WEBVTT

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Uh David, today is a very special day because it's Tuesday.

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And every Tuesday, what happens?

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Well, uh the latest episode of Evolutionary Psychology, the podcast comes out.

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And what is the tagline of the tagline is it's actual evolutionary psychology by

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Actual Evolutionary Psychologists.

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And you know, it's been uh really nice to hear from people saying that they're actual

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evolutionary psychologists and actually uh enjoying it, and they're confirming that it is

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kind of actually what we do.

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Yep.

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So here you go.

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Enjoy this next one.

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Happy Tuesday.

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David, I am always excited about our guests, but I'm especially excited about guests that

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uh we don't usually get to talk to in our day-to-day um sort of scientific um

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existence.

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And for me today, uh Ray Hames is one of those folks where um I had actually not really

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spent much time interacting with him previously, and um we got to talk to him about all

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kinds of stuff, including sort of early history of evolutionary behavioral sciences, and

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specifically working um in part with uh Nap Shagnon.

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That's right, with with the Yanomamo, which is a really fascinating group of people.

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He has some really uh uh incredible stories to tell about his experiences with the Yano

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Mamo.

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Uh this guy is a true veteran.

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Uh he was there right when the evolutionary behavioral sciences were becoming a thing.

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And uh this guy knows the development of this field.

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He has uh stories to tell and knowledge to share about how these fields developed and and

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you know whether they may have uh developed in the wrong way or the right way.

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Uh I think he has a few barbs about E.O.

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Wilson and about how maybe he oversimplified things.

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E.

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O.

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Wilson, for those of you who don't know, uh kicked off the evolutionary behavioral sciences

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with his book Sociobiology, uh, and that was later developed into evolutionary psychology

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by uh Leda Cosmodies and John Tubi.

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Uh but we get into all that history.

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Uh uh Ray was there from the very beginning, um, and uh he's just a a really um uh

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wonderful guy, brilliant mind, and uh we we learned so much from this conversation.

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Yeah, and we also had in the spirit of sort of the evolutionary social sciences as a

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community, we actually had a guest, uh um co-host, which who was uh Zach Garfield.

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So it's actually gonna be Ray and Zach and David and myself.

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So we're gonna we're gonna we're gonna I think start doing that um sometimes, especially

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having a returning guest kind of come on and and be with us um to talk to somebody new and

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you know, just different sort of different format.

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And it was wonderful to have Zach on because he had also unique uh experiences with Ray

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that we couldn't, David and I, um, sort of convey to folks.

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So I I really enjoyed that.

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Um one other note is that we did have some technical difficulty with um with Wi-Fi

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um uh in this episode.

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And so you might detect some some editing in the earlier uh stages um that you know so just

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just be aware of that.

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So thanks for bearing with that.

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Yes.

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All right.

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Without further ado, enjoy Ray Haynes.

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All right, so we are recording, and today we have uh a very special and unique uh set of

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guests.

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So by my math, we have one more person than we usually do.

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We usually have, well, actually, we usually have two or three people, but today we have

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four people.

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So we have uh returning guest, uh Zach Garfield, who is I would say our first guest

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co-host of the podcast.

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Um, but really why we're here is to talk to uh Ray Haymes.

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Um and Ray Hames, um, in addition to uh receiving the uh the HBES uh

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Lifetime Career Award has a number of um accolades and um awards and things, but I think

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we're gonna let Zach um sort of introduce who Ray is.

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Sure.

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Um thank you Dave and David for the chance to be a part of this conversation with Ray.

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Um so Ray Haymes uh is a professor emeritus at the University of Nebraska

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Lincoln um on his retirement uh tour now I suppose we could say And um

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I yeah, I first met Ray as I was an undergraduate at UNL.

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And I worked with Ray.

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He was my first introduction to anthropology and the evolutionary social sciences.

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Um, Ray's done pioneering work, uh, really sort of the first wave of human behavioral

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ecology and when evolutionary theory started to be sort of co-opted by cultural

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anthropologists, testing ideas uh that had come from math models and from biology among

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human populations.

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and he's done a lot of work on cooperation, food sharing, uh, the division of labor,

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decision making in households.

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Uh, also a wide sort of has his hands in a lot of other pots too, related to

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sexuality and marriage systems.

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And so he's he's kind of been around for the the emergence of our field.

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Um, he's invested a lot in methods too.

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So he's a methodological expert, especially regarding time allocation data collection

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and all the sort of tools that human behavioral ecologists were using, taking these models

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from biology and ethology and trying to apply them in rural subsistence-based communities.

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His accolades are extensive.

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He's trained many students.

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I'm one of them.

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Um he's recently uh member of the National Academy of Sciences as well.

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I think only the second uh faculty from UNL to join that's um that group.

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So um, you know, it was really an honor getting to work with Ray as an undergraduate, and

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he's continued to shepherd me along through my my training um and infected me with all many

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of his biases um along the way, which has been uh very useful.

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And it's yeah, it's an honor to have you here and to chat with you um on this podcast, Ray.

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Well, thank you for the nice uh introduction and I'm very happy to uh to to join uh

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Dave and David uh in this uh podcast.

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Uh I c listened to a few, one I think recently with uh with Ed Hagan.

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So here I am.

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Uh happy to be here.

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Uh I mean one one question to start and and uh Zach also uh feel free to jump in but but

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Ray one question is sort of um you know, as Zach mentioned, the you are sort of

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involved in sort of the first wave of applying these uh mathematical models from

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evolutionary biology at a time when doing so was just sort of unheard of or controversial.

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Um and I'm just sort of curious, sort of, what your experience was in

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sort of finding yourself in that situation.

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Uh yeah, I was among the first wave.

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Uh I I think uh, you know, um the shagdown was the you know true uh first wave

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along with don simons uh and people like david bus and then a little bit

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later uh tube and cosmeties uh you know came online i remember when

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i uh published a a paper on garden labor exchange um i got

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a a reviewer who said you know you've got to read who in the heck are these people uh but i

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looked up their work and found it to be uh very, very interesting, a bit rough, uh, because

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uh we were branded as um uh uh racist uh and um

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kind of spensarian uh conservatives.

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Uh and a lot of the problem stemmed from um, I think, if I may, uh

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Ed Wilson's work uh in terms of he said some really silly things, uh I should

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say inaccurate things.

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Uh what are some of those uh silly things?

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Or what are some examples of those silly things that he said?

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He said that you know all hunter gatherers were territorial.

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When in fact territoriality is a contingent response and resource density is high

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and predictability is high, then you would predict based on economic models,

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largely Jerem Brown's models of bird territoriality.

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And so you have a kind of range from home range systems to territorial systems.

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And so he was kind of like I would call him uh an old school

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ethologist who kind of approached human behavior from a very simple-minded

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sort of uh genetic determinism.

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Uh but still he's he's really important in in in our

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field.

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He just kind of like that got the stuff on hunter gatherers uh really, really wrong.

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Sort of like bringing in so the the ethology is this you know famous school of evolutionary

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biology that studied fixed action patterns or sort of innate reflexive behaviors like uh

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the probably the most commonly known one is imprinting.

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So a duckling will imprint on the the first thing it sees and sort of treat

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that thing as its parent.

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And so there are these famous photos of Conrad Lorenz with like a trail of ducklings

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following him along.

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And so you and what you seem to be saying is that he took this way of thinking, which may

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have worked out reasonably well in the case of ducklings, and applied it to humans, which

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led to some oversimplifications.

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Is that basically what you're saying?

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Yeah, uh indeed.

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And uh essentially he seemed to not be aware of the developments in behavioral ecology,

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in particular, of things like uh simple things like optimal foraging theory that

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demonstrated the contingency of uh of game selection, uh diet breath

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models, uh search patterns, etc., etc.

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Uh, which you know uh makes perfect sense uh because if we were stuck with fixed action

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patterns, we would be poorly adapted to to to the world.

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Yeah, yeah.

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Do you so how much of the the animosity do you think arose from Eo Wilson bungling

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things and oversimplifying things versus the mere fact of applying an evolutionary

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lens to human behavior?

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I think both are really critical.

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In fact, you know, when Evolution of Human Behavior had a previous name,

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and that was ethology and sociobiology.

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And I forget the date, but I think it was about 1980, early 80s,

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we had a meeting, I think it was at Michigan maybe, where uh Ed was a president,

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and we voted to change the name to Evolution and Human Behavior because

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there was this immediate association with the journal the term sociobiology, which was Ed's

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term, which meant that if you use that term to characterize yourself, you kind of were in

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his um mode of thinking.

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And so uh that was you know a kind of really important break that uh that

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that did occur.

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However, you know, uh still some of my old friends like Sarah Hurdy still use the term

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sociobiology to characterize uh herself, uh, but it's kind of a historical uh

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legacy.

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So there were uh I'm I'm trying to recall what the question was, you had a two part

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yeah it was just about whether um the uh applying evolution in general to have to

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do with the other

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What does evolution have to do with it?

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We're freed from that kind of constraint.

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And so that that mindset um was worked against us.

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One of the cartoonish like sort of narratives that at least I still hold a little bit is

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that um you know behavioral ecology was sort of not psychological enough, and that's

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why evolutionary psychology was necessary to really uh flesh out the

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evolved psychology and and actually talk about like what's the approximate system

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doing.

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But, you know, as I read a lot of the history of even ethology, but also human behavioral

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ecology, there's actually quite a bit of complex psychology in it.

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And so do you think it's sort of an inaccurate thing to say that human behavioral

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ecology wasn't psychological?

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Is that sort of an oversimplification?

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And was human behavioral ecology already doing evolutionary psychology, sort of?

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Um well it it it uh is an oversimplification, but it's actually pretty accurate.

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And uh, you know, what we do is essentially what Graven calls the the phenotypic gambit.

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Right.

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And we'll leave the neuromechanisms to you guys because you're really good at that.

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But our focus is on behavior.

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And behavior does have consequences, and there's got to be a payoff for particular kinds of

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behavior.

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And so this is something that um Don Simons uh brought in.

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Uh I think sometimes rather stridily, uh, but you know, of him.

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Uh and then of course John Alita you know brought that to the uh to the end that we're

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interested in looking at the uh real life consequences of behavior, because if

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a behavior is adaptive, we've got to show the payoff.

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Uh and it's clear that the psychological mechanisms are really important.

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And again, I would would view it as a division of labor.

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Yeah, yeah, that makes a lot of sense.

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How it felt like at that moment in time.

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I think like all of us would kind of agree that the evolutionary social sciences is this

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sort of know, paradigm shift.

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And at least that's our hope.

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And maybe the the future of fruits are still yet to be born, but we think that it's like a

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really big deal.

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I think most of the people in this field are quite passionate about it.

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They see it as like quite a big departure from, let's say, previous less or

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non-evolutionary models.

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But at that time, when this was first getting going, did it feel like it had the chance to

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be maybe what it would be perceived to be by like the the 90s and let's say now or was it

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just like I don't know let's try this new thing or did does that is my question clear did

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it did it seem like there was a a big sea change ahead or was it just like uh I don't know

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trying something weird and out of the box at the time?

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Well I think I can only speak for myself but uh if if m my idea was that

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if evolution is accurate, it ought to apply to us.

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And so the question becomes: how does it apply to us?

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And that was the thing that kind of drove me because we could

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look at all the sorts of physiological, morphological changes that

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occurred in the process of hominid evolution, clearly guided by

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evolution.

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But then when it came to the brain, somehow, you know, evolution didn't penetrate

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there.

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Somehow we became cultured and were like free of the bounds of

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evolutionary forces.

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And so I rejected, and I think a lot of us rejected that sort of uh

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process.

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The other thing that really was important is that we finally had a good

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hypothetical to deductive method to test our ideas.

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The only field at that time that really had that approach was economics.

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And were they, you know, rational choice, sort of, and so we have they had a real theory,

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although they there's some problems with that theory.

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And so a lot of us, you know, we're just like, wow, we've got this method where we

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can actually develop hypotheses and test them.

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And they may be wrong, but at least you you have that kind of security that as

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opposed to uh maybe I overgeneralize these ad hoc make sense to

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me stuff in psychology and sociology kind of models, we're getting us

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nowhere.

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Yeah.

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It's the same thing.

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It is an overgeneralization, but it's also accurate.

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It's the same answer you gave me a few minutes ago.

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Yes, exactly.

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And just for people listening, you know, those hypo hypothetic or deductive theories

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are essentially, you know, selection pressure dynamic models, right?

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So like things like optimal foraging or you know, ideal free distribution, or um

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things where you're sort of creating a model of saying, look, if there was a phenotypic

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design for dealing with a certain problem, what are the costs and benefits that that design

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would have to deal with and how would it respond or optimize those?

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And you can look at that for dealing with collecting food for conflict things like the

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asymmetric war of attrition.

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Um, you know, are those the kinds of models that you're talking about, these sort of um

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evolutionary game theory models?

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Yeah, I I think, you know, a a lot of us and and and I'll include uh my my

00:17:40.610 --> 00:17:46.120
compatriots at the time, uh Kim Hill, Bruce Winterholder, Eric Smith, Kristen

00:17:46.360 --> 00:17:47.080
Hawkes.

00:17:47.320 --> 00:17:51.880
Uh, we were, you know, uh essentially economic anthropologists.

00:17:52.200 --> 00:17:55.800
And so we knew about you know rational choice theory.

00:17:55.880 --> 00:18:01.800
Um, and then we read the literature on optimal foraging theory, uh, and

00:18:01.800 --> 00:18:06.360
we could see the mesh between the two, and we could see the direct application in terms of

00:18:06.360 --> 00:18:10.440
food getting activities for the kinds of research we did.

00:18:10.520 --> 00:18:16.010
And a lot of us worked in South America among you know barely acculturated uh

00:18:16.010 --> 00:18:21.930
groups and uh on hunter-gatherers and uh so that was something that you

00:18:21.930 --> 00:18:23.930
know immediately pulled us in.

00:18:24.090 --> 00:18:29.610
But and also we were um another kind of dimension that united us all we were we were

00:18:29.610 --> 00:18:31.370
quantitative in our approach.

00:18:31.770 --> 00:18:37.040
We want to know about return to effort uh and how that affected uh uh

00:18:37.040 --> 00:18:40.240
choices in terms of what people uh pursued.

00:18:40.400 --> 00:18:45.440
And so uh when we started uh reading um uh uh

00:18:45.760 --> 00:18:51.200
behavioral ecology it was a wonderful kind of uh uh guide for us.

00:18:51.920 --> 00:18:57.690
So if I'm hearing this right, it was sort of you were inspired by economics thinking

00:18:57.690 --> 00:19:02.810
about humans from this economic perspective, and then came across behavioral ecology as

00:19:02.810 --> 00:19:05.050
well and sort of integrated the two.

00:19:05.930 --> 00:19:10.650
But anyway, another element was kind of really interesting, group selection approach, which

00:19:10.650 --> 00:19:13.690
was very comforting to a lot of uh anthropologists.

00:19:13.930 --> 00:19:19.760
Uh and uh so uh that was uh and the whole

00:19:19.760 --> 00:19:25.680
issue of Wynn Edwards and population regulation and people

00:19:26.000 --> 00:19:30.240
doing things uh for the good of their group and ridiculous arguments.

00:19:30.400 --> 00:19:36.160
Uh please kill your kids because we don't want uh our population to overshoot the

00:19:36.160 --> 00:19:38.080
um uh resources.

00:19:39.840 --> 00:19:45.710
Uh uh in a population of, you know, 50 people in a village,

00:19:45.950 --> 00:19:50.750
okay, you gotta start killing your kids because we're worried about long-term uh ecological

00:19:50.750 --> 00:19:52.750
damage because we gotta maintain a stead.

