't surprised when the survey came

1126
01:03:54,580 --> 01:03:59,060
back supporting that view because it it came out in the interviews all the time.

1127
01:03:59,300 --> 01:04:02,660
Now, you know, the careful measurement means we we were able to compare different effect

1128
01:04:02,660 --> 01:04:03,060
sizes.

1129
01:04:03,220 --> 01:04:04,900
There's other things that are really important.

1130
01:04:05,140 --> 01:04:07,700
We got some specificity that it's not all friends.

1131
01:04:07,780 --> 01:04:10,260
It is specifically friends in these other communities.

1132
01:04:10,340 --> 01:04:11,860
Um there's benefit to that.

1133
01:04:11,940 --> 01:04:16,010
But even again, it was just weird that the the surveys felt like, oh, I have to do this to

1134
01:04:16,010 --> 01:04:20,410
prove it to other people, but the interviews I I was already uh fairly convinced it was was

1135
01:04:20,490 --> 01:04:22,730
gonna pop up and and that happens a lot.

1136
01:04:23,050 --> 01:04:23,290
Yeah.

1137
01:04:23,450 --> 01:04:24,890
No, that that's the best kind of work.

1138
01:04:24,970 --> 01:04:28,650
That's you know, you have you have the data for there who for for people who are, you know,

1139
01:04:28,890 --> 01:04:32,810
picky and skeptical, but you know, just it it's it's built on the foundation of actually

1140
01:04:32,810 --> 01:04:36,570
talking to people and and listening to their experiences and so that you know that it's the

1141
01:04:36,570 --> 01:04:41,580
data aren't, you spurious or a result of some bad measurement, like you actually have you

1142
01:04:41,580 --> 01:04:45,980
know a real connection to the people and understand what's going on at the ground level as

1143
01:04:45,980 --> 01:04:46,300
well.

1144
01:04:46,860 --> 01:04:48,220
So yeah.

1145
01:04:48,380 --> 01:04:52,860
I blame uh having to have deliverables to funding agencies.

1146
01:04:53,020 --> 01:04:55,820
We should say, I don't know what I'm gonna do.

1147
01:04:56,220 --> 01:05:01,660
Uh um and if I have an agenda, uh you should be suspicious of me.

1148
01:05:01,820 --> 01:05:02,460
Yeah.

1149
01:05:03,660 --> 01:05:07,850
Uh I I mean th this comes up a lot in training anthropology students.

1150
01:05:07,930 --> 01:05:12,410
Uh I I've had conversations with students who who feel that way who also want to do like

1151
01:05:12,410 --> 01:05:13,370
community engaged work.

1152
01:05:13,450 --> 01:05:17,530
And so in anthropology, there's a real push to like actually work with the community to

1153
01:05:17,530 --> 01:05:22,730
identify research questions that matter to them as well as your own research questions.

1154
01:05:22,890 --> 01:05:27,300
And so a lot of students are like, well, how do I go to the granting agencies without a

1155
01:05:27,300 --> 01:05:27,620
plan.

1156
01:05:28,020 --> 01:05:31,380
And it's the reality is you still do have a plan, right?

1157
01:05:31,700 --> 01:05:37,140
Uh um and so trying to train students that like the the plan has to be, you know,

1158
01:05:37,380 --> 01:05:40,820
morph and and and adjustable, but you need a plan going in.

1159
01:05:41,140 --> 01:05:45,940
Um if you you really can't just go out there into the community and just sit there and

1160
01:05:45,940 --> 01:05:46,340
learn.

1161
01:05:46,420 --> 01:05:48,330
Like the you need some direction.

1162
01:05:48,490 --> 01:05:53,210
But uh to your point though, I think uh outside of anthropology granting agencies, they

1163
01:05:53,210 --> 01:05:57,610
want a bit more specificity in like what hypotheses you're testing and things of that

1164
01:05:57,610 --> 01:05:58,170
nature.

1165
01:05:58,650 --> 01:05:59,290
Yes.

1166
01:06:01,130 --> 01:06:01,450
Cool.

1167
01:06:01,610 --> 01:06:06,730
Uh so there's um So the the wife murderer uh keeps keeps sticking in my head.

1168
01:06:07,530 --> 01:06:09,210
Maybe I'm just like obsessed with true crime.

1169
01:06:09,370 --> 01:06:11,690
I think the when we had the Brenda Bowser episode, I could start.

1170
01:06:12,010 --> 01:06:13,130
Oh, the death by Phantasm.

1171
01:06:13,690 --> 01:06:14,570
Yeah, that was great.

1172
01:06:14,860 --> 01:06:19,020
Any any story of of murder in in one of these communities always just sticks with me.

1173
01:06:19,180 --> 01:06:24,300
Um, but uh I I remember you mentioned, you know, work with um uh Leo Fatucci and Man

1174
01:06:24,460 --> 01:06:29,500
Versing on compensation and conflict mediation as an alternative to punishment.

1175
01:06:29,660 --> 01:06:33,180
And especially in a community where everyone is really interdependent and vital, it's much

1176
01:06:33,180 --> 01:06:38,060
more important to repair uh the the cooperation between the two disputants than it is to

1177
01:06:38,060 --> 01:06:42,140
punish or exclude one of the disputants because that, you know, uh excludes a really

1178
01:06:42,140 --> 01:06:43,020
valuable partner.

1179
01:06:43,190 --> 01:06:47,270
And so it's much more important to restore cooperation, mediate the conflict, bring people

1180
01:06:47,270 --> 01:06:51,270
together, uh, than it is to inflict costs, which is what we're so used to in the Western

1181
01:06:51,270 --> 01:06:55,270
world where we just send people off to prison or or whatever, so we don't have to deal with

1182
01:06:55,270 --> 01:06:55,510
them.

1183
01:06:55,750 --> 01:06:58,470
Um so back to the wife murderer.

1184
01:06:58,950 --> 01:07:04,790
Did did his did did the um did the per the wife who was murdered did was

1185
01:07:04,950 --> 01:07:07,110
there any compensation given to the family?

1186
01:07:07,270 --> 01:07:11,750
Um was there any kind of conflict mediation as a result of this, or do you not remember the

1187
01:07:11,750 --> 01:07:12,470
details?

1188
01:07:13,260 --> 01:07:14,780
I'm not aware of the details.

1189
01:07:14,860 --> 01:07:17,580
So I didn't ask too many questions about this.

1190
01:07:18,060 --> 01:07:20,780
I wasn't sure if it was appropriate or not.

1191
01:07:20,860 --> 01:07:23,900
And so a lot of this is hearing from other folks.

1192
01:07:26,540 --> 01:07:31,900
Like I said, the aunt of the mother of the woman who was murdered was very upset.

1193
01:07:32,060 --> 01:07:35,580
Like she in the interview was like, this guy's terrible.

1194
01:07:36,630 --> 01:07:39,350
The uncle actually did not have strong feelings.

1195
01:07:39,830 --> 01:07:42,070
Funny enough, was the aunt specifically.

1196
01:07:43,350 --> 01:07:46,150
And that was a genetic relationship with the aunt.

1197
01:07:47,030 --> 01:07:50,310
Yeah, I I'm not sure is the answer.

1198
01:07:50,630 --> 01:07:51,190
Yeah.