00:19:52.990 --> 00:19:57.390
You know, it was like laughable on the face of it when you're really I shouldn't be so

00:19:57.390 --> 00:19:58.990
sarcastic, I suppose.

00:19:59.070 --> 00:20:03.950
Uh but at the same time, it it it just was like bewildering.

00:20:04.110 --> 00:20:06.910
What parent would ever behave in that way?

00:20:07.150 --> 00:20:13.000
In fact, the argument would be uh uh you kill your kids and

00:20:13.080 --> 00:20:14.280
leave mine alone.

00:20:15.480 --> 00:20:16.280
Right, right.

00:20:16.920 --> 00:20:17.560
Yeah.

00:20:19.000 --> 00:20:23.960
Um Ray, you mentioned, you know, that you guys, you and your compatriots brought this

00:20:23.960 --> 00:20:25.880
quantitative approach in anthropology.

00:20:25.960 --> 00:20:30.280
But many of you were trained as like cultural anthropologists, maybe in your undergrad or

00:20:30.280 --> 00:20:31.640
earlier in your graduate training.

00:20:31.800 --> 00:20:35.370
So I kind of wonder like how it went in the field for you at that time, Because

00:20:35.530 --> 00:20:39.930
quantitative anthropologists always face this trade-off because we we need that qualitative

00:20:40.010 --> 00:20:44.570
ethnographic insight to know what questions to ask, know how to interpret our results.

00:20:44.890 --> 00:20:48.090
But at the same time, you know, collecting time allocation data is super intensive.

00:20:48.170 --> 00:20:52.490
So you kind of can't do both, but at the same time, you kind of have to do both.

00:20:52.650 --> 00:20:57.220
So I wonder how that went for you, like adopting a quantitative approach, but also trying

00:20:57.220 --> 00:20:59.620
to get this deep ethnographic insights.

00:20:59.780 --> 00:21:02.900
Um, you know, I I know you consider yourself an ethnographer as well.

00:21:02.980 --> 00:21:05.300
And then also, you know, which communities were you mostly working with?

00:21:05.380 --> 00:21:08.820
I didn't mention that in your in your introduction, but how did you balance that?

00:21:08.980 --> 00:21:12.500
Getting the ethnographic qualitative perspective while also collecting this rich

00:21:12.580 --> 00:21:14.020
quantitative data?

00:21:14.740 --> 00:21:20.340
Well, uh to do both because you know, we had uh a legacy of, you know, I'm

00:21:20.740 --> 00:21:23.630
uh Shagna was one of my mentors.

00:21:23.870 --> 00:21:26.510
Elma Service was another one of my my mentors.

00:21:26.750 --> 00:21:30.270
And both all of those people had done kind of good qualitative research.

00:21:30.350 --> 00:21:34.750
So it was kind of an expectation that we would balance the two.

00:21:35.150 --> 00:21:40.350
And you know, for example, if you look at, you know, speaking of Shagnan, um uh he was

00:21:40.350 --> 00:21:46.030
working with James Neal, and he really got into extensive

00:21:46.030 --> 00:21:51.900
demographic uh research, but added kinship to that

00:21:51.900 --> 00:21:56.540
dimension that I think um Neil wasn't too interested in.

00:21:56.700 --> 00:22:02.620
And then he was trained as to some extent as a you know a Michigan cultural

00:22:02.620 --> 00:22:08.060
evolutionist uh who believed in uh looking at the um uh

00:22:08.300 --> 00:22:12.460
humanistic and qualitative dimensions of of human behavior

00:22:14.670 --> 00:22:18.510
Have I answered your question?

00:22:19.230 --> 00:22:20.750
Yeah, yeah, yeah, I think so.

00:22:20.910 --> 00:22:22.750
So, what were the communities that you worked with?

00:22:22.830 --> 00:22:27.390
And did you, you know, did you work with translators in the field or did you develop

00:22:27.390 --> 00:22:30.270
language proficiency at the outsets?

00:22:31.230 --> 00:22:33.230
Well, uh a good question.

00:22:33.310 --> 00:22:38.820
Um, you're really full language capabilities, uh, because you you know you're in a village

00:22:38.900 --> 00:22:41.940
and you can't talk, don't know your language, and you don't know their language.

00:22:42.180 --> 00:22:48.100
And so the motivation is really powerful just to have some like normal human intercourse

00:22:48.100 --> 00:22:53.300
on a daily basis, whether it's hi, how you doing, you know, good morning, sort of stuff

00:22:53.300 --> 00:22:53.700
like that.

00:22:53.780 --> 00:22:59.780
And so uh you really are uh highly motivated uh to learn

00:22:59.780 --> 00:23:00.580
the language.

00:23:00.820 --> 00:23:06.650
And fortunately, Yanamamo was, I would say, uh it won't sound arrogant,

00:23:06.730 --> 00:23:08.970
but it was a pretty easy language to learn.

00:23:09.450 --> 00:23:14.650
Yaquana, another group I worked with, was really tough because the

00:23:14.970 --> 00:23:19.370
phonemic system, you know, for example, all the valves could be glottalized.

00:23:19.450 --> 00:23:24.490
And that takes a lot of practice to get your chops down speaking that way.

00:23:24.650 --> 00:23:30.010
And so actually, uh, when I did uh my research on the Yanamamo, I uh I used Gianamamo.

00:23:30.330 --> 00:23:35.740
And when I did my research on the Yaquana, I used Yanomamo because the Yaquana could

00:23:35.740 --> 00:23:41.660
understand um Yanomamo because of the trading relationships and intermarriages

00:23:41.820 --> 00:23:44.460
and some kind of village coalescences.

00:23:44.860 --> 00:23:49.900
And then also, you know, through a little Spanish for some of the yaquana who uh could uh

00:23:50.060 --> 00:23:53.100
mainly the men who could understand uh Spanish.

00:23:53.420 --> 00:23:59.420
And so um yeah learning the language is is uh is really critical.

00:24:00.610 --> 00:24:00.850
Yeah.

00:24:01.010 --> 00:24:04.850
And what what was that uh working with in the Yanamamo?

00:24:05.170 --> 00:24:11.090
I mean, you know, that was a very kind of famous and slightly infamous field site, um,

00:24:11.330 --> 00:24:16.690
especially with sort of the um the darkness in El Dorado controversy, which you know, you

00:24:16.690 --> 00:24:21.490
and Tubi and other people, you know, really vindicated and you know, showed that there was

00:24:21.490 --> 00:24:24.930
really nothing to that, or to the extent there was something to it on the on the other

00:24:24.930 --> 00:24:25.810
folks' end.

00:24:26.100 --> 00:24:29.700
But um like what was it like going to Yanamamo land?

00:24:30.020 --> 00:24:34.420
Uh and you know with with or without Nap Shagnan on what was that like?

00:24:34.900 --> 00:24:36.020
Oh what can I say?

00:24:36.180 --> 00:24:41.860
It was scary, not because of the Yanamamo per se, but I remember

00:24:42.020 --> 00:24:47.780
um I was with the team, uh we were all in a set of

00:24:47.780 --> 00:24:48.900
big canoes.

00:24:49.060 --> 00:24:52.420
I was the first one dropped off at the end of the Orinoco.

00:24:52.580 --> 00:24:58.510
We're easy um uh uh travel is is possible from

00:24:58.510 --> 00:24:59.390
that point forward.

00:24:59.470 --> 00:25:05.470
I'm we're talking about maybe oh uh 50 miles from the headwaters

00:25:05.710 --> 00:25:07.070
where I was dropped off.

00:25:07.310 --> 00:25:13.310
And I remember walking up the slope after I unpacked all my stuff and looking at

00:25:13.310 --> 00:25:19.020
Knapp and uh Bob Carnero and and a couple other people um uh

00:25:19.340 --> 00:25:25.260
leaving me and I thought as I walked up that slope, you know, okay, here it begins.

00:25:25.420 --> 00:25:30.940
Uh I had no canoe to uh get back to the to the

00:25:30.940 --> 00:25:31.580
missions.

00:25:31.820 --> 00:25:37.180
Uh I had no uh communication system uh in that uh

00:25:37.740 --> 00:25:43.190
uh uh what do you call that uh kind of communication uh

00:25:43.430 --> 00:25:49.430
well i i had no radio essentially to to call if i needed help and but you know

00:25:49.510 --> 00:25:55.350
i was young male uh and ready for for adventure and probably

00:25:55.430 --> 00:26:01.430
uh clearly overestimated uh my ability to to handle problems uh i

00:26:01.430 --> 00:26:07.030
did have a medical kit uh but i figured you know if i broke a leg i would be in

00:26:07.030 --> 00:26:12.820
bad shape uh and uh you know i in in kind of

00:26:12.820 --> 00:26:18.660
modern fieldwork, uh, you have good radio communication and you know where you

00:26:18.660 --> 00:26:19.700
can get help.

00:26:19.860 --> 00:26:23.540
And you've already pre-planned, you know, if something should go wrong.

00:26:23.700 --> 00:26:29.300
Uh, and then at the ultimate, you know, you can get extraction uh insurance,

00:26:29.460 --> 00:26:35.300
such that if you're in a really difficult to get to, uh, you know, uh, but you know, so

00:26:35.300 --> 00:26:37.620
back then, no satellite communications.

00:26:38.410 --> 00:26:42.730
And everything was, you know, by foot or by by river.

00:26:43.290 --> 00:26:46.890
But you know, after a while, you know, you're there for purpose.

00:26:47.450 --> 00:26:50.170
The Anomamo treated me really, really well.

00:26:50.810 --> 00:26:52.250
They're very kind to me.

00:26:52.570 --> 00:26:57.690
They could get real demanding, but then, you know, you could get, you know, right back in

00:26:57.690 --> 00:26:58.330
their face.

00:26:59.290 --> 00:27:03.370
But so I was really fortunate that

00:27:05.620 --> 00:27:09.380
they they treated me, you know, quite well.

00:27:09.620 --> 00:27:15.060
They the only thing that really bothered me later in the field was when it's not uncommon

00:27:15.060 --> 00:27:20.420
for the Anamamo to threaten you with mortal harm if you didn't give them something.

00:27:20.660 --> 00:27:26.020
Uh, and then you know, so there's this old guy, you know, he's kind of threatening you, and

00:27:26.020 --> 00:27:31.410
you know he've k he's killed six people, So he's perfectly capable of

00:27:31.410 --> 00:27:32.690
dispatching you.

00:27:33.010 --> 00:27:38.210
But you know, that would be the wrong thing to do because I was the source of axes and

00:27:38.210 --> 00:27:41.330
machetes and fish hooks and fish line, et cetera, et cetera.

00:27:41.490 --> 00:27:46.290
And they didn't want to kill the, you know, or he didn't want to response for killing the

00:27:46.450 --> 00:27:47.330
golden goose.

00:27:47.410 --> 00:27:51.330
But you know, people can get really mad and not think things through.

00:27:51.490 --> 00:27:56.770
Uh, and so uh, but anyway, uh the anima were very nice to me.

00:27:57.560 --> 00:27:59.080
Aside from the death threats.

00:28:00.200 --> 00:28:05.880
Yeah, but see that's just kind of like uh banter.

00:28:07.240 --> 00:28:07.720
Teasing.

00:28:07.800 --> 00:28:11.080
Is it kind of like was it is quasi-humorous?

00:28:11.720 --> 00:28:15.160
Well it was to push you to see how you would respond.

00:28:15.640 --> 00:28:16.440
It was testing it.

00:28:16.600 --> 00:28:18.280
So it's a kind of a game.

00:28:18.440 --> 00:28:18.600
Yeah.

00:28:19.080 --> 00:28:24.970
Uh and um you would just respond either silently or

00:28:25.210 --> 00:28:26.570
I don't think so.

00:28:27.050 --> 00:28:31.290
Uh you're a little guy and I could take you out right now, barehanded.

00:28:31.370 --> 00:28:34.090
You know, you just kind of give it back to them.

00:28:34.170 --> 00:28:38.250
Uh, but in a kind of like not overextended way.

00:28:38.410 --> 00:28:44.170
Uh and you want to, you know, kind of like uh uh get out of that back and

00:28:44.170 --> 00:28:45.850
forth as quickly as possible.

00:28:48.000 --> 00:28:53.360
Maybe could you tell us just like what a typical day looked like collecting data in a

00:28:53.360 --> 00:28:55.280
Yanamoma village in this time?

00:28:55.440 --> 00:28:59.680
And I mean I I imagine there's overlap with how what fieldwork is like today or in

00:28:59.680 --> 00:29:02.960
different places, but maybe there's some I don't know unique components.

00:29:03.120 --> 00:29:06.480
Like what was just like a typical, you know, you wake up in the morning until you go to bed

00:29:06.560 --> 00:29:07.440
on average.

00:29:08.310 --> 00:29:11.030
Well, wake up in the morning, have some coffee.

00:29:11.750 --> 00:29:13.590
Day starts when the sun gets up.

00:29:13.750 --> 00:29:19.190
Everyone is is is is uh is up, and day ends when the sun pretty much goes down.

00:29:19.430 --> 00:29:25.030
Although people will you know chat around the fires, uh eat a little bit, uh shamans will

00:29:25.750 --> 00:29:28.150
chant, uh babies will cry.

00:29:28.310 --> 00:29:34.000
Uh but by about I would say nine o'clock, everyone is sawing

00:29:34.000 --> 00:29:36.880
logs and comfortable in their in their hammocks.

00:29:36.960 --> 00:29:39.840
But uh getting up in the morning, uh it depends.

00:29:39.920 --> 00:29:45.120
You know, sometimes uh a real quick lunch because I have a hunting trip to go on with a

00:29:45.120 --> 00:29:48.800
bunch of people I'm gonna track and collect data doing that.

00:29:48.880 --> 00:29:52.800
And so might be gone for until until noon.

00:29:52.960 --> 00:29:55.680
Uh or maybe there was a gathering trip.

00:29:55.760 --> 00:30:01.590
And so I go out with uh some women and a couple of men, And we would go to a

00:30:01.590 --> 00:30:07.350
spot and and I would record gathering food, food

00:30:07.350 --> 00:30:10.790
collection uh activities, foraging activities.

00:30:11.830 --> 00:30:17.830
And then, you know, when I first got there, uh early in the morning, you know,

00:30:18.150 --> 00:30:23.030
I would uh be talking with a couple of young guys I hired to learn the language, to

00:30:23.030 --> 00:30:28.840
practice the language, and to, you know, really, I can't stress how much, you know, the the

00:30:28.840 --> 00:30:34.600
social isolation is is getting over that, getting through

00:30:34.600 --> 00:30:40.440
that is uh just to make yourself feel part of a group uh is is

00:30:40.440 --> 00:30:41.000
really important.

00:30:41.080 --> 00:30:42.040
So learning the language.

00:30:42.120 --> 00:30:47.480
And in fact, the thing is what I found interesting when I would go to Caracas to get

00:30:47.480 --> 00:30:53.240
resupplied, I felt really lonely because there was nobody there who gave a shit

00:30:53.240 --> 00:30:53.880
about me.

00:30:54.090 --> 00:30:58.170
You know, uh, I was just some, you know, faceless name.

00:30:58.330 --> 00:31:03.770
I felt psychologically much more comfortable back in the village where I had

00:31:03.770 --> 00:31:08.010
friends who actually, some of them, you know, cared about me.

00:31:08.170 --> 00:31:12.410
Others wanted to keep me around for the resources that I had, etc., etc.

00:31:12.970 --> 00:31:18.860
Um so uh, you know, early on to answer your question, uh couple

00:31:19.020 --> 00:31:20.700
hours in the morning learning the language.

00:31:20.860 --> 00:31:26.140
And then the nice thing about behavior observations is that you can, you know, essentially

00:31:26.140 --> 00:31:29.580
do it with limited uh uh competence.

00:31:29.980 --> 00:31:34.860
Uh and you know if someone wasn't there, then I would ask, you know, where's so-and-so?

00:31:35.180 --> 00:31:36.460
I was able to ask that.

00:31:36.620 --> 00:31:37.500
What were they doing?

00:31:37.660 --> 00:31:39.420
Who were they with, et cetera, et cetera.

00:31:39.580 --> 00:31:44.460
So you have not direct observations, you have reports of what people were doing.

00:31:44.700 --> 00:31:49.910
And so um the first part of my research was

00:31:50.470 --> 00:31:56.310
learning the language and then making rounds throughout the

00:31:56.310 --> 00:31:59.910
day and then uh see what everyone was doing.

00:32:00.070 --> 00:32:05.990
And then you know you have special topics, you know, uh who was married to whom, uh trying

00:32:05.990 --> 00:32:11.910
to get some good demographic kinship information uh and and things of that nature.

00:32:12.660 --> 00:32:12.820
Yeah.

00:32:12.980 --> 00:32:16.740
Some of your early work, or I mean, maybe not early, but just sort of you had things on

00:32:16.740 --> 00:32:17.860
like time allocation.

00:32:17.940 --> 00:32:22.100
And especially nowadays, it's so easy to just sort of push an electronic button.

00:32:22.340 --> 00:32:26.500
Um, you know, at that time, was it recording things on paper and pencil?

00:32:26.580 --> 00:32:29.700
Or you know, how are you recording time allocation things?

00:32:30.260 --> 00:32:32.500
You ever hear of a Fortran coding sheet?

00:32:32.740 --> 00:32:33.140
Mm-hmm.

00:32:34.100 --> 00:32:39.780
Yeah, that's what I I used, uh, you know, and uh

00:32:40.020 --> 00:32:44.210
so uh all that's you know, it's it's it's essentially a spreadsheet.

00:32:44.290 --> 00:32:47.730
Uh but but uh that was what I brought into the field.

00:32:47.890 --> 00:32:51.650
And then of course uh I had no computer at the time.

00:32:51.890 --> 00:32:56.930
Later on, we were some of the, I think maybe first anthropologists to use computers in

00:32:57.090 --> 00:32:58.130
remote areas.

00:32:58.370 --> 00:33:04.210
But yeah, everything was pencil and paper, pencil and paper, and then carbon paper because

00:33:04.290 --> 00:33:09.380
you know you want to have backups, uh, because you know, nothing could be more

00:33:09.380 --> 00:33:14.980
horrible than to uh be in the field for six months and lose your

00:33:14.980 --> 00:33:18.340
data or have the data somehow wrecked.

00:33:18.420 --> 00:33:23.460
And it means that's that's six months of your life, you know, just kind of like down the

00:33:23.460 --> 00:33:23.940
drain.

00:33:24.260 --> 00:33:30.230
And so you get really uh careful uh and always have this kind

00:33:30.230 --> 00:33:36.150
of shadow of paranoia uh you know what if what if you know something would uh would go on

00:33:36.470 --> 00:33:41.750
yeah and i don't think that uh area is particularly favorable to like pres preserving paper

00:33:41.910 --> 00:33:45.670
like i think people have talked about how their clothes rot you know like let alone paper

00:33:45.830 --> 00:33:51.670
nice sheets of paper uh that's not very friendly for paper you're right in fact uh

00:33:52.160 --> 00:33:57.360
Shagnell wrote a book called Studying the Yamamo, where he made a bunch of recommendations

00:33:57.360 --> 00:34:01.440
for people uh working in uh remote areas.

00:34:01.680 --> 00:34:07.440
And he was criticized for saying things like, you know, don't use red uh red ink on your

00:34:07.440 --> 00:34:07.680
pens.

00:34:08.080 --> 00:34:11.840
Well, it's goddamn right because it smears, it runs.

00:34:12.400 --> 00:34:17.810
And so he had a bunch of great tips for you know recording data,

00:34:17.970 --> 00:34:19.170
safeguarding data.

00:34:19.330 --> 00:34:24.130
He also had some really bad advice about what kind of shoes to uh to use.

00:34:24.370 --> 00:34:29.890
He he was in favor of Chuck Taylor of All-Stars, uh, which are terrible.

00:34:30.050 --> 00:34:35.730
Uh they had no heel cups, uh, they had no art supports, uh, you know,

00:34:35.890 --> 00:34:41.360
they the rocks will go right through you and there's not no waterproofing anywhere.

00:34:41.440 --> 00:34:42.000
Yeah.

00:34:43.040 --> 00:34:48.720
But but you know, he he uh and also that the thing is that uh uh you don't want a whole

00:34:48.720 --> 00:34:50.400
cotton uh anything.

00:34:50.560 --> 00:34:53.280
You want a polyester cotton blend.

00:34:53.600 --> 00:34:58.000
Uh but I've had ants, you know, eat through socks, wool socks for some reason.

00:34:58.080 --> 00:34:59.760
Some ants love wool socks.

00:35:00.320 --> 00:35:02.320
Uh or or socks that have a mole.

00:35:02.560 --> 00:35:08.390
So yeah, there there are lots of sort of practical things that uh uh are uh are

00:35:08.390 --> 00:35:09.030
really important.

00:35:09.590 --> 00:35:09.910
Yeah.

00:35:10.150 --> 00:35:15.910
What was um Napoleon Shagnon like uh as a sort of person in the

00:35:15.910 --> 00:35:18.070
field to be with and an advisor?

00:35:18.150 --> 00:35:19.430
Like what was that like?

00:35:20.550 --> 00:35:26.550
Uh well uh when I was first in the field, my

00:35:26.550 --> 00:35:32.550
first you know, probably 18 months divided in a bunch of segments, we didn't work much

00:35:32.550 --> 00:35:33.910
at all together.

00:35:34.680 --> 00:35:38.680
You know, I had my site initially with the Yanemama, later with the Yakwana.

00:35:39.720 --> 00:35:45.160
He would visit periodically to see how things were going on with the other two researchers,

00:35:45.400 --> 00:35:47.240
Ken Good and Eric Fredlin.

00:35:48.120 --> 00:35:53.720
And then later in the early 80s, we got an NSF grant

00:35:53.720 --> 00:35:55.960
together and we worked together.

00:35:57.390 --> 00:36:02.030
uh slept next to that man more than any other person except his wife.

00:36:02.190 --> 00:36:08.030
Uh and um uh so we were probably, oh I

00:36:08.030 --> 00:36:13.630
would say probably about 11 months over three different periods, you know, working

00:36:13.630 --> 00:36:14.270
together.

00:36:14.510 --> 00:36:18.270
Uh one thing is that the Alamamo adored him.

00:36:18.840 --> 00:36:24.440
They thought he was, you know, someone who could speak their language, act like a

00:36:24.440 --> 00:36:29.320
Yanomamo in terms of having the Yanamamo are very lively people.

00:36:29.560 --> 00:36:30.840
They like to joke.

00:36:31.160 --> 00:36:33.080
They're very spontaneous.

00:36:44.090 --> 00:36:47.610
in in terms of the personality, but Nap really had a knack.

00:36:49.530 --> 00:36:54.810
They had a personality that he kind of had uh to some extent.

00:36:55.130 --> 00:37:00.810
And so uh they just thought he was uh you know totally cool, uh,

00:37:01.130 --> 00:37:02.330
glad to have him.

00:37:02.570 --> 00:37:08.060
He had a reputation for being very generous, He had a reputation for

00:37:08.620 --> 00:37:10.620
speaking the language really well.

00:37:11.180 --> 00:37:17.020
And there's a certain kind of, you know, bravado you

00:37:17.020 --> 00:37:21.900
have to use when you're kind of like having that stature.

00:37:22.540 --> 00:37:24.940
And he was really, really good at it.

00:37:29.510 --> 00:37:35.510
So we uh we had a few fights in the field uh because I wanted to do

00:37:35.510 --> 00:37:41.110
A and he wanted to do B, or he thought I was too pushy here and I thought he was, you know,

00:37:41.590 --> 00:37:46.630
normal sorts of things, uh, but nothing that permanently, just for a couple days, you know,

00:37:46.790 --> 00:37:49.750
had us at odds with uh with one another.

00:37:49.830 --> 00:37:55.030
But it's you know kind of normal things where you're trying to coordinate each one's

00:37:55.030 --> 00:37:59.040
priorities and and different field work styles etc.

00:37:59.600 --> 00:38:05.600
Yeah yeah I think anybody would recognize that yeah for sure I mean what one uh some

00:38:05.600 --> 00:38:09.520
people just sort of described him as like sort of larger than life do you think that's

00:38:09.520 --> 00:38:14.560
accurate or was that sort of a glossing for people who didn't know him so well

00:38:15.760 --> 00:38:21.600
uh oh yeah definitely larger than life uh yeah that uh is uh true in a

00:38:21.600 --> 00:38:27.350
lot of uh a lot of areas uh especially with uh a few beers

00:38:27.350 --> 00:38:29.830
in him and uh things of that nature.

00:38:29.990 --> 00:38:35.830
But uh and also he was uh whenever I would visit him or he'd visit me, it's

00:38:35.830 --> 00:38:37.030
like it was playtime.

00:38:37.510 --> 00:38:43.510
Let's go uh shoot some skeet, uh let's go play golf, uh let's play some

00:38:43.510 --> 00:38:44.230
tennis.

00:38:44.470 --> 00:38:47.270
Uh he, you know, let's go fish it.

00:38:47.580 --> 00:38:51.580
Um uh I hear there's some good pheasant hunting around here, you know.

00:38:51.660 --> 00:38:57.500
So he was a very kind of like uh an active person, a playful person who liked,

00:38:57.580 --> 00:38:59.500
you know, uh to do physical things.

00:38:59.660 --> 00:39:03.340
And so yeah, larger than life, uh he uh

00:39:06.620 --> 00:39:08.750
well I'll stop there.

00:39:09.070 --> 00:39:09.630
Sure.

00:39:09.870 --> 00:39:14.030
Well one thing I wanted to ask about is sort of you've studied like time allocation, also

00:39:14.110 --> 00:39:17.550
hunting, you know, and you have this thing of like gamekeepers.

00:39:17.710 --> 00:39:23.550
And um I was sort of reflecting on, you know, uh we're all people with our

00:39:23.550 --> 00:39:25.150
own particular experiences.

00:39:25.390 --> 00:39:29.950
You know, I had a sort of weird upbringing where I grew up sort of like duck hunting and

00:39:29.950 --> 00:39:33.710
trapping in upstate New York and I sort of feel affinity to doing that.

00:39:33.940 --> 00:39:38.180
And I think that's sort of unusual, at least among experimental psychologists, you know, or

00:39:38.180 --> 00:39:39.780
the people I'm with.

00:39:39.940 --> 00:39:45.700
And I wonder, sort of, if like, you know, things like hunting or just subsistence

00:39:45.700 --> 00:39:50.100
things, you know, I think it's nice to talk to anthro folks, especially among us

00:39:50.100 --> 00:39:52.820
psychologists, because you, you know, you study that.

00:39:52.980 --> 00:39:58.510
But I do wonder if sort of like the culture of, you know not doing that sort of blinds us

00:39:58.510 --> 00:40:01.310
to, for example, like the importance of the psychology of hunting.

00:40:01.470 --> 00:40:04.830
I don't really know much work on that in evolutionary psychology.

00:40:04.910 --> 00:40:08.670
I know Clark has a little bit on it, you have a some work on it, but like among us

00:40:08.670 --> 00:40:11.390
psychologists, we're not really doing very much on that.

00:40:12.590 --> 00:40:12.990
Yeah.

00:40:13.230 --> 00:40:19.150
Uh I didn't well, you know, Nap uh essentially sometimes uh brought food into

00:40:19.150 --> 00:40:23.520
his family through hunting because they weren't very uh well off.

00:40:24.640 --> 00:40:29.440
And uh so and he was an extra excellent shot with a shotgun.

00:40:29.520 --> 00:40:34.720
He would be in competitions where you'd hit 99 out of 100 targets, you know, different

00:40:34.720 --> 00:40:35.280
gauges.

00:40:35.440 --> 00:40:39.680
And so he was really skilled, uh well, I would say a skilled outdoorsman.

00:40:39.760 --> 00:40:45.230
Yeah, I kind of grew up in that similar environment, and given where I lived.

00:40:45.310 --> 00:40:51.150
And so that helped a lot in terms of me studying hunting.

00:40:51.630 --> 00:40:57.550
But there were kind of certain limitations in that I had a 16-gauge shotgun I brought into

00:40:57.550 --> 00:40:58.190
the field.

00:40:58.430 --> 00:41:03.310
And a lot of it was for, you know, you get tired of canon tuna.

00:41:03.660 --> 00:41:09.340
uh uh, or someone gives you a piece of eight-day old tape here that is like turning

00:41:09.340 --> 00:41:09.980
yellow.

00:41:10.060 --> 00:41:12.300
Uh, you know, you want fresh food.

00:41:12.460 --> 00:41:17.740
Uh, and so uh, and then also uh just a bit of an aside,

00:41:19.180 --> 00:41:23.900
uh as a male, you were expected to be armed.

00:41:24.670 --> 00:41:30.590
And I remember one time I was going to go leave the village and I was going to

00:41:30.590 --> 00:41:35.470
trail a group of women who were going to go to a fishing spot.

00:41:35.710 --> 00:41:40.670
And I heard this shout out from two people, why are you leaving naked?

00:41:41.390 --> 00:41:46.750
And I'm looking, I've got more clothes on than the entire village has in their possession.

00:41:46.830 --> 00:41:48.190
What are you talking about?

00:41:48.350 --> 00:41:51.870
Well, it's another metaphor for why are you unarmed?

00:41:52.980 --> 00:41:58.580
And so the idea was that uh I should be unarmed, I should be armed

00:41:58.900 --> 00:42:04.740
because I'm with a group of women who could be abducted, and I'm their only uh defender.

00:42:04.980 --> 00:42:10.980
Uh and so uh, you know, carrying a weapon is just part of

00:42:10.980 --> 00:42:15.780
who you become uh if you're working with the uh with the anomamo.

00:42:17.390 --> 00:42:23.310
One thing that really impressed me about hunting, and you read about these,

00:42:23.390 --> 00:42:28.830
you know, great white hunters who go to Africa on safari and they have you know

00:42:29.150 --> 00:42:32.110
anything from a gun bear to a guide, etc.

00:42:32.350 --> 00:42:32.590
etc.

00:42:33.870 --> 00:42:39.780
I could have my shotgun and probably only hunt about, you know,

00:42:39.940 --> 00:42:44.820
one tenth of the efficiency that the Yanomamal have with their bows and arrows because

00:42:44.820 --> 00:42:50.820
where the game is likely to be, how to approach it, where does it go when it's wounded?

00:42:51.060 --> 00:42:56.500
How do you chase it if they you discover, you know, all these sorts of things, you know,

00:42:56.740 --> 00:42:59.860
demand a tremendous amount of time and skill.

00:43:00.020 --> 00:43:05.910
The thing, and I got fairly good, but the thing I could never uh be good at was going after

00:43:05.910 --> 00:43:11.510
monkeys because they're up there and you're running

00:43:11.510 --> 00:43:12.470
after them.

00:43:12.870 --> 00:43:18.630
And how the animal don't fall over and get tripped was always beyond

00:43:18.790 --> 00:43:22.710
me because I would never, I learned never to look up.