1199
01:07:51,510 --> 01:07:55,910
Because yeah, it's one might expect that, you know, perhaps the family was compensated in

1200
01:07:55,910 --> 01:08:00,150
some way and there was some kind of mediation thing that that resolved it, or I I don't

1201
01:08:00,150 --> 01:08:00,470
know.

1202
01:08:00,950 --> 01:08:04,950
I I haven't heard of that before, and I I think the challenge with the Hadza is that they

1203
01:08:04,950 --> 01:08:07,080
don't accumulate wealth really easily.

1204
01:08:07,400 --> 01:08:08,760
Again, that might be changing.

1205
01:08:09,080 --> 01:08:11,880
Um, but they don't accumulate a lot of wealth, so it would be hard.

1206
01:08:11,960 --> 01:08:17,960
I mean, so the classic example actually is from Polly Wiesner's work on Papu Nugini, where

1207
01:08:17,960 --> 01:08:23,000
they have these elaborate courts and they're giving like livestock uh to harm to victims

1208
01:08:23,000 --> 01:08:23,400
and stuff.

1209
01:08:23,560 --> 01:08:27,880
So I I think you would need at least some sort of sense of property or accumulation of

1210
01:08:27,880 --> 01:08:32,530
wealth that would work for compensation or or maybe forms of labor.

1211
01:08:32,610 --> 01:08:36,290
There's other right uh societies that do uh labor exchanges.

1212
01:08:36,370 --> 01:08:39,730
But with the Hodza, I I'm not sure what that would look like.

1213
01:08:40,130 --> 01:08:44,450
But I I I want to be careful here because uh someone else might have more experience that

1214
01:08:44,450 --> 01:08:46,690
and would be able to talk about that more.

1215
01:08:48,370 --> 01:08:48,930
For sure.

1216
01:08:49,090 --> 01:08:54,370
Yeah I guess it's just a perfect storm of of you know factors that would cause you know a

1217
01:08:54,370 --> 01:08:59,660
murderer to be continued, you know, to be a member of the community and that they can't

1218
01:08:59,660 --> 01:09:02,140
really compensate the victim's family.

1219
01:09:02,300 --> 01:09:05,340
Uh they're integral to the community and they can't really be excluded.

1220
01:09:05,420 --> 01:09:07,980
And so this is just what happens as a result.

1221
01:09:08,540 --> 01:09:11,980
Yeah, I I I I think that's the right way to put it, yeah.

1222
01:09:13,820 --> 01:09:14,380
Cool.

1223
01:09:14,620 --> 01:09:20,450
Um so we've been dwelling a lot on on the Hadza and and less so on the the fishing

1224
01:09:20,450 --> 01:09:23,970
communities and the work that you're doing with and uh Pizer.

1225
01:09:24,450 --> 01:09:30,210
Are there any uh interesting differences you've noted between your field work and the Hadza

1226
01:09:30,450 --> 01:09:33,010
versus your work in these fishing communities?

1227
01:09:33,170 --> 01:09:38,370
Um what what are you uh observing there that that is particularly exciting you or

1228
01:09:38,370 --> 01:09:39,250
interesting you?

1229
01:09:39,810 --> 01:09:45,500
Yeah, so uh like I said that the one interesting thing about this project to begin with is

1230
01:09:45,500 --> 01:09:46,860
that it's a bit more applied.

1231
01:09:46,940 --> 01:09:51,420
So one thing I wanted I've and been moving more in my work is thinking about like how can

1232
01:09:51,420 --> 01:09:57,100
we translate these theories to application or at least test them in ways that is adjacent

1233
01:09:57,180 --> 01:09:58,220
where maybe we could do something.

1234
01:09:58,380 --> 01:10:02,540
So part of this work is collaborating with an NGO that uh is helping fisheries management

1235
01:10:02,540 --> 01:10:03,180
in the area.

1236
01:10:03,420 --> 01:10:07,580
And like I said, so the the motivating question is that you have all these uh villages,

1237
01:10:07,740 --> 01:10:10,970
like if you imagine a bay, you'll have like four or five villages around it, and they're

1238
01:10:10,970 --> 01:10:13,850
all accessing the reef in the middle for the fisheries.

1239
01:10:14,090 --> 01:10:18,570
And so classically, you'll get these community based uh institutions.

1240
01:10:19,050 --> 01:10:23,690
This is from like Eleanor Ostrom's work, where the community works together to like create

1241
01:10:23,690 --> 01:10:24,890
rules and enforce them.

1242
01:10:25,050 --> 01:10:28,410
But the issue here, of course, is that it's four different villages, right?

1243
01:10:28,490 --> 01:10:30,650
These communities have to work together.

1244
01:10:30,810 --> 01:10:35,690
Um, and really it's uh a collective action problem where you need individuals in each

1245
01:10:35,690 --> 01:10:40,380
village who are willing to report legal fishing, help clean the beach, develop landing

1246
01:10:40,380 --> 01:10:41,580
sites, things like that.

1247
01:10:41,820 --> 01:10:46,620
And so we're interested in whether or not these relationships between these villages could

1248
01:10:46,620 --> 01:10:49,340
help drive participation in here.

1249
01:10:49,420 --> 01:10:53,260
And again, the idea here is that there's some involved stake here.

1250
01:10:53,340 --> 01:10:57,740
So one thing we find is that these what we're calling long-distance relationships between

1251
01:10:57,740 --> 01:11:01,580
villages are really important for accessing loans for like new boats.

1252
01:11:01,740 --> 01:11:05,590
And the only way you're going to get that loan back is if they're able to keep fishing,

1253
01:11:05,670 --> 01:11:05,830
right?

1254
01:11:05,990 --> 01:11:10,390
And so once you have this sort of stake in other people in other communities accessing the

1255
01:11:10,390 --> 01:11:14,550
fishery, this creates, you know, this is more benefit for you in participation.

1256
01:11:14,710 --> 01:11:17,270
So sort of classic cooperation problem, right?

1257
01:11:17,430 --> 01:11:22,550
Um, and so we find that long distance friends encourage participation in these fisheries

1258
01:11:22,550 --> 01:11:22,870
management.

1259
01:11:22,950 --> 01:11:23,990
We replicated that effect.

1260
01:11:24,070 --> 01:11:26,470
So we did this in 2022 and 2023.

1261
01:11:26,550 --> 01:11:27,590
Uh so that was really nice.

1262
01:11:27,670 --> 01:11:31,270
And again, we also replicated that it was specifically these long distance friends.

1263
01:11:31,350 --> 01:11:34,880
So it wasn't how many friends or family you have in your village with you and wasn't f uh

1264
01:11:34,960 --> 01:11:35,920
family in other villages.

1265
01:11:36,000 --> 01:11:38,320
So very specifically these long distance friends.

1266
01:11:38,560 --> 01:11:44,400
What we just we have a preprint out now where we find uh even interest in having more long

1267
01:11:44,480 --> 01:11:50,400
distance friends, independent of having these uh friendships realized, also predicts

1268
01:11:50,400 --> 01:11:51,120
participation.

1269
01:11:51,360 --> 01:11:55,680
So we created this measurement uh we're calling long distance orientation or LDO.

1270
01:11:55,840 --> 01:12:01,170
So basically asking people do you like hearing about uh people's lives in other villages.