00:43:22.870 --> 00:43:28.160
I looked at brown butts in front of me uh because i had to you know

00:43:28.400 --> 00:43:34.400
watch where i was going because it was so so hard to to run through the jungle uh

00:43:34.480 --> 00:43:38.400
you know it's kind of i think there's a credence clearwater song about that but anyway uh

00:43:38.560 --> 00:43:44.480
it's it's really difficult yeah yes what

00:43:44.640 --> 00:43:50.480
one of the many stories uh uh and for learning that that's things that like just kids are

00:43:50.480 --> 00:43:55.670
doing running through the jungle uh during the day uh and they're just doing that all their

00:43:55.670 --> 00:43:55.990
life.

00:43:56.070 --> 00:43:56.710
Yeah.

00:43:57.750 --> 00:43:57.990
Yeah.

00:43:58.230 --> 00:44:03.830
So anyway, I really learned about you know the the skill of hunting and how long it takes

00:44:03.830 --> 00:44:05.190
to uh uh develop.

00:44:05.350 --> 00:44:11.110
I remember one time I had this book on birds of South America and this old

00:44:11.110 --> 00:44:16.950
guy had a grandson with him and he's going through this book and he knew so many of the

00:44:16.950 --> 00:44:22.680
birds and he was telling his grandson about the sounds they make, where they're

00:44:22.680 --> 00:44:27.960
found, uh, and all this sorts of you know really rich uh what we call traditional

00:44:27.960 --> 00:44:33.400
ecological knowledge that was being transmitted to this kid through this book uh that I

00:44:33.480 --> 00:44:34.360
that I had.

00:44:34.680 --> 00:44:35.880
Yeah, yeah.

00:44:36.120 --> 00:44:37.080
It's amazing.

00:44:37.240 --> 00:44:37.880
Yeah.

00:44:38.280 --> 00:44:44.120
Um and what uh for for sort of moving back a little bit towards the

00:44:44.120 --> 00:44:49.850
science thing, um What was, you know, when you're in the field and

00:44:49.850 --> 00:44:55.770
then going back to sort of scientific conferences, what was it like

00:44:55.770 --> 00:44:59.370
at that point when you were, you know, where you were presenting your data?

00:44:59.530 --> 00:45:01.690
Were people sort of saying, well, what are you doing?

00:45:01.850 --> 00:45:07.050
Or was it, were you just presenting at the uh Human Behavior and Evolution Society?

00:45:07.210 --> 00:45:10.970
Like, did you feel like you had a scientific home among people?

00:45:11.130 --> 00:45:16.800
Or were you sort of feeling like uh you didn't have anywhere to to present this work.

00:45:17.920 --> 00:45:23.920
Well, uh initially the the the uh the work uh that I

00:45:23.920 --> 00:45:29.600
presented on on hunting, you know, was pretty straightforward uh and uh presented at the

00:45:29.600 --> 00:45:32.160
American Anthropological Association meetings.

00:45:32.480 --> 00:45:37.520
Uh but there was a change going on uh as I was uh

00:45:38.150 --> 00:45:43.830
early in my career where you know science and science is science was was less appreciated.

00:45:44.070 --> 00:45:49.990
Uh and it became a point where science became the enemy of any good uh

00:45:50.310 --> 00:45:51.270
researcher.

00:45:51.670 --> 00:45:57.510
Uh and so initially um no problem uh presenting papers,

00:45:57.590 --> 00:46:01.990
but then of course I got interested in the Evolution Behavior Uh Society.

00:46:02.470 --> 00:46:08.000
Uh and it was a better home for some of the things that I wanted to do because people are a

00:46:08.000 --> 00:46:09.680
lot more interested in it.

00:46:10.080 --> 00:46:15.920
Uh one thing that was uh disheartening about the American Anthropological Association

00:46:15.920 --> 00:46:21.760
was that uh you go to a meeting, there are literally hundreds of sessions, there are

00:46:21.760 --> 00:46:26.960
10,000 anthropologists there, uh, and you're looking through the uh program

00:46:27.280 --> 00:46:33.190
guide, and you can't find anything that you really want to listen

00:46:33.190 --> 00:46:33.510
to.

00:46:34.070 --> 00:46:38.870
It's like the uh Bruce Springsteen song 57 Channels and Nothing On.

00:46:39.270 --> 00:46:44.870
It's like, why am I going to this meeting if I'm gonna only go to two or three sessions?

00:46:45.030 --> 00:46:50.740
So later on, uh the Evolutionary Anthology Society was developed and

00:46:51.220 --> 00:46:53.380
and I started participating in that.

00:46:53.460 --> 00:46:54.580
That was better.

00:46:55.220 --> 00:47:00.500
But to go to a national meeting and only want to go to six sessions,

00:47:00.660 --> 00:47:04.500
maybe, uh, you know, good cost benefit proposition.

00:47:04.660 --> 00:47:10.420
So I I tried to, you know, I was became the president for a couple years, uh,

00:47:10.740 --> 00:47:15.810
and uh I just kind of like gave up on going.

00:47:15.890 --> 00:47:21.810
So I haven't been to an anthropology meeting since about maybe 2015

00:47:22.690 --> 00:47:23.890
or something like that.

00:47:23.970 --> 00:47:29.970
And again, it was like, you know, uh nothing to listen to, and then

00:47:29.970 --> 00:47:35.500
kind of like a basic hostility to one science, uh and then two

00:47:35.580 --> 00:47:41.500
especially evolutionary science and so uh it wasn't a good place

00:47:41.500 --> 00:47:47.020
to network and to make connections to be effectively

00:47:47.020 --> 00:47:51.500
criticized in terms of you know your approach you know you know why don't you look at it

00:47:51.500 --> 00:47:57.180
this way as opposed to a condemnation you know what the hell are you um doing

00:47:57.340 --> 00:47:59.730
practicing science etc Right.

00:47:59.890 --> 00:48:03.010
So it was just such a broad, you know, it wasn't even helpful criticism.

00:48:03.090 --> 00:48:08.130
It was just sort of like just leave as opposed to like, you know, do something, do analyze

00:48:08.130 --> 00:48:08.930
the data a different way.

00:48:09.010 --> 00:48:10.370
Or have you thought about this question?

00:48:10.530 --> 00:48:11.170
Yeah.

00:48:12.370 --> 00:48:12.770
Yeah.

00:48:12.930 --> 00:48:18.930
So uh uh the uh evolution of human behavior meetings were, you know, much uh more

00:48:19.170 --> 00:48:23.010
more useful because you could get good feedback.

00:48:23.580 --> 00:48:25.500
And you know, the evolutionary psych.

00:48:25.900 --> 00:48:30.860
I remember one time gave a paper at at uh at Michigan.

00:48:31.020 --> 00:48:34.700
Uh, I think Monique Berghoff Mulder invited me.

00:48:34.860 --> 00:48:40.140
And then after the meeting, talking to Randy Nessie, they keeps asking me all these

00:48:40.140 --> 00:48:41.740
psychological questions.

00:48:41.980 --> 00:48:47.850
And I said, I said, if I were a psychologist, I would be, you know, trying to work

00:48:47.850 --> 00:48:48.970
on those questions.

00:48:49.450 --> 00:48:53.930
But you know, the real problem that I think a lot of evolutionary psychology psychologists

00:48:53.930 --> 00:48:59.770
don't realize is that trying to do what some of

00:48:59.770 --> 00:49:05.530
you do in terms of getting a bunch of you know students or or what

00:49:05.850 --> 00:49:11.500
a sample to answer a questionnaire is it just

00:49:11.500 --> 00:49:17.500
can't be done for a lot of populations because I remember I had uh

00:49:17.660 --> 00:49:23.660
someone from Creighton University who was a psychologist wanted me to translate

00:49:24.140 --> 00:49:30.140
a set of questions he had that he thought uh because he got some money we

00:49:30.140 --> 00:49:32.140
could investigate among the Yanamawa.

00:49:32.380 --> 00:49:35.340
And I had to tell him, I can't do the translation.

00:49:35.650 --> 00:49:38.050
It just makes no sense.

00:49:38.290 --> 00:49:42.690
And so a lot of what uh uh

00:49:43.330 --> 00:49:49.010
psychologists do is depends on a kind of set of

00:49:49.010 --> 00:49:55.010
assumptions about uh culture and psychology, you know,

00:49:55.170 --> 00:49:57.250
about like, do you feel depressed?

00:49:57.490 --> 00:50:02.540
Well that's a hard word to translate to the Yanamamo.

00:50:04.060 --> 00:50:05.980
You know, are you horny?

00:50:06.060 --> 00:50:12.060
That's easy to translate with the with the Yanamamo or the Aquana.

00:50:12.860 --> 00:50:17.900
So there are a lot of, you know, and then the idea of a lighter scale, you know, that's

00:50:17.900 --> 00:50:23.350
another kind of like, what the hell are you asking me, uh, anthropologist?

00:50:23.510 --> 00:50:25.910
You know, it it it's just so difficult.

00:50:26.470 --> 00:50:31.990
Um this is not to say it can't be done, uh, and I think it should be done.

00:50:32.150 --> 00:50:37.110
Uh, but um I think maybe Zach can help me.

00:50:37.510 --> 00:50:42.980
You know the research done by Stubbard Hox on the Hazza, where he did the

00:50:42.980 --> 00:50:48.820
translation and how it just didn't work out at all in terms of could you

00:50:48.820 --> 00:50:54.500
recall that that that paper I was yeah they're looking at if so a lot of times research

00:50:54.500 --> 00:50:59.220
might be done in uh a third language or a common language, like let's say you can use

00:50:59.220 --> 00:51:04.020
Spanish and among let's say you're working with some Yaquana or for example, or you can use

00:51:04.020 --> 00:51:07.090
Swahili, um, but it's the participant's second language.

00:51:07.250 --> 00:51:12.290
And as it turns out, that sort of intermediary language can be a big have a big influence

00:51:12.290 --> 00:51:14.690
on the ways per people respond.

00:51:14.770 --> 00:51:17.970
And I mean that makes sense for everyone who speaks a second language, even if you're

00:51:17.970 --> 00:51:21.730
fluent in that language, it kind of patterns your your thinking in a way or your behavior.

00:51:21.810 --> 00:51:27.090
And so that's yeah, language is really a even if you can translate the concepts, the the

00:51:27.090 --> 00:51:32.850
language through which you translate them has like a a filtering effect or adds some noise.

00:51:33.920 --> 00:51:34.320
Right.

00:51:34.480 --> 00:51:40.400
And I I would uh uh maybe you could post that paper uh somewhere uh uh on this podcast.

00:51:40.560 --> 00:51:43.200
Uh but uh it's it's a really important paper.

00:51:43.360 --> 00:51:49.360
And it also, you know, when we talk about things we might ask people, there's

00:51:49.360 --> 00:51:51.760
a tremendous amount of cultural conditioning.

00:51:52.000 --> 00:51:56.160
So people thoroughly understand what you're talking about.

00:51:56.320 --> 00:52:01.680
But to try and figure out how to translate it to another culture is just enormously

00:52:01.920 --> 00:52:02.240
difficult.

00:52:02.720 --> 00:52:03.410
Yeah, Yeah.

00:52:03.570 --> 00:52:07.010
And I think that's one of the values, right, of us talking to anthropologists.

00:52:07.090 --> 00:52:10.130
And I think like also developmental psychologists deal with this too, right?

00:52:10.210 --> 00:52:15.810
Is you can't rely on this sort of the water that all the fish are swimming in, just the the

00:52:15.810 --> 00:52:17.970
collection of common sense assumptions.

00:52:18.290 --> 00:52:19.650
And to really see that.

00:52:19.730 --> 00:52:25.570
I mean, I, you know, I love talking to Zach and all of all of you anthropologists, just

00:52:25.570 --> 00:52:28.210
because it does keep us honest in terms of our assumptions.

00:52:28.370 --> 00:52:28.690
Yeah.

00:52:29.120 --> 00:52:31.920
Well, now I just want to do a research project on horniness.

00:52:36.240 --> 00:52:40.320
Well, uh, I know all the words in Yatomal that relate to

00:52:42.800 --> 00:52:47.120
you know this also is an interesting point that as an anthropologist, you have to have your

00:52:47.120 --> 00:52:48.960
rapport with the community, right?

00:52:49.040 --> 00:52:53.120
And then you have to kind of be strategic about certain questions you asked because it's it

00:52:53.120 --> 00:52:56.560
can potentially kind of burn your your social capital with your community.

00:52:56.870 --> 00:53:00.390
so there might be some topic that could be very interesting to ask scientifically, some

00:53:00.390 --> 00:53:05.910
questions, but like, God, do I want to actually ask that question to people who are, you

00:53:05.910 --> 00:53:08.630
know, in my social world in this community?

00:53:08.950 --> 00:53:10.790
Like they think you're already weird enough.

00:53:10.950 --> 00:53:13.990
You know, you can't come in asking about certain there's just certain things, not that it's

00:53:13.990 --> 00:53:18.950
culturally taboo, but it's just gonna make you seem even weirder and like a like a psycho

00:53:19.030 --> 00:53:20.230
than you already are.

00:53:20.740 --> 00:53:23.540
Yeah, I I I've I've that's a great point.

00:53:23.700 --> 00:53:27.780
Uh because you know you're you're you're with an intimate group and could you imagine let's

00:53:27.940 --> 00:53:31.940
uh say you have a group of people you hang out with and you start asking them about their

00:53:31.940 --> 00:53:36.740
sexual behavior, they're gonna be going like, you know, what the hell is he trying to you

00:53:36.740 --> 00:53:40.660
know pourn in on what I've, you know, blah blah blah, et cetera.

00:53:40.740 --> 00:53:42.820
So yeah, you're you're absolutely right.

00:53:44.090 --> 00:53:49.370
Um, Ray, you have a really cool paper on you know the myth of the ecologically noble

00:53:49.370 --> 00:53:53.770
savage, where you've you know taught and you've talked a lot about you know representations

00:53:53.770 --> 00:53:54.570
of indigenous people.

00:53:54.650 --> 00:53:58.330
And I'm just wondering like it doesn't seem like we've really made much progress in the

00:53:58.330 --> 00:53:59.690
past 20 years about that.

00:53:59.850 --> 00:54:05.530
Maybe the rise of social media also gives people like more of a voice, and so we have more,

00:54:05.770 --> 00:54:11.290
let's say, less than charitable or ignorant perspectives talking about indigenous

00:54:11.290 --> 00:54:11.930
peoples.

00:54:12.170 --> 00:54:14.600
I don't know, just where do you think we are as a field?

00:54:14.680 --> 00:54:17.880
And like what should anthropologists or scientists be doing?

00:54:17.960 --> 00:54:23.800
And um where do you see like the representation of indigenous peoples today

00:54:23.800 --> 00:54:24.840
as to where they were?

00:54:24.920 --> 00:54:29.080
You know, I think that paper was in the 90s or early 2000s when you wrote that paper.

00:54:29.320 --> 00:54:29.960
So I don't know.

00:54:30.040 --> 00:54:31.640
I mean, it doesn't seem like we've made much progress.

00:54:31.800 --> 00:54:34.280
Do you have any hope for well?

00:54:34.360 --> 00:54:39.000
I I think we've made a a bit of progress, but but here's the the catch.

00:54:39.480 --> 00:54:45.030
Uh Tribal populations have been oppressed, marginalized,

00:54:45.270 --> 00:54:47.750
and harmed in so many ways.

00:54:48.390 --> 00:54:54.150
And so the tendency is to essentially argue that these are really

00:54:54.150 --> 00:54:55.030
nice people.

00:54:55.750 --> 00:55:01.510
And a lot of the problems that they face are a consequence of colonial incursions,

00:55:01.670 --> 00:55:06.040
which, you know, is is right on in many, many respects.