1271
01:12:01,330 --> 01:12:03,330
Do you like visiting people in other villages?

1272
01:12:03,810 --> 01:12:05,490
And in the US, we tested this.

1273
01:12:05,650 --> 01:12:09,970
This is distinct from things like extroversion or openness to new experiences.

1274
01:12:10,130 --> 01:12:12,690
They correlate, but we can distinctly measure them.

1275
01:12:13,090 --> 01:12:18,210
And interestingly enough, uh LDO positively predicts having more long distance friends.

1276
01:12:18,370 --> 01:12:23,330
And once that's in the model, extroversion negatively predicts having more long distance

1277
01:12:23,330 --> 01:12:26,450
friends or predicts fewer long distance friends.

1278
01:12:26,530 --> 01:12:29,010
So there does seem to be some distinctiveness here.

1279
01:12:29,220 --> 01:12:34,900
And so we find in these fishing villages that people with higher LDO are more

1280
01:12:34,900 --> 01:12:37,140
willing to participate in these fisheries management.

1281
01:12:37,220 --> 01:12:41,060
And the idea here is that if you want to, if you're interested in building more

1282
01:12:41,060 --> 01:12:44,020
long-distance friends, you have to be a good cooperative partner yourself.

1283
01:12:44,100 --> 01:12:48,580
And so we think this is a partner choice mechanism where uh interest in long-distance

1284
01:12:48,580 --> 01:12:53,870
relationships is sort of upregulating cooperation in these long-distance settings and

1285
01:12:53,870 --> 01:12:54,510
situations.

1286
01:12:55,230 --> 01:12:59,550
So that pretty excited about that because it's a nice mix of some of my psychology

1287
01:12:59,710 --> 01:13:04,190
background and anthropology and really bring them together in an interesting way.

1288
01:13:04,750 --> 01:13:08,910
That's interesting, especially the when you add LDO and extroversion to the model,

1289
01:13:09,070 --> 01:13:10,350
extroversion predicts it negatively.

1290
01:13:10,430 --> 01:13:16,420
I mean, could it be that what's going on there is that extroversion is um predicting

1291
01:13:16,580 --> 01:13:20,740
sort of uh indiscriminate socializing to independent of the community.

1292
01:13:20,820 --> 01:13:25,220
And so you're gonna socialize more with the people in your in your group who are close and

1293
01:13:25,220 --> 01:13:30,820
also potentially um outsiders, whereas LDO is a disproportionate interest in outsiders

1294
01:13:30,820 --> 01:13:31,780
relative to insiders.

1295
01:13:31,940 --> 01:13:36,340
And so once you control for that, um extroversion is going to be predicting this uh

1296
01:13:36,420 --> 01:13:41,170
interest in uh insiders and that's going to negatively predict uh uh could something like

1297
01:13:41,170 --> 01:13:45,010
that be going on i i i feel like i should have more conversations with you about my

1298
01:13:45,010 --> 01:13:50,450
research because you you put it uh so well um but yeah i i think that's that's one way to

1299
01:13:50,450 --> 01:13:55,250
think about it um is that uh extroversion you want to hang out with people more generally

1300
01:13:55,410 --> 01:14:00,280
um and so that's probably gonna be people closer to you and LDO and I without it in the

1301
01:14:00,280 --> 01:14:04,680
model, I think uh extroversion like weekly positively predicts long distance friends.

1302
01:14:04,760 --> 01:14:07,400
Um, in the and this is only in the US sample.

1303
01:14:07,480 --> 01:14:12,280
We weren't able to adapt the big five uh to the Tanzanian setting.

1304
01:14:12,520 --> 01:14:17,480
Um the other thing it could be this going back to again measurement sort of reifying

1305
01:14:17,640 --> 01:14:18,200
theory.

1306
01:14:18,440 --> 01:14:24,250
If you look at the questions for extroversion, there are often things like I like to go to

1307
01:14:24,250 --> 01:14:29,690
parties uh with lots of friends, or I like to a lot of it's very close, uh

1308
01:14:29,850 --> 01:14:31,050
immediate socializing.

1309
01:14:31,130 --> 01:14:36,970
And so it could be the psychology that that's tapping might actually be more specific or or

1310
01:14:36,970 --> 01:14:42,890
less specific, but the way it's being asked, I think is in part sort of uh pushing it to

1311
01:14:42,890 --> 01:14:44,490
where it negatively predicts, right?

1312
01:14:44,570 --> 01:14:48,730
So in the US, like when we look at like some of the comments from the surveys, a lot of

1313
01:14:48,730 --> 01:14:51,620
people are talking about meeting long distance friends like online and stuff.

1314
01:14:51,700 --> 01:14:55,540
And so you're probably probably also picking up a difference there where, you know, people

1315
01:14:55,540 --> 01:15:00,660
who are a bit more introverted are more willing to in interact online and are picking up

1316
01:15:00,660 --> 01:15:01,540
long distance friends.

1317
01:15:01,700 --> 01:15:05,620
But the more interesting one is the one you said where like maybe there's a real difference

1318
01:15:05,620 --> 01:15:09,860
in that psychology, but can't rule out, you know, it's something about the the measurement

1319
01:15:09,860 --> 01:15:11,300
itself in this case.

1320
01:15:12,190 --> 01:15:13,070
That's cool.

1321
01:15:13,390 --> 01:15:19,390
Um I'm asking you to speculate here, but um, do you think this is a

1322
01:15:19,390 --> 01:15:24,670
kind of personality trait where like some people are just inherently more interested in

1323
01:15:24,670 --> 01:15:27,870
socializing with distant community members and some people aren't?

1324
01:15:28,110 --> 01:15:32,830
Or is is there a different story at play, like where maybe people who are more anxious

1325
01:15:32,830 --> 01:15:37,340
about resource shortfalls really are more motivated to form these long distance connections

1326
01:15:37,420 --> 01:15:40,540
to buffer themselves against risk and that is what's driving it.

1327
01:15:40,620 --> 01:15:45,260
So what what do you think is is going on here with this this variation in interest and and

1328
01:15:45,420 --> 01:15:46,780
long distance ties?

1329
01:15:47,980 --> 01:15:53,100
We Ann and I went back and forth on whether we call this a personality trait, an internal

1330
01:15:53,100 --> 01:15:57,340
regulatory variable, um, or you know, something else.

1331
01:15:57,740 --> 01:16:01,180
I'm I'm less interested in that sort of taxonomy to be honest.

1332
01:16:01,420 --> 01:16:03,340
What I this is speculation.

1333
01:16:03,500 --> 01:16:08,930
What we think it's probably a fairly consistent trait, but one that can

1334
01:16:09,170 --> 01:16:11,650
move as you adjust situations.

1335
01:16:11,810 --> 01:16:16,290
So, you know, one thing that will probably impact this is like cost and convenience of long

1336
01:16:16,370 --> 01:16:17,330
distance traveling.

1337
01:16:17,570 --> 01:16:19,730
So uh, you know, I live in Pullman.

1338
01:16:19,890 --> 01:16:21,970
This is eight miles from the town of Moscow.

1339
01:16:22,130 --> 01:16:23,410
There's no bus between the two.

1340
01:16:23,490 --> 01:16:27,820
So if you only have a bike in Pullman, then Moscow feels like a really long distance.

1341
01:16:27,980 --> 01:16:29,900
That's a trip you have to plan for.

1342
01:16:30,060 --> 01:16:34,540
But once you buy a car, then maybe you know your idea of distance now changes, right?

1343
01:16:34,620 --> 01:16:37,980
And so this would be related to like some of the psychological distance literature where

1344
01:16:37,980 --> 01:16:41,900
you find that, you know, people's perceptions of like time and space are all sort of

1345
01:16:41,900 --> 01:16:42,780
wrapped together.

1346
01:16:43,020 --> 01:16:44,780
And so we kind of suspected some of that.

1347
01:16:44,860 --> 01:16:50,070
So as the costs and benefits of uh traveling, of maintaining these relationships, as you

1348
01:16:50,070 --> 01:16:54,630
said, like if there's more need for risk buffering, um, then that could help.

1349
01:16:54,790 --> 01:17:00,150
So again, in our society, we usually rely on financial institutions for a lot of our risk

1350
01:17:00,150 --> 01:17:00,790
buffering, right?

1351
01:17:00,870 --> 01:17:05,990
More so, I think, than uh friends, especially people here in uh a higher uh

1352
01:17:06,230 --> 01:17:06,950
SES.

1353
01:17:07,430 --> 01:17:11,510
Uh, but in Tanzania, right, they are relying on their friends a lot for help.

1354
01:17:11,590 --> 01:17:17,110
And so one interesting thing is that they used to, before phone scams became a problem,

1355
01:17:17,660 --> 01:17:22,860
favorite activity would be uh calling like their number neighbors and like uh interacting

1356
01:17:22,860 --> 01:17:26,460
with someone far away and maintaining relationships.

1357
01:17:26,540 --> 01:17:32,220
And it could be that because they don't have these other risk-buffering institutions, um,

1358
01:17:32,460 --> 01:17:37,020
that they're more interested in uh relationships in general and maybe long distance

1359
01:17:37,020 --> 01:17:41,820
relationships in particular to help with those sort of community-wide uh shocks.

1360
01:17:44,790 --> 01:17:45,430
Yeah.

1361
01:17:45,830 --> 01:17:49,830
Um so so I again I think I think it's another great way to put my research.

1362
01:17:51,350 --> 01:17:51,750
Cool.

1363
01:17:51,990 --> 01:17:53,350
I mean fascinating stuff.

1364
01:17:53,510 --> 01:17:58,150
Um so I mean we're uh approaching you know an hour and a half now, and I want to make sure

1365
01:17:58,150 --> 01:18:02,470
that we've covered the topics that that you are personally most excited about.

1366
01:18:02,550 --> 01:18:06,550
Is there anything that we haven't covered that you're particularly interested in?

1367
01:18:06,710 --> 01:18:10,870
Uh uh new new directions, new ideas that that are stewing in you?

1368
01:18:11,380 --> 01:18:11,380
own.

1369
01:18:12,020 --> 01:18:15,700
Early enough on tenure track, I should have a lot of uh new ideas, right?

1370
01:18:16,020 --> 01:18:21,860
Uh one project I didn't talk about that I'm thinking about how to follow up on.

1371
01:18:22,020 --> 01:18:25,540
It was uh one of the casualties of some of the grant cancellations.

1372
01:18:25,700 --> 01:18:31,300
Uh, but this was my uh work in collaboration with some of the uh epidemiologists in our vet

1373
01:18:31,540 --> 01:18:32,180
med school here.

1374
01:18:32,340 --> 01:18:36,020
So we're interested in uh climate sensitive diseases, right?

1375
01:18:36,100 --> 01:18:40,830
So diseases, um, especially vector-borne diseases, so those that are carried by mosquitoes,

1376
01:18:41,070 --> 01:18:46,270
ticks, sandflies, et cetera, as the climate changes, right, their ecology changes.

1377
01:18:46,350 --> 01:18:48,270
And so their range and behavior will change.

1378
01:18:48,350 --> 01:18:53,390
And so there's a lot of diseases that have been identified that as climate's changing, the

1379
01:18:53,390 --> 01:18:55,630
epidemiology of these diseases are expected to change.

1380
01:18:55,790 --> 01:18:57,790
So we're looking here at Rift Valley Fever.

1381
01:18:57,870 --> 01:19:03,390
It's a hemorrhagic fever that primarily impacts livestock, but can uh jump over to

1382
01:19:03,390 --> 01:19:08,990
humans either by directly interacting with uh blood from the uh animal or from mosquito

1383
01:19:09,240 --> 01:19:09,720
bites.

1384
01:19:09,880 --> 01:19:14,840
And so historically, what you used to find is that you'd get Rift Valley Fever epidemics in

1385
01:19:14,840 --> 01:19:19,160
this area in northern Kenya with the El Nino southern oscillation.

1386
01:19:19,240 --> 01:19:24,520
There would be massive rainstorms that would flood these dry lands that would then

1387
01:19:25,160 --> 01:19:29,880
create breeding grounds for mosquitoes, and they you'd get epidemics following the uh the

1388
01:19:29,880 --> 01:19:30,840
mosquito storms.

1389
01:19:31,270 --> 01:19:36,150
What we found is that as the precipitation is changing, so you can actually track

1390
01:19:36,150 --> 01:19:39,750
precipitation change over several decades and temperature change.

1391
01:19:39,910 --> 01:19:43,110
What we're finding in the area is you're getting more extreme flooding.

1392
01:19:43,190 --> 01:19:46,710
So you get more rain on average, but fewer rainy days.

1393
01:19:46,790 --> 01:19:48,790
So it's coming more extreme.

1394
01:19:49,030 --> 01:19:53,030
And so what we're finding now is that there's more outbreaks happening between the

1395
01:19:53,030 --> 01:19:55,670
southern, between the El Nino southern oscillation.

1396
01:19:55,830 --> 01:19:59,700
And so we were interested in well, how are people adapting to these changes, right?

1397
01:19:59,780 --> 01:20:03,540
So what climate change adaptations are people developing in these communities?

1398
01:20:04,340 --> 01:20:05,780
And this was an interesting project.

1399
01:20:05,860 --> 01:20:08,180
So what we found was that they're really not.

1400
01:20:08,580 --> 01:20:12,580
What's happening is that they have so many different threats posed by climate change.

1401
01:20:12,660 --> 01:20:17,460
So they have to deal with, you know, decreased precipitation and increased droughts.

1402
01:20:17,620 --> 01:20:22,100
They have to deal with more conflict with these other communities in response to that

1403
01:20:22,100 --> 01:20:22,660
drought.

1404
01:20:22,820 --> 01:20:28,570
That, you know, what they used to do to avoid their animals getting sick would be to move

1405
01:20:28,570 --> 01:20:30,810
away from the floods where the mosquitoes were.

1406
01:20:30,970 --> 01:20:34,970
But now they're sort of more sedentary, they're settling around these permanent boreholes,

1407
01:20:35,050 --> 01:20:36,650
they can't move to new regions.

1408
01:20:36,810 --> 01:20:41,930
And so what we're finding is that these different threats posed by climate change are

1409
01:20:41,930 --> 01:20:44,170
really impacting people's to adapt to it.