00:55:06.280 --> 00:55:12.200
And so to suggest that they are not stewards of the environment, or the other

00:55:12.200 --> 00:55:18.200
issue uh related to this is how much warfare or violence do they engage in, how often do

00:55:18.200 --> 00:55:20.920
they uh uh beat their wives, etc.

00:55:21.480 --> 00:55:27.000
Uh so if you point those things out uh that we regard as

00:55:27.000 --> 00:55:32.830
reprehensible from our cultural perspective, and so and I'll leave it

00:55:32.990 --> 00:55:38.990
I'll I won't leave it I'll emphasize from our cultural perspective uh

00:55:39.230 --> 00:55:44.990
then you essentially tell others who may not care about native

00:55:45.150 --> 00:55:50.910
peoples that these people aren't worth saving helping etc etc we got this

00:55:50.910 --> 00:55:56.670
reaction from cultural survival how dare you suggest the Yanamam are warlike because

00:55:56.990 --> 00:56:02.840
we can't get donors to help them out if they believe that they are warlike

00:56:03.000 --> 00:56:06.120
because you know, screw them, they're not worth saving.

00:56:06.280 --> 00:56:10.200
Uh, may they kill each other off, you know, or something of that nature.

00:56:10.440 --> 00:56:16.280
And so uh the degree to which we want to help Native

00:56:16.280 --> 00:56:22.120
peoples depends on how much they measure up to values that we

00:56:22.120 --> 00:56:24.040
hold very, very highly.

00:56:24.200 --> 00:56:28.870
So there's a huge hypocrisy there uh going on.

00:56:29.030 --> 00:56:34.070
And you know, I think one should just essentially say, well that's true, but let's help

00:56:34.070 --> 00:56:35.430
them because they're terribly oppressed.

00:56:35.590 --> 00:56:40.870
They have uh like what you're doing in in in terms of of of health among the people you're

00:56:40.870 --> 00:56:45.270
working with, Ethiopia, uh, you know, let's do what we can to help out.

00:56:45.430 --> 00:56:51.040
So uh so we still have this

00:56:51.280 --> 00:56:57.200
Rousseauian view that still dominates uh how people regard native

00:56:57.200 --> 00:56:57.920
peoples.

00:56:58.080 --> 00:57:03.920
Uh and it's you know much more complex than that in terms of uh you know, uh

00:57:04.080 --> 00:57:09.440
humans used to be nice until things got modern, you know, until we discovered

00:57:09.440 --> 00:57:14.730
warfare, until we discovered effective technology to take

00:57:14.730 --> 00:57:15.610
resources.

00:57:16.330 --> 00:57:22.330
And so, you know, and you can't go back.

00:57:23.530 --> 00:57:28.890
And if you do go back, you found out that they were just like us, uh,

00:57:29.050 --> 00:57:34.440
self-serving, uh, short-sighted, uh, no care for the environment.

00:57:34.520 --> 00:57:36.520
Well care a concern for the environment.

00:57:36.840 --> 00:57:42.200
In fact, I'll I'll I'll I've taken a little bit of a of a change on on

00:57:42.200 --> 00:57:43.160
conservation.

00:57:43.320 --> 00:57:49.080
There's some really good evidence for the Pacific that conservation does occur

00:57:49.080 --> 00:57:50.440
among resources.

00:57:50.840 --> 00:57:56.680
And essentially it has to do with the regulation that chiefs make

00:57:56.840 --> 00:58:02.610
in terms of uh can fish where, in what seasons, et cetera,

00:58:02.690 --> 00:58:03.490
et cetera.

00:58:03.650 --> 00:58:09.570
Uh, but you know, these are very hierarchical sorts of systems, uh, and

00:58:09.570 --> 00:58:14.530
where there's some real punishment uh for people who who break the rules.

00:58:14.770 --> 00:58:20.690
And so one could say that uh we have examples, uh at least in the

00:58:20.690 --> 00:58:25.570
Pacific, uh, where there were really good and effective

00:58:25.570 --> 00:58:29.000
conservation uh methods employed.

00:58:29.240 --> 00:58:31.320
And you know, you wonder about the Pacific.

00:58:31.400 --> 00:58:33.480
Well, you know, you live in an island.

00:58:33.800 --> 00:58:39.480
Uh, you can't move away if you screw up your resources, and so the populations

00:58:39.800 --> 00:58:45.800
that uh manage to persist have ways of conserving resources

00:58:45.800 --> 00:58:51.470
by regulating uh the uh the exploitation of those resources.

00:58:51.710 --> 00:58:57.310
These systems have been destroyed largely because uh

00:58:57.630 --> 00:59:03.070
entrepreneurs on those islands didn't want any restrictions put on their

00:59:03.390 --> 00:59:09.230
uh uh catches so they could make more money and uh so you

00:59:09.230 --> 00:59:15.140
had these rare systems of effective conservation that essentially

00:59:15.140 --> 00:59:20.900
were were wrecked uh by self-serving uh individuals who were, you know,

00:59:21.300 --> 00:59:26.740
uh one thing to look at is that these systems can work if the

00:59:26.740 --> 00:59:28.260
demand is local.

00:59:28.500 --> 00:59:33.780
That is, you're just trying to supply, but when you make the demand international, then

00:59:33.780 --> 00:59:39.220
there's no check on what uh uh what exploitation can

00:59:39.220 --> 00:59:39.860
occur.

00:59:40.630 --> 00:59:41.510
That's really interesting.

00:59:41.670 --> 00:59:41.830
Yeah.

00:59:41.910 --> 00:59:44.390
That's a really interesting distinction, local versus international.

00:59:44.470 --> 00:59:44.630
Yeah.

00:59:44.950 --> 00:59:49.190
I mean, these stories that you're telling us from the Anamama are just so uh vivid and

00:59:49.190 --> 00:59:49.910
wonderful.

00:59:50.070 --> 00:59:56.070
Um I'm curious if you think there are any um puzzles in the field of

00:59:56.070 --> 01:00:01.510
evolutionary behavioral science that you think still remain unsolved, or what you think is

01:00:01.510 --> 01:00:04.950
the is the future of the field and where what directions we should be headed.

01:00:05.740 --> 01:00:08.540
Well, uh how cooperation works.

01:00:08.700 --> 01:00:14.540
Uh, you know, we have models of uh of kin selection, we have models of uh

01:00:14.540 --> 01:00:16.220
reciprocal altruism.

01:00:16.780 --> 01:00:22.300
Uh one thing that uh really impressed me and I don't know if it impressed other people is

01:00:22.300 --> 01:00:27.610
some of the work done by uh Kaplan and and and Mike Gervin

01:00:28.010 --> 01:00:33.930
in terms of intergenerational transfers of resources and

01:00:33.930 --> 01:00:39.930
how cooperation, you know, we tend to think of it as you know, mature adults, dyadic sorts

01:00:39.930 --> 01:00:44.890
of relationships, but you see this kind of horizontal pattern, uh, excuse me, vertical

01:00:44.890 --> 01:00:50.650
pattern going on, where actually, and I'd love to test this, uh, it looks

01:00:50.650 --> 01:00:55.660
like young couples beginning their

01:00:56.620 --> 01:01:02.220
family lives often can't produce enough food that they need to

01:01:02.220 --> 01:01:02.860
consume.

01:01:03.660 --> 01:01:09.180
And so that requires a kind of vertical transmission from older

01:01:09.180 --> 01:01:14.940
relatives, not necessarily grandmas, as Chris and Hawkes would have it, but

01:01:14.940 --> 01:01:20.590
from others and uh how that works to me is, you know, as an

01:01:20.590 --> 01:01:23.150
economic anthropologist, is really, really interesting.

01:01:23.230 --> 01:01:28.270
And it's something that is, I think, uh really unique about humans.

01:01:28.350 --> 01:01:33.710
Although we see it, for example, in like killer whales, and how the mother-killer whale,

01:01:33.870 --> 01:01:39.580
the grandmother, seems to have this wonderful knowledge about where resources are

01:01:39.740 --> 01:01:43.340
in good times and bad times and also hunting techniques.

01:01:43.500 --> 01:01:49.500
And so I think this kind of vertical generation interaction is

01:01:49.500 --> 01:01:55.500
a really important area of research that uh that we uh to uh

01:01:55.500 --> 01:01:56.380
take a look at.

01:01:56.540 --> 01:02:01.900
And part of it, you know, is stimulated early on by Kristen Hawk's work on the grandmother

01:02:01.900 --> 01:02:03.100
uh hypothesis.

01:02:03.340 --> 01:02:09.230
Although I like that an awful lot, it's kind of like overextended uh in

01:02:09.230 --> 01:02:15.150
terms of her suggesting that men are just showing off uh and are mate guarding and are

01:02:15.150 --> 01:02:20.750
not really concerned about their own kids, uh only about their reputations as big hunters

01:02:20.830 --> 01:02:22.750
uh or big time hunters.

01:02:22.910 --> 01:02:28.830
Uh but so that I think is is is to me, you know, personally,

01:02:29.150 --> 01:02:34.830
uh understanding those dynamics because it kind of we see these patterns in other animals

01:02:34.910 --> 01:02:40.820
too, whereas this kind of like uh intergenerational transfer of uh

01:02:41.140 --> 01:02:45.060
of goods and services are actually you know cooperation.

01:02:47.700 --> 01:02:48.020
Yeah.

01:02:48.260 --> 01:02:53.860
And you know, uh especially considering that in Western societies we seem to be so

01:02:53.860 --> 01:02:59.380
severed from uh our extended families, and the extent of grandparental

01:02:59.380 --> 01:03:04.090
investment is so low because our culture is changing so quickly, and the knowledge that our

01:03:04.090 --> 01:03:06.890
grandparents has accumulated is currently out of date.

01:03:07.050 --> 01:03:12.010
You know, our elders have never been more irrelevant than in any time in human history,

01:03:12.250 --> 01:03:16.490
because what they know and what they know how to do is no longer relevant to the future to

01:03:16.490 --> 01:03:20.650
the to the most current generation because because you know society and technology is

01:03:20.650 --> 01:03:25.370
changing so quickly and what was useful in the previous generation may not be useful to the

01:03:25.370 --> 01:03:31.120
present generation, which is diametrically opposite to what you see uh in hunter-gatherer

01:03:31.120 --> 01:03:37.120
societies or in uh forager societies, uh where uh uh elders are repositories of

01:03:37.200 --> 01:03:41.360
of wisdom and knowledge and and they're and they have a con and they're revered for for

01:03:41.360 --> 01:03:42.560
that for that knowledge.

01:03:42.640 --> 01:03:47.520
Uh and it's hard for us to wrap our heads around that from a Western uh standpoint.

01:03:47.600 --> 01:03:51.600
And and how we I mean I I guess another outstanding question will be how we have gotten to

01:03:51.600 --> 01:03:57.350
this place where we are are are so um disconnected from uh

01:03:57.510 --> 01:04:03.430
familial and kin sources of cooperation and so dependent on non-kin cooperation relative

01:04:03.430 --> 01:04:06.950
to at any other point uh in human evolutionary history.

01:04:07.430 --> 01:04:08.870
Yeah, I think you're absolutely right.

01:04:08.950 --> 01:04:14.870
And you know the th the the gist of the problem is that uh older people are costs.

01:04:15.110 --> 01:04:15.430
Yep.

01:04:15.590 --> 01:04:21.420
Uh because we have inadequate uh health care, especially in this country.

01:04:21.580 --> 01:04:23.020
And so what good are they?

01:04:23.100 --> 01:04:27.740
Except, you know, uh we've got to uh uh spend our money.

01:04:27.900 --> 01:04:33.660
Uh there's some interesting research uh like uh from Germany, where it turns out that uh

01:04:33.820 --> 01:04:39.660
uh grandmothers, especially uh living on pensions, allocate a large

01:04:39.660 --> 01:04:45.340
fraction of their income to their grandchildren, and so they're still trying to

01:04:46.220 --> 01:04:47.100
help out.

01:04:47.410 --> 01:04:49.250
So you're you're absolutely right.

01:04:50.050 --> 01:04:51.890
So what are the value of older people?

01:04:52.050 --> 01:04:57.330
Because back in the day, well, they had a lot of knowledge about uh resource distributions

01:04:57.330 --> 01:05:01.890
and how to adapt to uh environmental contingencies.

01:05:02.210 --> 01:05:08.130
But today uh the whole making a living situation is

01:05:08.130 --> 01:05:13.730
new to them just as it's you know uh new to you and so they have um

01:05:15.580 --> 01:05:21.340
I hate to be cynical, you know, but you know, the the reasons that back in the day

01:05:21.420 --> 01:05:25.900
perhaps one could argue, and I'll just make this argument maybe it's not i inaccurate, they

01:05:25.900 --> 01:05:27.020
were valuable.

01:05:27.660 --> 01:05:29.660
They were fonts of knowledge.

01:05:29.820 --> 01:05:32.380
Uh they were good to have around.

01:05:32.620 --> 01:05:38.390
Uh and in fact, you know, I I gave uh Mike Gervin's got a new book coming

01:05:38.390 --> 01:05:40.950
out uh on uh old people.

01:05:41.190 --> 01:05:41.990
Was it 70?

01:05:42.070 --> 01:05:43.590
I think I forget what it's called.

01:05:43.750 --> 01:05:49.750
But but I sent him a picture of this old, old Yanomamo uh shaman,

01:05:49.830 --> 01:05:55.670
Dedahewa, being groomed by a bunch of little girls to another photograph to

01:05:55.670 --> 01:06:01.480
show you how valued old people were uh in societies and so i don't

01:06:01.640 --> 01:06:06.840
i i gave him two four deman was this guy who an old guy who knew how to make really potent

01:06:06.840 --> 01:06:12.600
curare uh and he would make the curare and give it to everybody he no longer

01:06:12.600 --> 01:06:18.440
hunted but you know he was really really valuable uh to the to the local

01:06:18.440 --> 01:06:23.640
groups so uh the problem i see uh is that

01:06:23.880 --> 01:06:29.690
older people are viewed as costs and not

01:06:29.690 --> 01:06:35.050
viewed as uh as benefits to uh to have around, um,

01:06:35.370 --> 01:06:38.490
especially as people are scattered all over the place.

01:06:38.810 --> 01:06:42.090
You know, uh, who's gonna help you out on date night?

01:06:42.250 --> 01:06:47.130
You know, uh grandma's not around, or grandpa's not around.

01:06:47.210 --> 01:06:52.520
So I think uh as you're pointed out, we're we're entering a really kind of

01:06:52.840 --> 01:06:54.440
interesting time.

01:06:55.240 --> 01:07:00.840
Uh, but I think uh as I mentioned before, I think that if there were

01:07:01.720 --> 01:07:07.320
I'd like to you could do a comparative study perhaps, uh, where we have like uh

01:07:07.640 --> 01:07:13.230
universal health care, our grandparents or elderly kin

01:07:13.470 --> 01:07:19.390
more valued and loved compared to our own nation where uh you've got to

01:07:19.390 --> 01:07:20.190
help out.

01:07:21.870 --> 01:07:22.190
Yeah.

01:07:22.430 --> 01:07:26.830
That our attitudes toward the elders would would depend on the costs and benefits that

01:07:26.830 --> 01:07:28.190
they're associated with.

01:07:28.270 --> 01:07:33.630
And if those costs are uh taken care of by someone else, then maybe we might view them as

01:07:33.630 --> 01:07:35.470
more of a net benefit for us.

01:07:36.080 --> 01:07:36.560
Exactly.

01:07:36.640 --> 01:07:39.360
I mean, that's a harsh way of looking at humanity.

01:07:40.080 --> 01:07:45.360
But I think the test implications are pretty obvious.

01:07:45.840 --> 01:07:49.760
It might be harsher to ignore that implication of humanity too, right?

01:07:50.400 --> 01:07:50.640
Yeah.

01:07:50.800 --> 01:07:53.280
Well, I'm sensitive because you know I'm an old person.

01:07:53.520 --> 01:07:55.840
I'm 77 years of age.

01:07:56.080 --> 01:08:00.400
But fortunately, uh we have you know adequate savings, et cetera, et cetera.

01:08:00.480 --> 01:08:06.270
Uh, and we still want to see our grandkids and and uh always believed that, you know, it

01:08:06.430 --> 01:08:07.950
push came to shove.

01:08:08.590 --> 01:08:14.510
Yeah, thankfully thankfully, you know, we're we're in a a subculture, you know, uh

01:08:14.590 --> 01:08:20.350
a group of scientists where elders still are, you know, repositories of of knowledge and

01:08:20.350 --> 01:08:25.070
you do have a lot of valuable knowledge, you know, for us uh as as scientists, you know,

01:08:25.150 --> 01:08:27.550
based on all the experiences you've accumulated.

01:08:27.710 --> 01:08:30.190
Um and so thankfully you're at least still valuable to us.

01:08:30.590 --> 01:08:31.710
I don't know about your grandkids.

01:08:31.950 --> 01:08:36.760
Yeah, but I just had a eighteen hundred dollar chest x-ray.

01:08:38.280 --> 01:08:42.120
That uh uh blue crosses were sh anyway.

01:08:42.360 --> 01:08:43.240
Yeah, it's terrible.

01:08:43.400 --> 01:08:43.560
Yeah.

01:08:43.800 --> 01:08:48.280
I I just as like I lived in Germany for nine, ten years, and people on post Facebook would

01:08:48.280 --> 01:08:52.120
be like, Oh, we there we did this GoFundMe to like, you know, prevent like these poor

01:08:52.120 --> 01:08:56.690
people who have like there's a childhood child with leukemia, and we did a go fund me so

01:08:56.690 --> 01:08:57.490
they wouldn't lose their house.

01:08:57.570 --> 01:08:59.490
And all the all the Americans are like, that's great.

01:08:59.570 --> 01:09:01.730
And all the Europeans are like, that's horrible.

01:09:10.530 --> 01:09:10.850
Yeah.

01:09:11.090 --> 01:09:16.130
Well w one of the mysteries that I often get asked about from an evolutionary perspective

01:09:16.450 --> 01:09:18.450
is um homosexuality.

01:09:18.610 --> 01:09:22.690
Uh I know you've done uh a bit of research on this question, and that to me I think is

01:09:22.690 --> 01:09:26.820
still one of the one of the major outstanding mysteries in evolutionary behavioral sciences

01:09:26.900 --> 01:09:31.860
is how how we can understand this uh phenomenon uh from a Darwinian perspective.

01:09:32.020 --> 01:09:36.100
Uh and I'm curious what you know what you think about that question, how you've approached

01:09:36.100 --> 01:09:40.020
it, and whether you uh have any insights on it, or whether you think there are certain

01:09:40.020 --> 01:09:42.740
directions that are more promising uh than others.

01:09:43.620 --> 01:09:48.340
Well, Zach can answer that question too, because he helped uh affect my my thinking on the

01:09:48.420 --> 01:09:49.700
uh on the topic.

01:09:49.860 --> 01:09:55.550
Uh I think, you know, uh back in the day, everyone was expected to marry and have

01:09:55.550 --> 01:09:56.190
kids.

01:09:56.510 --> 01:10:02.430
And so I would say that in many cultures, homosexuality was no big deal, as long as you

01:10:02.430 --> 01:10:07.870
could, you know, uh have your uh sexual desire satisfied uh by a

01:10:07.870 --> 01:10:09.470
same-sex relationship.

01:10:09.630 --> 01:10:15.160
Uh what's really interesting is that uh if you look at the work of Lisa Dynam,

01:10:15.480 --> 01:10:21.160
uh women are much more uh flexible, uh, much more likely to engage in

01:10:21.160 --> 01:10:23.880
intimate relationships uh than men.

01:10:24.040 --> 01:10:29.880
And part of it is culture, but also I think that uh the selection pressure

01:10:29.880 --> 01:10:35.720
for women to be in heterosexual relationships

01:10:36.150 --> 01:10:41.910
was much weaker because back in the day, you're gonna get married, girl, and you're gonna

01:10:41.910 --> 01:10:45.350
have kids, and there was no two ways about it.

01:10:45.750 --> 01:10:51.110
Uh, and so there wasn't, I'm thinking, I'm

01:10:51.350 --> 01:10:57.350
hypothesizing this point, a kind of uh uh having a a

01:10:57.350 --> 01:11:02.880
strength of you know, a strong heterosexual relationship in women that was

01:11:02.880 --> 01:11:07.840
relaxed because they were going to be heterosexual in the practical dimensions of it in

01:11:07.840 --> 01:11:09.120
terms of having kids.

01:11:09.280 --> 01:11:11.040
So yeah, be fluid.

01:11:11.200 --> 01:11:14.560
No, no, no, no kind of problem uh at all.

01:11:14.720 --> 01:11:20.480
And then also uh for men, uh heterosexuality is you know

01:11:20.640 --> 01:11:23.920
having kids is really important in every culture.

01:11:25.410 --> 01:11:31.250
And so I think what I want

01:11:31.250 --> 01:11:37.170
to say is that we seem to find it everywhere, that is homosexuality everywhere.

01:11:37.810 --> 01:11:43.410
And to me, it's not too surprising that the

01:11:43.970 --> 01:11:48.930
uh mechanism, psychological mechanisms that lead to

01:11:48.930 --> 01:11:54.400
heterosexuality, they can be weak as long as the culture, or they can be weaker as long as

01:11:54.400 --> 01:12:00.160
the culture demands that in order to achieve uh high social status

01:12:00.240 --> 01:12:06.000
or reasonable social status, uh, is to engage in some heterosexuality that engages

01:12:06.080 --> 01:12:08.080
that leads to uh to reproduction.

01:12:08.880 --> 01:12:13.680
It's an interesting irony that it seems like the idea there is that um

01:12:14.000 --> 01:12:19.990
heteropatriarchal norms ironically led to the evolution of homosexuality,

01:12:20.070 --> 01:12:24.390
or at least it led to the relaxed selection pressures on heterosexuality.

01:12:24.470 --> 01:12:30.230
Because when you have such strong social norms that you have to have kids, um, that relaxes

01:12:30.230 --> 01:12:36.150
the selection pressure uh for um you know uh being exclusively heterosexual in

01:12:36.150 --> 01:12:38.790
terms of your your uh desires and your orientation.

01:12:38.870 --> 01:12:42.790
Because if you're if you're gonna have kids anyway, then it you know, your your actual

01:12:42.790 --> 01:12:47.240
desires are free to be a little more off that beaten path.

01:12:47.320 --> 01:12:47.720
Yeah.

01:12:48.040 --> 01:12:48.360
Right.

01:12:48.440 --> 01:12:51.720
I I I think that's a it's it's a really good way of uh putting it.

01:12:51.960 --> 01:12:57.640
What's interesting is that if we look at Western societies, uh two to three percent of

01:12:57.640 --> 01:13:01.400
males seem to engage in be heterosexual, excuse me, homosexual.

01:13:01.800 --> 01:13:04.360
And that kind of low-up is kind of interesting.

01:13:04.520 --> 01:13:08.550
We keep finding that figure, you know all over the place.

01:13:08.870 --> 01:13:14.230
Uh and uh I'm not quite exactly sure what it means but it's it's uh

01:13:14.630 --> 01:13:15.990
it's really interesting.

01:13:16.070 --> 01:13:21.510
But I think yeah patriarchy is something that uh has

01:13:21.510 --> 01:13:27.430
allowed uh homosexuality or bisexuality whatever to

01:13:27.430 --> 01:13:33.160
uh to emerge Now, at the same time,

01:13:33.560 --> 01:13:38.760
a de-emphasis on fertility also may be having the sort of same effect.

01:13:40.120 --> 01:13:42.200
How so could you elaborate on that?

01:13:43.080 --> 01:13:44.120
What was I thinking?

01:13:44.200 --> 01:13:49.960
Uh in terms of if it's if the expectation is that

01:13:49.960 --> 01:13:55.570
you don't need to have kids to achieve social status,

01:13:56.130 --> 01:14:02.050
then your sexuality is free to vary in terms of what your your

01:14:02.050 --> 01:14:03.890
inclinations may be.

01:14:06.930 --> 01:14:07.570
Interesting.

01:14:07.810 --> 01:14:08.690
Does that make sense?

01:14:08.850 --> 01:14:09.810
Maybe not.

01:14:12.690 --> 01:14:15.380
Um yeah, I think so.

01:14:15.540 --> 01:14:16.500
I mean, i it's interesting.

01:14:16.580 --> 01:14:22.580
At least in the contemporary US, social norms surrounding having kids and having

01:14:22.660 --> 01:14:27.700
uh a large family and devoting resources into family and child rearing, that tends to go

01:14:27.700 --> 01:14:32.980
along with uh homophobia or anti uh homosexual attitudes.

01:14:33.380 --> 01:14:38.740
And so at least in the US, uh kind of uh preference for uh monogamy,

01:14:39.170 --> 01:14:44.370
uh intensive parental investment, you know, having lots of kids and being uh against

01:14:44.370 --> 01:14:49.730
homosexuality, those things those things uh go together um statistically.

01:14:49.890 --> 01:14:53.970
Um and so that that's an interesting um phenomenon.

01:14:54.050 --> 01:15:00.050
Uh I I'm not sure if if there are analogs in other places or how you would understand that.

01:15:01.060 --> 01:15:03.460
I I guess I can add a little bit to this.

01:15:03.780 --> 01:15:08.980
What Ray and I did and what what this work involved was also going through the ethnographic

01:15:08.980 --> 01:15:14.340
record to sort of document all the forms in which um you know same-sex

01:15:14.340 --> 01:15:16.900
behavior was documented to have taken.

01:15:17.140 --> 01:15:20.820
And you know, just like kinship systems where basically humans have invented every

01:15:20.820 --> 01:15:25.270
possible, seemingly probably not all, but maybe most of the possible ways we could organize

01:15:25.270 --> 01:15:30.230
ourselves in terms of kinship, we also organize ourselves along these varied dimensions in

01:15:30.230 --> 01:15:31.430
regards of gender.

01:15:31.670 --> 01:15:37.030
And this sort of third gender or multigender system is quite common across societies.

01:15:37.110 --> 01:15:40.870
So we also kind of bring our Western perspective to say, you know, what is homosexuality,

01:15:41.030 --> 01:15:42.630
what is heterosexuality?

01:15:42.790 --> 01:15:48.140
And part of this work was trying to unpack that using more biologically and the sex

01:15:48.140 --> 01:15:53.020
research oriented terms, trying to disentangle behavior and preference.

01:15:53.260 --> 01:15:57.740
And as it turns out, you know, you have many different societies with multiple gender

01:15:57.740 --> 01:16:01.180
categories, not just a binary gender category.

01:16:01.420 --> 01:16:07.180
And in those contexts, let's say a male, a biological male who identifies as

01:16:07.180 --> 01:16:12.930
a man, may have sex or engage in sex with a biological male who identifies as a third

01:16:13.010 --> 01:16:16.770
gender or even a fourth or a fifth gender categories in some contexts.

01:16:17.090 --> 01:16:22.370
And then neither of them are seen as a anormal or

01:16:22.370 --> 01:16:28.370
atypical, or would be considered engaging in homosexual relationships because it's

01:16:28.370 --> 01:16:34.240
still a pattern of sex that's socially acceptable given their gendered categories.

01:16:34.400 --> 01:16:38.880
But there's a wide range of gendered categories and you know social rules about who engages

01:16:38.880 --> 01:16:42.240
in sex based on what gendered category you're a part of.

01:16:42.400 --> 01:16:47.680
And the families kind of identify individuals at a young age and sort of socialize them

01:16:47.680 --> 01:16:50.240
into these different different gender categories.

01:16:50.480 --> 01:16:56.080
Um so it's uh it's the full spectrum of human variation uh in this

01:16:56.080 --> 01:17:00.320
intersection of gender and sex is as mind blowing.

01:17:00.640 --> 01:17:06.230
Well the Yeah, the the uh one one element is that typically

01:17:06.390 --> 01:17:12.310
the uh uh those third, fourth genders, uh

01:17:12.390 --> 01:17:15.510
they don't have high social status most of the time.

01:17:15.910 --> 01:17:19.430
Uh they're regarded uh as as somewhat inferior.

01:17:19.670 --> 01:17:25.350
But as you all probably know, uh my friend and colleague Paul Vase has done the best

01:17:25.350 --> 01:17:29.110
research uh on this sort of phenomena.

01:17:29.700 --> 01:17:34.980
And you know, the the his classic work on the uh uh Samoans, the

01:17:34.980 --> 01:17:40.900
Fafine, uh essentially uh it's a culture where they recognize

01:17:40.900 --> 01:17:46.740
it and they don't discriminate against it, and they say, okay, well, that's the way

01:17:46.740 --> 01:17:50.900
he is, uh, and they have these legitimate relationships.

01:17:51.060 --> 01:17:56.990
Um he doesn't talk a lot about status in terms, but they uh clearly

01:17:57.070 --> 01:18:03.070
you know don't have as high a status but still they're they're accepted it's like you know

01:18:03.310 --> 01:18:09.310
that's the way uh uh that person is and they just kind of leave it at

01:18:09.310 --> 01:18:15.230
that but he's uh has done some really interesting research both in Mexico and

01:18:15.230 --> 01:18:21.230
Samoa and now in Southeast Asia uh on how it works out in these societies where

01:18:21.230 --> 01:18:26.980
it's they're recognized uh as quote a legitimate s kind of

01:18:27.300 --> 01:18:28.980
orientation to hell.

01:18:29.540 --> 01:18:35.300
Do you think uh there is a a explanation or a theoretical approach

01:18:35.620 --> 01:18:41.300
to um you know sexual orientation, uh uh uh gender

01:18:41.300 --> 01:18:42.020
atypicality?

01:18:42.100 --> 01:18:46.420
Do you think there is a theoretical approach that that can offer a good explanation for

01:18:46.420 --> 01:18:48.660
these phenomena from an evolutionary perspective?

01:18:48.900 --> 01:18:54.110
Or do you think there there is you know one set of ideas that is more promising than

01:18:54.110 --> 01:18:59.870
another uh well you know the the thing that probably uh

01:19:00.830 --> 01:19:06.590
frustrates us all is that how can a behavior that leads to

01:19:06.590 --> 01:19:12.510
zero fitness persist in a population generation after generation that's

01:19:12.510 --> 01:19:18.110
the the rub yeah and also it's kind of interesting that it seems to be two to

01:19:18.190 --> 01:19:23.520
three percent of any population and we overgeneralizing here.

01:19:24.240 --> 01:19:29.280
And so um there are

01:19:30.240 --> 01:19:35.680
some ideas about, you know, um the it was the the

01:19:35.680 --> 01:19:41.440
sexually antagonistic uh theory by some Italian researchers that somehow the

01:19:41.600 --> 01:19:47.550
the women uh are uh uh of or or excuse me the the the the the

01:19:47.550 --> 01:19:53.550
sibl females are the uh female siblings of these homosexual males have

01:19:53.550 --> 01:19:59.150
higher fertility and somehow I don't know what and and there's been some research that

01:19:59.150 --> 01:20:03.870
shows that it's not the case et cetera et cetera there's also you know a weird thing it may

01:20:03.870 --> 01:20:08.500
be a totally a side effect Ray Blancher's birth order uh model.