1410
01:20:44,330 --> 01:20:50,260
And so what I'm hoping to follow up with this is really look at how people are sort of

1411
01:20:50,260 --> 01:20:54,900
uh representing and conceptualizing this sort of threat landscape of climate change and how

1412
01:20:54,900 --> 01:20:56,420
how are they able to respond to it?

1413
01:20:56,500 --> 01:21:02,420
Like, can they see past the near future of say uh a drought and look into the

1414
01:21:02,420 --> 01:21:06,180
long term about like, okay, how can we actually adapt to these different challenges?

1415
01:21:06,340 --> 01:21:09,700
Um, and so I'm really excited about following up on that work.

1416
01:21:09,940 --> 01:21:15,860
Um, again, in part because it really has some real-world implications for the folks we're

1417
01:21:15,860 --> 01:21:18,820
working with, and um, you know, that excites me quite a bit.

1418
01:21:20,370 --> 01:21:21,170
That's fascinating.

1419
01:21:21,250 --> 01:21:25,970
Well, what what things are you are you looking to measure with with regard to people's

1420
01:21:25,970 --> 01:21:30,850
ability to adapt to a changing climate and potentially a changing pathogen environment?

1421
01:21:31,250 --> 01:21:34,770
What are some of the variables that you're that you're interested in in looking at?

1422
01:21:35,330 --> 01:21:38,370
So we try to measure perceived climate change.

1423
01:21:38,450 --> 01:21:41,250
So we'd ask people how much you think climate's changing.

1424
01:21:41,410 --> 01:21:43,410
And it turns out this is a really hard question to ask.

1425
01:21:43,570 --> 01:21:47,810
Other people have reported having challenges where people have a hard time seeing past

1426
01:21:47,810 --> 01:21:48,930
seasonal variability.

1427
01:21:49,180 --> 01:21:52,220
And the other thing that's happening is that, you know, there's a ton of NGOs that are

1428
01:21:52,220 --> 01:21:53,100
working in this area.

1429
01:21:53,180 --> 01:21:55,420
And so they'll come and talk to them about climate change.

1430
01:21:55,500 --> 01:22:00,300
And so even when we translate it, we have to be careful if we use the same language the

1431
01:22:00,300 --> 01:22:03,980
NGOs use, then it sort of triggers like, oh, I know I'm supposed to talk about how

1432
01:22:03,980 --> 01:22:04,780
difficult this is.

1433
01:22:05,020 --> 01:22:09,820
So we're trying to measure like um, you know, and and part of this still goes back to long

1434
01:22:09,900 --> 01:22:13,180
distance relationships and sort of buffering against these community wide shocks.

1435
01:22:13,350 --> 01:22:13,590
right?

1436
01:22:13,670 --> 01:22:18,230
So if you think the climate's changing, maybe you'll make more intergroup relationships,

1437
01:22:18,310 --> 01:22:19,110
for example.

1438
01:22:19,350 --> 01:22:23,510
Um, so we're trying to measure uh originally sort of different aspects of climate

1439
01:22:23,510 --> 01:22:24,150
variability.

1440
01:22:24,390 --> 01:22:30,230
So um if you look, you can uh in actual weather data, you can break out different kinds

1441
01:22:30,230 --> 01:22:33,670
of variation, trying to see if people psychologically match that.

1442
01:22:34,020 --> 01:22:37,780
Our first go-around didn't seem to work well, so we'll have to get around it.

1443
01:22:37,940 --> 01:22:41,300
But also sort of mapping out like these different kinds of threats.

1444
01:22:41,460 --> 01:22:47,460
So do they see uh these changes in climate associated with changes in predators and

1445
01:22:47,460 --> 01:22:52,900
changes in conflict and changes in pathogens, and see do they have a couple model in their

1446
01:22:52,900 --> 01:22:57,890
head of this connection between climate change and you know you would think that'd be sort

1447
01:22:57,890 --> 01:23:01,490
of the necessary first step in thinking about how they would adapt to these, right?

1448
01:23:01,570 --> 01:23:03,730
Is how do they actually map out these threats?

1449
01:23:03,890 --> 01:23:08,290
Um something I'm I'm thinking about about how how can we measure this um in these

1450
01:23:08,290 --> 01:23:08,850
communities.

1451
01:23:09,810 --> 01:23:13,810
So the first step is just seeing if they're aware that the stuff is going on and aware of

1452
01:23:13,810 --> 01:23:15,890
the different ecological changes.

1453
01:23:16,050 --> 01:23:20,130
And then once you have that nailed down you could potentially see if awareness of these

1454
01:23:20,130 --> 01:23:25,820
ecological changes is affecting other variables like uh perhaps um cooperation with um

1455
01:23:25,820 --> 01:23:29,580
long-distance uh people in other in other communities.

1456
01:23:30,220 --> 01:23:31,100
Yeah, exactly.

1457
01:23:31,260 --> 01:23:36,140
And like you said, this was we had a grant from a subgrant through these centers for

1458
01:23:36,140 --> 01:23:37,900
research in emerging infectious disease.

1459
01:23:38,060 --> 01:23:43,820
This was a uh IH NIAD-funded um uh network of research

1460
01:23:43,820 --> 01:23:44,460
centers.

1461
01:23:44,700 --> 01:23:50,110
It was canceled in part um with a lot of the other cancellations,

1462
01:23:50,590 --> 01:23:53,070
and so wasn't able to follow up on that yet.

1463
01:23:53,150 --> 01:23:56,910
So still thinking about how I'll get back out there and follow up.

1464
01:23:57,230 --> 01:24:01,310
And you know, this is the reality of doing maybe not even just field work, but science in

1465
01:24:01,310 --> 01:24:01,710
general, right?

1466
01:24:01,790 --> 01:24:06,590
Is that very often we uh outside circumstances push us in one direction or another.

1467
01:24:06,750 --> 01:24:12,600
But um you know to the to the extent that I the will to research what I want, um, would

1468
01:24:12,760 --> 01:24:13,880
would love to follow up on this.

1469
01:24:13,960 --> 01:24:14,280
Yeah.

1470
01:24:14,520 --> 01:24:14,760
Yeah.

1471
01:24:14,920 --> 01:24:18,920
When we were in Morocco, you told me that the mosquitoes there we wouldn't need to worry

1472
01:24:18,920 --> 01:24:19,160
about.

1473
01:24:19,240 --> 01:24:25,080
You were saying you were you have expertise in mosquito uh taxonomizing for for good

1474
01:24:25,080 --> 01:24:25,720
reason.

1475
01:24:26,120 --> 01:24:27,000
Yeah, yeah.

1476
01:24:27,160 --> 01:24:31,350
Um and I remember when we got the grant proposal uh feedback.

1477
01:24:31,510 --> 01:24:34,470
That was the only feedback we got was that someone was really upset we didn't talk more

1478
01:24:34,470 --> 01:24:35,110
about mosquitoes.

1479
01:24:35,190 --> 01:24:36,230
And I thought, oh, that's silly.

1480
01:24:36,390 --> 01:24:41,110
And then actually reading up on the different uh genus of mosquitoes and what they spread.

1481
01:24:41,190 --> 01:24:42,710
And so, like Riff Valley fever.

1482
01:24:42,950 --> 01:24:47,350
So most uh diseases they're going to be spread by one specific genus or another.

1483
01:24:47,510 --> 01:24:50,630
Um, and you you can tell there are pretty visible differences.