01:20:09.220 --> 01:20:15.220
That the more uh older brothers you have, the higher

01:20:15.220 --> 01:20:19.220
the probability that you are going to be uh homosexual.

01:20:19.460 --> 01:20:25.380
So it has to do with andronization of the womb and how that has an

01:20:25.380 --> 01:20:27.780
effect on sexual orientation.

01:20:27.940 --> 01:20:33.010
So to me, that is the most promising

01:20:33.330 --> 01:20:33.970
area.

01:20:34.450 --> 01:20:40.370
And what it is kind of a you know essentially a side effect, a systematic

01:20:40.370 --> 01:20:40.930
side effect.

01:20:41.010 --> 01:20:46.610
It's not selected for, uh, but it just occurs as this

01:20:46.610 --> 01:20:51.090
process goes on, uh, as you have more and more boys.

01:20:51.330 --> 01:20:55.730
Are you familiar with the uh uh uh Ray Blanchard's theory, that area?

01:20:56.160 --> 01:20:57.760
Yeah, uh roughly familiar.

01:20:57.840 --> 01:21:03.760
Yeah, the idea that the more male siblings you have, the more likely a male

01:21:03.760 --> 01:21:09.680
homosexuality is to arise because of the uh something about the androgens

01:21:09.680 --> 01:21:11.200
and the immune response.

01:21:11.680 --> 01:21:11.840
Right.

01:21:12.080 --> 01:21:12.560
Yeah.

01:21:13.520 --> 01:21:19.490
But what's really interesting is that it looks like it's very dosage dependent because the

01:21:19.490 --> 01:21:25.330
probability increases stepwise with each number of older brothers you have, which to me

01:21:25.410 --> 01:21:30.610
is really powerful indirect evidence that something is going on there to

01:21:31.170 --> 01:21:33.250
have this uh occur.

01:21:33.570 --> 01:21:34.050
Yeah.

01:21:34.370 --> 01:21:38.370
Yeah, that I that that seems probably the most promising direction, especially especially

01:21:38.370 --> 01:21:41.650
when you look at you know the the twin studies regarding homosexuality.

01:21:41.810 --> 01:21:46.460
It seems to be relatively low uh genetic heritability, which suggests that the prenatal

01:21:46.460 --> 01:21:50.540
environment might be um the the driving factor.

01:21:51.100 --> 01:21:51.420
Right.

01:21:51.580 --> 01:21:57.260
And for uh you know the uh the uh uh diamond's idea about uh uh

01:21:57.420 --> 01:22:02.380
female fluidity uh maybe as we mentioned before explained by

01:22:02.380 --> 01:22:03.500
patriarchy.

01:22:03.980 --> 01:22:05.330
Yeah absolutely.

01:22:05.490 --> 01:22:08.210
Well still still I think a lot of different mechanisms.

01:22:08.530 --> 01:22:09.970
Yeah, very different mechanisms.

01:22:10.210 --> 01:22:15.250
I think it's still, you know, probably a you know really mysterious and interesting uh area

01:22:15.250 --> 01:22:19.250
of research that I think we still we we know so little about it.

01:22:19.490 --> 01:22:23.090
Um yeah, do you guys have any other questions?

01:22:23.650 --> 01:22:28.290
Uh just uh remember like the Don Simon's Evolution of Human Sexuality was such a great book

01:22:28.370 --> 01:22:34.300
where it talked about sort of using uh male and female homosexuality as a window into

01:22:34.300 --> 01:22:39.580
like mating preferences because it's not um hindered by having to coordinate with opposite

01:22:39.580 --> 01:22:45.420
sex and that that that thought just I wanted to ask, right, if there's anything if

01:22:45.500 --> 01:22:49.820
if people who are listening who are sort of newer generation evolutionary behavioral

01:22:49.820 --> 01:22:55.180
sciences scientists, um where there might be sort of classic books like I think the

01:22:55.180 --> 01:23:00.730
evolution of human sexuality is one, I think the um evolutionary ecology, the Smith and

01:23:00.730 --> 01:23:05.530
Winter Halder, I think you have a time allocation paper that I think it's 92,

01:23:06.570 --> 01:23:08.570
Evolutionary Ecology and Human Behavior.

01:23:08.650 --> 01:23:10.410
That's also like a great classic book.

01:23:10.570 --> 01:23:16.010
Are there any sort of uh things that a new student might miss

01:23:16.970 --> 01:23:21.930
that would be sort of a real thing to either read or like go look at if it's up on YouTube

01:23:22.090 --> 01:23:22.570
or something?

01:23:22.650 --> 01:23:27.140
You know, is there something that you would recommend to people that they might miss if

01:23:27.140 --> 01:23:28.740
they're just starting out now.

01:23:29.380 --> 01:23:35.380
Oh, well, uh you brought up Don Simons uh and uh I was uh I

01:23:35.380 --> 01:23:40.820
don't know how many copies I uh or versions I've read of the evolution of human sexuality,

01:23:40.900 --> 01:23:41.860
but it was many.

01:23:42.180 --> 01:23:47.300
In fact, I even translated some French stuff for him on Aceh uh Hunters.

01:23:47.860 --> 01:23:53.780
Uh and uh but Don got it so right in terms of uh

01:23:55.170 --> 01:24:01.010
male homosexuals are just like male heterosexuals except for the object

01:24:01.010 --> 01:24:02.050
of their desire.

01:24:02.610 --> 01:24:07.010
But you know, otherwise they're they're they're stereotypic males.

01:24:07.330 --> 01:24:12.050
Uh and that was a really uh important uh uh insight.

01:24:12.370 --> 01:24:18.290
Uh that uh so that book definitely uh is and the wonderful thing about that book,

01:24:18.450 --> 01:24:20.130
it's really well written.

01:24:20.440 --> 01:24:23.000
He's got a very terse style.

01:24:23.240 --> 01:24:26.520
In fact, almost sometimes too terse.

01:24:27.320 --> 01:24:33.240
But I remember going through version after version, and he was such a

01:24:33.240 --> 01:24:34.760
meticulous writer.

01:24:35.000 --> 01:24:38.600
He really wanted to be economical and to the point.

01:24:38.840 --> 01:24:44.770
And so I think it's a wonderful introduction to the field just because of its

01:24:44.770 --> 01:24:45.890
readability.

01:24:46.130 --> 01:24:46.370
Yeah.

01:24:46.690 --> 01:24:52.690
Uh what uh to me, the most important thing I ever read was

01:24:52.690 --> 01:24:58.610
a paper by Richard Alexander uh called the uh evolution of of sociality,

01:24:58.690 --> 01:25:01.650
I forget in the annual review of ecology and systematics.

01:25:01.970 --> 01:25:07.650
And as a young scholar, it really you know answered a question, you know, like

01:25:07.890 --> 01:25:09.810
why do humans live in groups?

01:25:10.080 --> 01:25:12.960
Well, Dick had an explanation for that.

01:25:14.000 --> 01:25:19.360
And so, and that steps you into you know the whole field of social organization.

01:25:19.520 --> 01:25:20.960
We're a social species.

01:25:21.200 --> 01:25:26.240
And it was like uh it was a revelation uh to to me.

01:25:26.400 --> 01:25:31.120
And also uh Dick was a very good mentor.

01:25:31.520 --> 01:25:36.490
Uh and his uh what's his book, The Evolution of morality.

01:25:37.370 --> 01:25:39.610
Yeah, the biology of moral systems.

01:25:40.170 --> 01:25:40.250
Yeah.

01:25:40.490 --> 01:25:44.250
Biology of moral systems is something I would recommend to anybody.

01:25:44.810 --> 01:25:47.610
He didn't have the writing skill of a Don Simon.

01:25:47.930 --> 01:25:52.250
But still, it's it was one of the most important books.

01:25:52.410 --> 01:25:58.010
So I've it was kind of like, you know, I I had I was a Santa Barbarian, like you are, you

01:25:58.010 --> 01:26:03.280
know, and so I had Don Simons on one side, and then I had Richard Alexander on the other

01:26:03.280 --> 01:26:03.520
side.

01:26:03.600 --> 01:26:09.440
So I kind of, you know, had an appreciation for both points of view, uh,

01:26:10.560 --> 01:26:16.080
even though I was much more of a behavioral ecologist like uh Dick Alexander

01:26:16.400 --> 01:26:20.640
was, but still uh appreciated uh Don's uh Don's work.

01:26:20.950 --> 01:26:22.790
Yeah, by by some sequence of events.

01:26:22.870 --> 01:26:28.070
I mean, I know what they are, but uh so I was a graduate student when Don was retiring, and

01:26:28.070 --> 01:26:33.750
I went to his office uh to get some of his books, and one of my most cherished uh science

01:26:33.750 --> 01:26:39.590
artifacts is I have Don Simon's copy of Richard Alexander's Biology of

01:26:39.590 --> 01:26:43.430
Moral Systems, and it's barked up in the margins all over.

01:26:43.760 --> 01:26:49.520
And I can I can read about 90% of the markup, and it's incredible because Don is so

01:26:49.520 --> 01:26:51.520
gracious to him.

01:26:51.840 --> 01:26:57.680
But there's times where Don is marking, oh yeah, no, this is like kind of baby

01:26:57.680 --> 01:26:58.160
counting.

01:26:58.320 --> 01:26:59.840
I mean, he doesn't use exactly that word.

01:26:59.920 --> 01:27:04.400
Maybe he does a few times because it's just notes to himself, but it's real time sort of

01:27:04.720 --> 01:27:10.560
Don's thinking about Richard Alexander is incredible, wonderful, but here is where

01:27:10.800 --> 01:27:16.250
this sort of assumption of sort of omnipresent or omniscient fitness

01:27:16.250 --> 01:27:17.850
maximizing doesn't work.

01:27:18.010 --> 01:27:22.250
It's an incredible uh thing to read those those m notes in the margins.

01:27:22.730 --> 01:27:23.130
Oh well.

01:27:23.370 --> 01:27:24.810
I'm I'm envious that you have that.

01:27:25.450 --> 01:27:26.490
Maybe scan it.

01:27:26.810 --> 01:27:27.930
No, that'd be great.

01:27:28.490 --> 01:27:34.330
The the the only uh physical re rem uh uh artifact I have from Don Simons

01:27:34.490 --> 01:27:40.250
was was um uh as he was writing the evolution of human sexuality, his

01:27:40.250 --> 01:27:41.770
tenure was on the line.

01:27:42.640 --> 01:27:45.920
Uh and we were gonna play tennis.

01:27:46.160 --> 01:27:49.360
And one day he said, he gave me his tennis racket.

01:27:49.600 --> 01:27:51.600
He says, I can't play tennis.

01:27:51.680 --> 01:27:53.040
I've got to work on this book.

01:27:53.120 --> 01:27:54.320
I only have time to run.

01:27:54.640 --> 01:27:58.560
And so he gave me this uh this head racket with a red throat.

01:27:58.640 --> 01:28:03.040
I don't know if you play tennis, you'd know that's an old kind of uh uh aluminum uh racket.

01:28:03.280 --> 01:28:07.760
But then of course I broke the racket eventually after about a couple of years.

01:28:08.720 --> 01:28:09.310
Oh, Don?

01:28:11.550 --> 01:28:12.750
He was a great guy.

01:28:12.990 --> 01:28:13.230
Yeah.

01:28:13.390 --> 01:28:14.030
How did Don?

01:28:14.350 --> 01:28:20.110
I mean, my I understood John Shuby once told me that I think uh Sherry Washburn was at

01:28:20.110 --> 01:28:24.910
Berkeley and didn't like that Don was doing evolution applied to humans, and that's why Don

01:28:24.910 --> 01:28:26.510
ended up at UCSB.

01:28:26.670 --> 01:28:27.950
Do you know that story?

01:28:28.350 --> 01:28:33.790
Well, I know that Washburn didn't like uh uh modern evolutionary approaches, especially to

01:28:33.790 --> 01:28:35.070
human behavior.

01:28:35.360 --> 01:28:39.920
Uh and was Washburn on his thesis committee?

01:28:40.560 --> 01:28:41.200
I don't know.

01:28:41.760 --> 01:28:45.520
I mean, this is all sort of becoming fuzzy in my mind because this is something John told

01:28:45.520 --> 01:28:49.520
me, John Thuby told me just like you know, interpersonally.

01:28:49.840 --> 01:28:55.360
Um, so it wasn't something, but I thought Simons had been

01:28:55.920 --> 01:28:58.720
somehow either a student of, I'm not sure.

01:28:58.800 --> 01:28:59.600
I actually don't know.

01:28:59.760 --> 01:29:04.160
This is something I'm fuzzy on about Sherry Washburn and Don Simons and the relationship.

01:29:04.570 --> 01:29:07.290
So they had a what kind of relationship?

01:29:07.850 --> 01:29:13.610
Well, I I don't know if I don't know if Don was a faculty uh and then sort of was trying to

01:29:13.610 --> 01:29:19.370
get tenure and was a colleague of Sherry Washburn, or um if he was more junior and worked

01:29:19.370 --> 01:29:25.050
with Sherry Washburn and then Washburn was uh uh a senior

01:29:25.050 --> 01:29:26.410
anthropologist Berkeley.

01:29:26.650 --> 01:29:27.050
Right.

01:29:27.290 --> 01:29:33.080
And he was, you know, uh uh one of the things that was the uh so and

01:29:33.320 --> 01:29:39.160
he was very, you know, if you look at Washburn and Lancaster, uh man the hunter kind

01:29:39.160 --> 01:29:44.760
of kind of approach, he did kind of take a an evolutionary approach where he suggested that

01:29:44.760 --> 01:29:50.280
hunting was a thing that made us humans, uh, which in fact hunting made us

01:29:50.280 --> 01:29:50.840
interesting.

01:29:50.920 --> 01:29:56.350
Uh but I don't know that it made us humans any more than uh grandmothers made us uh humans.

01:29:56.510 --> 01:29:56.670
Right.

01:29:56.910 --> 01:30:02.910
Uh but uh but then he kind of uh I'm trying to recall I probably can't get it

01:30:02.910 --> 01:30:08.590
right so I won't say it but he wasn't very in favor of modern

01:30:08.750 --> 01:30:14.270
approaches or or Eil Wilson kind of approaches to the to understanding human behavior.

01:30:14.510 --> 01:30:16.990
But Don got his degree at Berkeley, right?

01:30:17.230 --> 01:30:17.550
Right.

01:30:17.790 --> 01:30:18.830
Yeah exactly.

01:30:19.070 --> 01:30:22.990
And he did his thesis on Reese's monkeys, Reese's play.

01:30:23.200 --> 01:30:24.320
Yeah, that's right.

01:30:24.480 --> 01:30:25.920
Done in uh Kayo.

01:30:26.080 --> 01:30:26.720
Yeah.

01:30:27.760 --> 01:30:28.400
Yeah.

01:30:29.120 --> 01:30:32.880
Well, uh is there anything we should have asked you, Ray?

01:30:34.480 --> 01:30:36.720
I don't think so, but you're absolutely right.

01:30:37.040 --> 01:30:39.440
An hour and a half went by really uh rapidly.

01:30:39.600 --> 01:30:39.760
Yeah.

01:30:40.640 --> 01:30:46.320
Over uh an hour and a half because you guys are really engaging uh and ask a lot of really

01:30:46.320 --> 01:30:48.400
uh interesting uh questions.

01:30:49.350 --> 01:30:53.750
I would say, you know, you started asking questions about uh Darkness in El Dorado.

01:30:54.310 --> 01:30:59.990
And uh if my view is essentially a point of view that uh Alice

01:30:59.990 --> 01:31:04.150
Trager wrote and her characterization that went on there.

01:31:04.310 --> 01:31:06.470
Uh one thing that was really interesting.

01:31:06.950 --> 01:31:11.270
So in my view, it was a kind of a hit job.

01:31:11.760 --> 01:31:14.160
and I don't know who paid for the hit.

01:31:14.400 --> 01:31:20.320
Uh, but uh Tierney published the book, showed up

01:31:20.320 --> 01:31:26.240
at an early meeting of the American Anthropological Association, and then disappeared

01:31:26.240 --> 01:31:28.160
off the face of the earth.

01:31:28.480 --> 01:31:34.480
So he could never be questioned about why he took

01:31:34.480 --> 01:31:39.130
various views, But you know, there was a whole

01:31:40.250 --> 01:31:44.650
group of people who really didn't like Shagla.

01:31:45.210 --> 01:31:50.970
And part of it had to do with his evolutionary approaches to human

01:31:50.970 --> 01:31:51.690
behavior.

01:31:51.930 --> 01:31:57.840
The other part had to do with his demonstration that some uh

01:31:58.160 --> 01:32:04.160
foraging horticultural people were really aggressive, engaged in a lot of warfare,

01:32:04.480 --> 01:32:10.480
and regarded it as, you know, uh uh a really manly thing to do if you were

01:32:10.480 --> 01:32:16.400
in that culture, which, if they had bothered or read anything about Native American warlike

01:32:16.400 --> 01:32:20.400
cultures, they wouldn't have been surprised what Shagnon found out about the about the

01:32:20.400 --> 01:32:21.120
Alamamos.

01:32:21.280 --> 01:32:27.030
So I think uh that book was, I would call it uh

01:32:27.590 --> 01:32:29.110
a hit jump.

01:32:29.590 --> 01:32:35.030
Uh, and that essentially tyranny pulled together all the people who didn't like

01:32:35.030 --> 01:32:39.750
Shagna and who did not like him for, I think,

01:32:40.390 --> 01:32:42.310
illegitimate reasons.

01:32:42.470 --> 01:32:45.750
Uh and so you have that uh that book.

01:32:45.990 --> 01:32:51.820
Interestingly, the last I heard about Tierney was that he was in

01:32:51.820 --> 01:32:56.060
conversation with Wakefield about publishing someone.

01:32:56.300 --> 01:33:02.300
I'm talking about the Wakefield who argued that uh vaccines were causing autism

01:33:02.940 --> 01:33:04.380
among among kids.

01:33:04.700 --> 01:33:07.580
Wow, that's like a circle of hell right there.

01:33:07.740 --> 01:33:08.220
Yeah.

01:33:08.620 --> 01:33:08.780
Yeah.

01:33:08.940 --> 01:33:13.740
Well, he's got a famous brother, John Tierney, who who's a uh a journalist, right?

01:33:13.900 --> 01:33:16.610
Uh, who does pretty good uh research.

01:33:16.930 --> 01:33:19.730
Uh he publishes a lot in the city journal, but anyway.

01:33:19.890 --> 01:33:25.810
So anyway, uh I I thought when I first read it,

01:33:25.970 --> 01:33:31.890
I got this uh autocopy of the book that Kim Hill had sent me,

01:33:32.290 --> 01:33:38.260
and I read it and for days I was I

01:33:38.260 --> 01:33:43.220
was in a daze because I just couldn't believe and here you're here's something I'd worked

01:33:43.220 --> 01:33:48.820
with and it just uh the the

01:33:48.820 --> 01:33:54.660
depressing psychological impact and stressful it had on me was was was

01:33:54.660 --> 01:34:00.330
amazing but can you imagine what it the impact it had on Chad Yeah.

01:34:01.050 --> 01:34:05.450
In terms of you know what it did for his uh his well-being.

01:34:05.610 --> 01:34:09.610
Yeah it's just uh uh incredible.

01:34:09.850 --> 01:34:15.850
But I think now that most people realize that it was a hit job

01:34:16.090 --> 01:34:20.540
uh and uh much of what was said was was inaccurate.

01:34:20.700 --> 01:34:22.300
Shagna wasn't perfect.

01:34:22.620 --> 01:34:24.380
None of us are perfect.

01:34:25.180 --> 01:34:31.180
But still none of us have been kind of like celebrated

01:34:31.180 --> 01:34:35.100
as a horrible person in front of the the whole world.

01:34:35.260 --> 01:34:40.540
And so just try to think of what what impact it would have on you

01:34:41.020 --> 01:34:46.010
if you were the subject of that sort of uh of uh phenomena.

01:34:46.330 --> 01:34:46.890
Yeah, yeah.

01:34:46.970 --> 01:34:51.930
As I think John Tuby once put it, it's like very few people get falsely accused of sort of

01:34:51.930 --> 01:34:53.610
genocide, essentially.

01:34:53.770 --> 01:34:58.970
Uh and just even the prima facie case of, you know, a measles epidemic with vaccines like

01:34:59.130 --> 01:34:59.850
just doesn't work.

01:35:00.010 --> 01:35:04.010
And so the fact that it had any footing at all is just incredible.

01:35:04.170 --> 01:35:09.210
Um, you know, and it's just yeah, it's a terrible, terrible travesty of sort of fact

01:35:09.290 --> 01:35:11.690
checking and scientific literacy.

01:35:11.850 --> 01:35:12.170
Yeah.

01:35:12.700 --> 01:35:17.020
Well, one thing I'll say one last thing about that is that uh

01:35:18.300 --> 01:35:23.420
James Neal and Napoleon Chagnon should have been awarded a

01:35:23.420 --> 01:35:29.100
humanitarian prize by the American Anthropological Association because

01:35:29.340 --> 01:35:35.260
Neil and his research uh discovered that the Yanamama were a virgin

01:35:35.260 --> 01:35:37.900
soil as in terms of measles.

01:35:38.700 --> 01:35:44.510
He got the measles vaccine uh into Venezuela uh

01:35:44.670 --> 01:35:50.510
in anticipation of, excuse me, with plans to vaccinate, discovered

01:35:50.510 --> 01:35:56.030
that uh a measles epidemic had had uh broken out.

01:35:56.190 --> 01:36:01.630
And so it was Shagnon and the evangelical uh missionaries, Protestant

01:36:01.630 --> 01:36:07.540
missionaries, who decided to vaccinate from the outside in, which is the way you deal

01:36:07.540 --> 01:36:08.660
with with epidemics.

01:36:08.740 --> 01:36:11.780
You don't go from the inside out, you go from the outside in.

01:36:12.020 --> 01:36:17.620
And without their efforts, thousands of Yanomamal would have perished.

01:36:18.180 --> 01:36:22.020
But instead, the story became positive epidemic.

01:36:22.260 --> 01:36:22.900
Yeah, yeah.

01:36:22.980 --> 01:36:23.860
It's incredible.

01:36:24.020 --> 01:36:24.340
Yeah.

01:36:24.420 --> 01:36:27.700
It's unfortunately, uh the that's the yeah.

01:36:27.780 --> 01:36:32.710
I mean, hopefully history, you know, if the historical record is corrected, but hopefully

01:36:32.790 --> 01:36:35.670
that story will be told well.

01:36:36.070 --> 01:36:40.470
Anyone who makes a movie, uh, there should be a movie about Nap Shagnon.

01:36:40.550 --> 01:36:43.670
I I think that that's a low-hanging fruit right there.

01:36:44.470 --> 01:36:46.870
Uh well, there may be.

01:36:47.750 --> 01:36:49.830
I know his son was recording things.

01:36:49.990 --> 01:36:52.870
Uh, I don't know what what became of that footage, but there should be at least a

01:36:52.870 --> 01:36:55.590
documentary, if not a movie, about Nap Shagnon.

01:36:55.820 --> 01:36:57.820
David, get on that with your LA folks.

01:36:58.140 --> 01:36:59.500
All right, I'll I'll look into it.

01:37:00.940 --> 01:37:02.780
Well, this is really fun.

01:37:02.940 --> 01:37:08.860
Ray, uh, thank you so much for uh the the hour and a half and also for for all

01:37:08.860 --> 01:37:12.060
the years and for for being present during all those times.

01:37:12.220 --> 01:37:17.100
Your work is, you know, why many of us are here, either directly or indirectly, certainly

01:37:17.100 --> 01:37:18.140
directly for Zach.

01:37:18.300 --> 01:37:21.690
Um uh, You know, I'll let him speak for himself on the way out here or two.

01:37:21.930 --> 01:37:27.690
But just thank you so much for all the work that you've done and continue to do and inspire

01:37:27.930 --> 01:37:33.450
people to do this fun, weird um career of applying evolution to human

01:37:33.450 --> 01:37:34.250
behavior.

01:37:35.050 --> 01:37:39.770
Well, uh at the same time, I'm really uh impressed by this this new generation of

01:37:41.100 --> 01:37:47.100
evolutionary scientists in terms of your uh statistical skills which we were l uh largely

01:37:47.100 --> 01:37:53.100
uh lacking in terms of your ability to uh uh create interesting uh

01:37:53.100 --> 01:37:59.100
hypotheses to to test and find ways of testing them and uh so i

01:37:59.100 --> 01:38:04.540
think uh you guys have become the you know cutting edge now of of uh

01:38:17.770 --> 01:38:18.970
Yeah, thanks so much, Ray.

01:38:19.050 --> 01:38:20.010
It's great to talk to you.

01:38:20.090 --> 01:38:24.970
And um yeah, you know, it's just serendipitous that my introduction to anthropology

01:38:24.970 --> 01:38:27.050
happened to be in your your lecture hall.

01:38:27.130 --> 01:38:30.570
And um I guess I'll close with one one funny story.

01:38:30.730 --> 01:38:34.100
You know, Ray has such a commanding presence in the classroom.

01:38:34.180 --> 01:38:39.060
He's obviously a super nice guy, really collegial, but in the classroom he takes it very

01:38:39.060 --> 01:38:39.860
seriously.

01:38:40.020 --> 01:38:44.180
And I remember it was my first time back to the university in this huge lecture hall.

01:38:44.340 --> 01:38:47.780
And you're talking about the Yanamamo and these ethnographies we're going to read.

01:38:47.860 --> 01:38:51.620
And I think it was one of the first or second lectures and you know you you have a nice,

01:38:51.780 --> 01:38:52.580
very commanding presence.

01:38:52.660 --> 01:38:57.630
And then up in the back row there was this kid one day reading a newspaper and you just

01:38:57.630 --> 01:39:02.830
like stopped your lecture mid-sentence and said something to the effect of like, You can do

01:39:02.830 --> 01:39:06.830
that elsewhere, you better put that away right now or leave the room.

01:39:06.990 --> 01:39:12.910
And it was the whole 300 students just instantly got silent and all the attention

01:39:12.910 --> 01:39:14.270
came right back to the lecture.

01:39:14.510 --> 01:39:19.710
And then years later, like five years later, I was meeting a friend of my brother's and he

01:39:19.710 --> 01:39:22.110
introduced himself to me and said, You might remember me.

01:39:22.270 --> 01:39:25.160
You remember Ray Haymes' class in culture anthropology?

01:39:25.320 --> 01:39:27.160
He called out that guy reading the newspaper?

01:39:27.320 --> 01:39:28.040
That was me.

01:39:30.520 --> 01:39:31.160
Really?

01:39:31.880 --> 01:39:32.120
Yeah.

01:39:32.280 --> 01:39:37.240
So, I mean, you were legendary on the on the campus of University of Nebraska for bringing

01:39:37.240 --> 01:39:39.720
these stories of the Yanamomo and ethnography.

01:39:39.800 --> 01:39:43.960
And there's a whole uh group and generation of us that came from Nebraska that wouldn't

01:39:43.960 --> 01:39:48.330
have any idea about evolutionary social science had it not been for your your presence

01:39:48.330 --> 01:39:48.490
there.

01:39:48.650 --> 01:39:53.610
So thank you for your service to Nebraska and and this is and our communities more

01:39:53.930 --> 01:39:54.730
broadly.

01:39:55.450 --> 01:39:59.210
Well, thank you very much and uh interesting uh story.

01:39:59.450 --> 01:40:02.330
Uh it was effective.

01:40:02.410 --> 01:40:03.050
It was an effective.

01:40:03.130 --> 01:40:05.130
I I'll try it in my own teaching someday.

01:40:05.530 --> 01:40:07.450
Did anything have did the person elaborate?

01:40:07.530 --> 01:40:11.180
Did they say sort of, you know, I was all of a sudden after that day, I sort of woke up

01:40:11.180 --> 01:40:12.620
earlier, worked harder and that kind of thing.

01:40:12.860 --> 01:40:14.940
Yeah, it just scared him, scared him straight, you know.

01:40:15.100 --> 01:40:15.580
No more.

01:40:17.740 --> 01:40:17.980
Yep.

01:40:18.220 --> 01:40:19.020
He paid attention.

01:40:19.420 --> 01:40:22.140
My view back then was that I don't take rule.

01:40:23.180 --> 01:40:28.060
So, you know, don't ask uh I gotta answer this phone.

01:40:28.300 --> 01:40:31.180
But uh so read your newspaper in the lobby.

01:40:33.970 --> 01:40:34.690
Thanks, Rick.

01:40:35.250 --> 01:40:35.490
All right.

01:40:35.570 --> 01:40:35.730
Great.

01:40:35.890 --> 01:40:36.770
It was a pleasure.

01:40:36.930 --> 01:40:37.890
Uh take care.

01:40:38.130 --> 01:40:38.690
Bye.

01:40:42.850 --> 01:40:46.050
Well, you're still here listening, which means that you must like what you're hearing.

01:40:46.210 --> 01:40:48.690
So what can people do if they like what they're hearing, Dave?

01:40:49.010 --> 01:40:51.330
They can uh leave a good review.

01:40:51.490 --> 01:40:57.490
They can share it with uh this episode with somebody on social media, or

01:40:57.570 --> 01:41:03.380
um the old fashioned way of looking over at them through the um sky or

01:41:03.380 --> 01:41:09.300
air, the ground walking around, um, you know, using their voice, not sitting on

01:41:09.300 --> 01:41:14.100
a screen and saying, Hey, look at this thing, which is also on the computer.

01:41:14.180 --> 01:41:16.180
So I guess, you know, whatever, it's all on the computer.

01:41:16.500 --> 01:41:16.740
Yeah.

01:41:16.820 --> 01:41:22.340
I mean I mean sending vibrations through the air by vibrating our vocal cords.

01:41:22.580 --> 01:41:23.620
Uh, you know, that's it.

01:41:23.780 --> 01:41:25.380
Yeah, if you're reductive about it, that's true.

01:41:25.460 --> 01:41:26.820
It's all weird when you're when you're reducing.

01:41:27.140 --> 01:41:31.140
I mean, that's that's the OG social media is just l literal vibes.

01:41:31.550 --> 01:41:36.990
Can I just say that the uh Good Vibrations by The Beach Boys is an excellent, excellent

01:41:36.990 --> 01:41:37.230
song.

01:41:37.310 --> 01:41:42.830
Brian Wilson really just turned as they say, he turned the uh the recording studio into an

01:41:42.830 --> 01:41:43.230
instrument.

01:41:43.390 --> 01:41:46.750
So uh if you haven't listened to Good Vibrations in a while, you should check it out.

01:41:47.150 --> 01:41:51.870
It's a great album and please send some good vibes our way, kind reviews, check us out on

01:41:51.870 --> 01:41:52.510
Patreon.

01:41:52.670 --> 01:41:54.350
Uh we we love to hear all of it.

01:41:54.510 --> 01:41:56.510
So uh we'll see you next week.

01:41:56.750 --> 01:41:57.310
Fantastic.

01:41:57.470 --> 01:41:58.990
Listen to some good music today.

01:41:59.120 --> 01:41:59.600
Yeah.