1484
01:24:50,710 --> 01:24:53,990
Uh Riff Alley fever spread by just about everything, really.

1485
01:24:54,070 --> 01:24:59,860
We found uh all three genus of mosquitoes that spread it, um ticks have been known to

1486
01:24:59,860 --> 01:25:04,260
spread it, sand flies, and so it's been kind of crazy diving into this virus literature and

1487
01:25:04,340 --> 01:25:09,620
like realizing how scary it can be when you have a disease like this that can spread

1488
01:25:09,620 --> 01:25:11,620
through all these different kinds of vectors.

1489
01:25:11,860 --> 01:25:12,260
Yeah.

1490
01:25:13,780 --> 01:25:15,060
Which oh good.

1491
01:25:15,700 --> 01:25:20,850
Yeah, no, I I was just curious, um in terms of how these communities are conceptualizing

1492
01:25:20,850 --> 01:25:21,330
these changes.

1493
01:25:21,410 --> 01:25:25,490
Cause, you know, we obviously think about it in terms of meteorological changes in the germ

1494
01:25:25,490 --> 01:25:29,970
theory of disease, but they might not be exposed to those ideas or or are they?

1495
01:25:30,050 --> 01:25:30,290
I don't know.

1496
01:25:30,370 --> 01:25:33,090
I mean, do they have a different way of conceptualizing these changes?

1497
01:25:33,730 --> 01:25:37,090
They do have some exposure to the germ theory of disease.

1498
01:25:37,250 --> 01:25:41,970
Um, and it it varied between uh a couple of different villages we visited, how much they

1499
01:25:41,970 --> 01:25:43,090
bought into it.

1500
01:25:43,330 --> 01:25:45,970
Uh one community was very insistent.

1501
01:25:46,120 --> 01:25:50,840
This is like uh a response to us abandoning our traditional ways.

1502
01:25:51,000 --> 01:25:53,480
Like it was very much not germ theory of disease.

1503
01:25:53,800 --> 01:25:54,040
Interesting.

1504
01:25:54,840 --> 01:25:59,000
Sort of being punished by a supernatural agent for true in the US too.

1505
01:25:59,080 --> 01:25:59,240
Yeah.

1506
01:25:59,480 --> 01:25:59,640
Yeah.

1507
01:25:59,720 --> 01:25:59,880
Yeah.

1508
01:26:00,200 --> 01:26:02,040
I mean we we certainly get some of that as well as well.

1509
01:26:02,760 --> 01:26:04,440
That's like exactly true here.

1510
01:26:04,520 --> 01:26:04,840
Yeah.

1511
01:26:05,080 --> 01:26:05,240
Yeah.

1512
01:26:05,480 --> 01:26:05,880
Yeah.

1513
01:26:06,040 --> 01:26:08,120
Um but it to your point, right?

1514
01:26:08,200 --> 01:26:12,280
It matters how they think what's causing this because if you did want to design an

1515
01:26:12,280 --> 01:26:16,010
intervention, you know it's it's going to impact how they they buy into it.

1516
01:26:16,090 --> 01:26:19,610
If, you know, now they they interact with a lot of like vet techs.

1517
01:26:19,850 --> 01:26:23,690
The govern Kenyan government does do vaccine um campaigns.

1518
01:26:23,770 --> 01:26:29,530
So they have some exposure and for some diseases, they like like malaria, you know,

1519
01:26:29,610 --> 01:26:33,450
they they don't know the details, but they're pretty certain that's spread by mosquitoes

1520
01:26:33,530 --> 01:26:36,170
and that they're they buy that there's some sort of parasite.

1521
01:26:36,730 --> 01:26:38,490
So it depends on the specifics.

1522
01:26:38,570 --> 01:26:44,520
For Rift Valley fever, um that one they tended to buy more into the germ theory of

1523
01:26:44,520 --> 01:26:47,160
disease for a lot of those explanations.

1524
01:26:47,400 --> 01:26:49,160
Um yeah.

1525
01:26:49,800 --> 01:26:50,200
Cool.

1526
01:26:50,440 --> 01:26:56,040
Do they have any awareness of um industry being behind climate change or uh

1527
01:26:56,920 --> 01:26:59,800
is that has that not gotten around?

1528
01:27:00,440 --> 01:27:03,640
They tend to blame local changes.

1529
01:27:03,800 --> 01:27:09,130
Um so they would talk about their own tree cutting, and and it's hard to tell, you know, do

1530
01:27:09,130 --> 01:27:13,690
they think this is having a larger impact on the climate versus like you can see the effect

1531
01:27:13,690 --> 01:27:17,530
of cutting trees meant there's massive dust storms because there's nothing catching the

1532
01:27:17,530 --> 01:27:17,850
dust.

1533
01:27:17,930 --> 01:27:19,690
And so people would complain about that that.

1534
01:27:20,170 --> 01:27:25,930
Um you know, and and this is sort of a challenge of doing sort of more applied work in

1535
01:27:25,930 --> 01:27:31,290
these settings, is that the reality is that they're gonna be the most impacted by climate

1536
01:27:31,290 --> 01:27:33,370
change, but have done the least to contribute.

1537
01:27:33,770 --> 01:27:39,280
But you do get like NGO scolds who'll be like, well, you need to, you know, sequester more

1538
01:27:39,280 --> 01:27:41,040
carbon or however they would put it.

1539
01:27:41,200 --> 01:27:44,320
And it's like these guys did not cause the problem.

1540
01:27:44,480 --> 01:27:49,360
Like, you know, um, so it's trying to balance that that line.

1541
01:27:49,680 --> 01:27:50,320
Yeah.

1542
01:27:51,840 --> 01:27:53,120
Fascinating.

1543
01:27:54,160 --> 01:27:54,800
All right.

1544
01:27:55,520 --> 01:28:00,000
Well, um I think you know, we we would done an hour and a half.

1545
01:28:00,080 --> 01:28:01,920
I think that's pretty good.

1546
01:28:02,080 --> 01:28:02,480
Yeah, Chris.

1547
01:28:02,800 --> 01:28:04,400
This is a really fun conversation.

1548
01:28:04,480 --> 01:28:06,720
Thanks for uh chatting with us, Chris.

1549
01:28:07,090 --> 01:28:08,050
Yeah, appreciate it.

1550
01:28:08,210 --> 01:28:11,730
Really uh enjoyed talking, especially about things like methods and and measurements and

1551
01:28:11,810 --> 01:28:13,970
you know, how can we do that better cross-culturally?

1552
01:28:14,050 --> 01:28:15,570
Uh this was a really fun conversation.

1553
01:28:15,730 --> 01:28:15,970
Yeah.

1554
01:28:16,290 --> 01:28:22,130
I hope that you uh get all your funding back and uh and that you uh how do you avoid

1555
01:28:22,130 --> 01:28:23,810
mosquitoes in the field?

1556
01:28:24,290 --> 01:28:25,570
Uh not well.

1557
01:28:25,730 --> 01:28:31,660
Uh uh you know, uh repellent uh if you

1558
01:28:31,660 --> 01:28:32,860
can get a mosquito net.

1559
01:28:33,100 --> 01:28:35,660
Um, but like I was staying at one guest house.

1560
01:28:35,820 --> 01:28:39,020
The mosquito net was clearly not treated, bunch of holes.

1561
01:28:39,180 --> 01:28:43,660
I woke up the next morning with literally dozens of mosquitoes in my net, and you know, I

1562
01:28:43,660 --> 01:28:48,140
was killing them, and it's just like splotches of my blood, and I'm you know, very upset

1563
01:28:48,140 --> 01:28:48,460
about it.

1564
01:28:49,020 --> 01:28:54,220
Um It was it's a mosquito net that just keeps your mosquitoes with you, is really the way

1565
01:28:54,220 --> 01:28:54,540
it works.

1566
01:28:55,020 --> 01:28:56,460
That that's what ended up happening.

1567
01:28:56,540 --> 01:28:56,860
Yeah.

1568
01:28:57,020 --> 01:29:02,850
So um fortunately I haven't gotten anything fun or exciting in

1569
01:29:02,850 --> 01:29:03,890
terms of diseases.

1570
01:29:03,970 --> 01:29:05,410
Uh so hopefully that will continue.

1571
01:29:05,490 --> 01:29:11,170
But yeah, thank you for your service,

1572
01:29:11,330 --> 01:29:11,650
Chris.

1573
01:29:11,970 --> 01:29:13,890
Yes, thank you for your service and and Godspeed.

1574
01:29:14,050 --> 01:29:17,250
Hope I hope you don't get any fun and interesting diseases.

1575
01:29:18,130 --> 01:29:18,930
Yeah, thank you so much.

1576
01:29:19,330 --> 01:29:21,250
Your diseases stay very very boring.

1577
01:29:22,280 --> 01:29:23,320
As as do we all.

1578
01:29:23,400 --> 01:29:25,160
Uh yeah, thank you so much.

1579
01:29:29,800 --> 01:29:32,120
David, you are still here.

1580
01:29:32,680 --> 01:29:35,720
I'm still here, and you the listener are still listening.

1581
01:29:36,280 --> 01:29:37,400
You might not be.

1582
01:29:37,560 --> 01:29:39,320
Uh but you're not hearing us.

1583
01:29:39,560 --> 01:29:45,410
Although at the very least, our yeah, I mean it could be is that someone left their phone

1584
01:29:45,490 --> 01:29:48,610
and when and they're not actually listening, but it's just it kept playing.

1585
01:29:48,850 --> 01:29:52,130
Well, somebody uh might have listened and then stopped listening.

1586
01:29:52,210 --> 01:29:54,050
So in that never mind, it's okay.

1587
01:29:54,210 --> 01:29:56,850
Or they could just be spacing out, you think?

1588
01:29:57,410 --> 01:30:01,490
Well, I was thinking about somebody who listens to the episode but then stops at the outro

1589
01:30:01,650 --> 01:30:06,370
because they know that what's gonna happen in the outro is not is missable, is missable,

1590
01:30:06,450 --> 01:30:06,690
yeah.

1591
01:30:06,940 --> 01:30:07,260
Yeah.

1592
01:30:07,500 --> 01:30:08,620
And so are they a listener?

1593
01:30:08,700 --> 01:30:10,300
They're not listening, but it doesn't matter.

1594
01:30:10,380 --> 01:30:11,900
It's really, really yeah.

1595
01:30:11,980 --> 01:30:14,540
I I I I might cut this out myself.

1596
01:30:15,580 --> 01:30:17,740
Anyway, uh, you're here, David.

1597
01:30:17,820 --> 01:30:19,340
The listener is here.

1598
01:30:19,660 --> 01:30:20,300
Uh yeah.

1599
01:30:20,620 --> 01:30:24,860
We could give our song and dance routine of supporting us, Patreon, social media, leave us

1600
01:30:24,860 --> 01:30:30,140
a kind review, but we usually we've been doing kind of banter in in the outros instead,

1601
01:30:30,380 --> 01:30:30,700
right?

1602
01:30:31,100 --> 01:30:32,380
Uh I think so.

1603
01:30:32,910 --> 01:30:34,030
Do you have any banter?

1604
01:30:34,670 --> 01:30:35,550
I think I just did it.

1605
01:30:35,630 --> 01:30:36,430
That's all I have at the end.

1606
01:30:36,590 --> 01:30:36,990
You just did it?

1607
01:30:37,070 --> 01:30:37,870
That was the banter?

1608
01:30:38,030 --> 01:30:38,190
Yeah.

1609
01:30:38,430 --> 01:30:42,270
I'm st honest, I'm still not a hundred percent from HBus.

1610
01:30:44,190 --> 01:30:44,990
Yeah, I know.

1611
01:30:45,070 --> 01:30:48,270
You're still cup recovering from the sickness, whatever it is.

1612
01:30:50,910 --> 01:30:53,390
So David, thank you for carrying this episode today.

1613
01:30:54,220 --> 01:30:55,660
Yeah, no, absolutely.

1614
01:30:55,820 --> 01:30:57,580
Um, sickness is a is a real thing.

1615
01:30:57,740 --> 01:30:58,860
Lastitude's a real thing.

1616
01:30:59,020 --> 01:31:00,380
Uh stay tuned for for Josh.

1617
01:31:01,340 --> 01:31:02,140
Oh, there you go, David.

1618
01:31:02,220 --> 01:31:02,540
There you go.

1619
01:31:02,620 --> 01:31:03,900
That's why they pay you the big bucks.

1620
01:31:04,060 --> 01:31:09,660
I'm drinking coffee to just sort of perk myself up, but that was a great segue into Josh

1621
01:31:09,660 --> 01:31:12,380
Schnodgrass is going to be our upcoming guest.

1622
01:31:12,540 --> 01:31:17,900
So this is a um a teaser for Josh Schnodgrass about the

1623
01:31:18,860 --> 01:31:24,510
the emotion of of being sick and how it depletes you and it even depletes your

1624
01:31:24,510 --> 01:31:27,550
banter ability apparently.

1625
01:31:27,870 --> 01:31:28,270
Yes.

1626
01:31:28,910 --> 01:31:31,390
I think that and that was one of the first previews we've done.

1627
01:31:31,470 --> 01:31:33,150
So but um yeah.

1628
01:31:33,710 --> 01:31:34,030
Yeah.

1629
01:31:34,190 --> 01:31:36,830
Should we do a trailer for the next one at the end?

1630
01:31:37,390 --> 01:31:39,870
Uh I can do I can do my trailer voice.

1631
01:31:40,110 --> 01:31:41,230
I want to hear your trailer voice.

1632
01:31:41,550 --> 01:31:41,950
No words.

1633
01:31:42,110 --> 01:31:42,510
Please do it.

1634
01:31:45,300 --> 01:31:51,140
One man dares to ask the questions to

1635
01:31:51,140 --> 01:31:51,860
a scholar.

1636
01:31:52,260 --> 01:31:53,860
Well uh is that pretty good?

1637
01:31:54,260 --> 01:31:55,140
That's really good.

1638
01:31:55,300 --> 01:31:57,700
Um is it Will Arnett?

1639
01:31:57,780 --> 01:32:01,380
Is that who's uh the guy who does a lot of um he's not rust rust?

1640
01:32:01,940 --> 01:32:04,740
No, it's not Will Arnett, although he has a verse.

1641
01:32:05,140 --> 01:32:05,860
No, Will Arnett.

1642
01:32:06,020 --> 01:32:08,020
No, but Will Arnett does uh voiceovers.

1643
01:32:08,420 --> 01:32:12,660
He does, but he doesn't think he does like Oh, he doesn't do when in a world though, yeah.

1644
01:32:12,740 --> 01:32:13,140
Who does that?

1645
01:32:14,260 --> 01:32:15,410
I forget his name.

1646
01:32:15,490 --> 01:32:17,410
I think his name is like Don something.

1647
01:32:18,770 --> 01:32:19,010
Okay.

1648
01:32:19,410 --> 01:32:19,650
Anyway.

1649
01:32:19,970 --> 01:32:20,530
Um in a world.

1650
01:32:20,850 --> 01:32:22,770
They don't do those kinds of movie trailers anymore.

1651
01:32:22,850 --> 01:32:23,490
I miss them.

1652
01:32:23,810 --> 01:32:26,050
They don't have a voiceover actor doing the trailers.

1653
01:32:26,370 --> 01:32:27,730
Don LaFontaine.

1654
01:32:28,130 --> 01:32:29,490
Yeah, Don Lafontaine.

1655
01:32:29,570 --> 01:32:29,890
That's the guy.

1656
01:32:30,130 --> 01:32:30,370
Yeah.

1657
01:32:30,530 --> 01:32:33,570
Maybe we can get him to do our intros and that'd be really fun.

1658
01:32:33,890 --> 01:32:34,850
That would be great.

1659
01:32:35,040 --> 01:32:35,600
Yeah.

1660
01:32:35,920 --> 01:32:39,280
Is he still I mean he probably he's he hasn't gotten a lot of work.

1661
01:32:39,520 --> 01:32:43,280
You know, there he they don't do voiceovers anymore for trailers.

1662
01:32:43,520 --> 01:32:45,360
There's um I miss them.

1663
01:32:45,680 --> 01:32:46,320
Yeah.

1664
01:32:47,280 --> 01:32:48,720
He's still alive.

1665
01:32:48,880 --> 01:32:54,800
I feel like that that's one the that's one of um the things that I miss from the 90s and

1666
01:32:54,800 --> 01:32:57,120
early 2000s is the movie trailer voice.

1667
01:32:57,520 --> 01:33:01,920
And the other thing I miss is film scores that have a damn melody.

1668
01:33:02,690 --> 01:33:06,930
Everything is just drones and completely devoid of melody these days.

1669
01:33:07,090 --> 01:33:12,050
I miss the John Williams memorable melody that's that stays with you after the movie and

1670
01:33:12,050 --> 01:33:12,530
gets it.

1671
01:33:12,770 --> 01:33:18,210
Jurassic Park, I I still listen to Jurassic Park, you know, it's gorgeous pie that

1672
01:33:18,210 --> 01:33:20,770
soundtrack is really gorgeous piece of music.

1673
01:33:20,930 --> 01:33:23,090
And you know, film scores just don't do that anymore.

1674
01:33:23,170 --> 01:33:24,210
They're just drones.

1675
01:33:24,610 --> 01:33:25,650
It's really disappointing.

1676
01:33:25,730 --> 01:33:27,330
Yeah, we've regressed as a crossing.

1677
01:33:27,650 --> 01:33:28,930
Drones and green screens, yeah.

1678
01:33:29,010 --> 01:33:29,250
Yeah.

1679
01:33:29,600 --> 01:33:33,200
Drones, green screens, yeah, electronic screens.

1680
01:33:33,680 --> 01:33:38,080
Yeah, I mean, I don't you know, don't get me wrong, I like a good drone as much as the next

1681
01:33:38,080 --> 01:33:41,200
guy, but also you gotta have a melody, you know?

1682
01:33:41,600 --> 01:33:42,800
You preach, David.

1683
01:33:43,200 --> 01:33:44,000
Yeah, all right, all right.

1684
01:33:44,160 --> 01:33:48,720
So all of you folks who are doing um s uh Hollywood um

1685
01:33:49,360 --> 01:33:50,320
composition.

1686
01:33:51,130 --> 01:33:51,770
Yeah.

1687
01:33:52,250 --> 01:33:53,290
Take notice.

1688
01:33:53,610 --> 01:33:57,530
Take notice and uh, you know, enjoy some some John Williams.

1689
01:33:57,930 --> 01:34:00,330
Yeah, enjoy the melody on the way out here, too.

1690
01:34:00,490 --> 01:34:00,810
Yeah.

1691
01:34:00,970 --> 01:34:01,210
Yeah.

1692
01:34:01,370 --> 01:34:01,770
David.

1693
01:34:02,090 --> 01:34:05,050
Jurassic Park, Indiana Jones, Star Wars, whatever does it for you.

1694
01:34:05,210 --> 01:34:08,730
Listen to it, get it in your head, it'll provide a nice soundtrack to your life.

1695
01:34:08,970 --> 01:34:12,890
Are we allowed to play Jurassic Park as our outro for this episode?

1696
01:34:13,660 --> 01:34:16,700
Um, I think we might have to get them the rights.

1697
01:34:17,500 --> 01:34:20,300
But I I no one's gonna sue us, so I'll probably do it.

1698
01:34:20,700 --> 01:34:21,740
We'll call Sam Neil.

1699
01:34:22,060 --> 01:34:24,460
That that would be hilarious if somebody sued us.

1700
01:34:26,220 --> 01:34:31,420
Well, uh we probably won't get to it, but imagine Jurassic Park uh for it.

1701
01:34:32,060 --> 01:34:34,620
I could just hum the theme to Jurassic Park.

1702
01:34:35,420 --> 01:34:40,990
David, you're on you don't need any would that be the new that that yeah.

1703
01:34:41,710 --> 01:34:42,270
Can you work on that?

1704
01:34:42,350 --> 01:34:44,990
Can you do a mashup of Manafort and Jurassic Park?

1705
01:34:45,310 --> 01:34:46,350
Oh, that's a good idea.

1706
01:34:46,590 --> 01:34:46,830
Okay.

1707
01:34:46,990 --> 01:34:47,550
I'll work on it.

1708
01:34:47,710 --> 01:34:47,870
All right.

1709
01:34:47,950 --> 01:34:48,510
You're two.

1710
01:34:48,590 --> 01:34:51,870
We can slightly modify the um intro and outro.

1711
01:34:51,950 --> 01:34:52,830
So all right.

1712
01:34:52,910 --> 01:34:57,150
Uh everybody, thank you for listening for all three of you who who've stick stuck through

1713
01:34:57,150 --> 01:34:58,110
it this long.

1714
01:34:58,270 --> 01:35:00,110
Um I'll see you.

1715
01:35:00,190 --> 01:35:01,230
We'll see you next week.

1716
01:35:01,580 --> 01:35:03,260
Thank you for your service, listener.

1717
01:35:03,420 --> 01:35:03,740
Yeah.

1718
01:35:04,060 --> 01:35:04,460
Exactly.

1719
01:35:05,180 --> 01:35:05,820
Bye, David.

1720
01:35:05,900 --> 01:35:06,380
See you next week.

1721
01:35:06,460 --> 01:35:06,780
That was great.

1722
01:35:07,020 --> 01:35:07,500
Take it easy.

1723
01:35:07,580 --> 01:35:08,460
All right, bye.