WEBVTT 00:00:00.240 --> 00:00:02.800 This is Evolutionary Psychology the Podcast. 00:00:03.120 --> 00:00:08.080 Actual Evolutionary Psychology by Actual Evolutionary Psychologists. 00:00:23.040 --> 00:00:25.440 David, today we are talking to Chris Smith. 00:00:25.920 --> 00:00:27.200 Chris Smith with a K. 00:00:28.080 --> 00:00:28.960 That's right. 00:00:29.270 --> 00:00:32.710 Um, and we had a really fun conversation with Chris. 00:00:32.870 --> 00:00:38.870 Uh we talked all about uh his fieldwork with both uh the Hadza 00:00:39.350 --> 00:00:42.550 and another another community he was working with with and and Pizer. 00:00:42.950 --> 00:00:44.150 We spoke to our previous episode. 00:00:44.630 --> 00:00:50.520 Both are in Tanzania um yes, and I don't I I couldn't pr pronounce 00:00:50.520 --> 00:00:50.920 correctly. 00:00:51.080 --> 00:00:53.560 You'll have to listen to the episode to hear the correct pronunciation. 00:00:53.960 --> 00:00:55.960 That's a nice incentive for you to listen. 00:00:56.280 --> 00:01:00.120 Uh so that you can get the the name of of this uh fishing community. 00:01:00.360 --> 00:01:05.400 But yeah, we talked about partner choice, cooperation, um norms, 00:01:06.200 --> 00:01:12.170 the uh the methodological difficulties of doing anthropological field work, the 00:01:12.170 --> 00:01:13.850 collision of theory with reality. 00:01:13.930 --> 00:01:14.970 It was a really fun conversation. 00:01:15.130 --> 00:01:17.130 Did I did I miss anything there, Dave? 00:01:17.450 --> 00:01:22.970 Uh mosquitoes and um I think mosquitoes. 00:01:23.050 --> 00:01:24.410 Oh and climate change we talked about. 00:01:24.490 --> 00:01:28.170 Yeah how yeah how communities are adapting to climate change. 00:01:28.330 --> 00:01:30.810 Um yeah it was it was super fun and interesting. 00:01:31.100 --> 00:01:32.460 Chris is always a great hang. 00:01:32.860 --> 00:01:33.100 Yeah. 00:01:33.180 --> 00:01:38.140 And uh it's really nice to have uh anthropologists on and you uh thanked him for his 00:01:38.140 --> 00:01:40.380 service several times as is appropriate. 00:01:40.780 --> 00:01:41.260 That's true. 00:01:41.340 --> 00:01:44.460 And if you are an anthropologist listening, thank you for your service. 00:01:45.260 --> 00:01:46.540 Uh wonderful. 00:01:46.700 --> 00:01:52.140 So uh without further ado, here is Chris Smith, David and I talking about um what Chris has 00:01:52.140 --> 00:01:56.770 learned in the field and uh what it might mean for for all of us. 00:01:57.090 --> 00:01:58.370 Yep, enjoy. 00:02:00.850 --> 00:02:02.850 Chris, thank you for being here. 00:02:03.090 --> 00:02:04.210 How are you doing today? 00:02:04.690 --> 00:02:05.410 I'm doing great. 00:02:05.490 --> 00:02:06.370 Thank you for having me. 00:02:06.450 --> 00:02:09.010 Uh happy to chat with you all and uh yeah. 00:02:09.730 --> 00:02:10.450 All right, great. 00:02:10.610 --> 00:02:13.010 Um we just saw you in person at HBus. 00:02:13.250 --> 00:02:18.560 Um we were all talking before we started about um how some of us uh fell ill and some of us 00:02:18.560 --> 00:02:22.560 didn't and maybe we'll get to illness um in in later in the conversation. 00:02:22.880 --> 00:02:25.200 You do um field work. 00:02:25.920 --> 00:02:29.680 Um can you tell us a little bit about where you do your field work? 00:02:30.000 --> 00:02:33.280 I feel like we we had a long stretch of anthropologists on. 00:02:33.440 --> 00:02:38.910 We've lately had psychologists and we're we psychologists are boring folks because you know 00:02:39.070 --> 00:02:40.110 we don't do fieldwork. 00:02:40.190 --> 00:02:44.910 So can you tell us a little bit about where you have done or currently do field work? 00:02:45.070 --> 00:02:47.550 Um and maybe that'll start us off. 00:02:48.270 --> 00:02:51.870 And if not, you could just talk about the wonderful drawing behind you. 00:02:52.430 --> 00:02:52.830 Yeah. 00:02:52.990 --> 00:02:56.990 Uh well it's funny because I I straddle psychology and anthropology, right? 00:02:57.070 --> 00:02:57.870 Uh exactly. 00:02:57.950 --> 00:02:58.110 Yeah. 00:02:58.270 --> 00:02:59.070 I think of you, yes. 00:02:59.310 --> 00:03:05.300 I think of you um uh I I'm a psychologist, so I think it's great to be 00:03:05.300 --> 00:03:05.940 a psychologist. 00:03:06.020 --> 00:03:08.660 So for better or worse, I think of you as a psychologist too. 00:03:08.740 --> 00:03:09.940 So yes, exactly. 00:03:10.260 --> 00:03:12.980 Uh well, I try to tell my department I'm an anthropologist now. 00:03:13.140 --> 00:03:13.220 Okay. 00:03:13.300 --> 00:03:14.660 Uh well I said out. 00:03:15.460 --> 00:03:17.140 Well, I said two, so it's both. 00:03:17.220 --> 00:03:17.380 Yeah. 00:03:17.700 --> 00:03:18.020 Yeah. 00:03:18.260 --> 00:03:20.820 Um, so I work uh in East Africa. 00:03:20.980 --> 00:03:25.940 So I started working in 2016 in Tanzania, working with Hadza 00:03:26.020 --> 00:03:27.140 hunter-gatherers. 00:03:27.380 --> 00:03:33.190 Um, I moved towards the coast of Tanzania in 2021 on a more recent project 00:03:33.350 --> 00:03:37.270 working with uh fishermen and fishing villages along the coast of Tanzania. 00:03:37.590 --> 00:03:42.070 And most recently I started working in Kenya, collaborating with some veterinarians and 00:03:42.070 --> 00:03:47.190 epidemiologists, um, primarily in northern Kenya and Marsebit, working with uh 00:03:47.190 --> 00:03:49.350 pastoralists, so Gabra and Rendile. 00:03:49.910 --> 00:03:54.390 Um, so I've uh had a chance to really explore quite a bit of East Africa now over the 00:03:54.390 --> 00:03:54.710 years. 00:03:55.100 --> 00:03:55.340 Wow. 00:03:55.500 --> 00:04:01.180 And was are those locations especially for us psychologists, um, 00:04:01.340 --> 00:04:06.300 or those of us who don't do any of any of this, uh, how does one get a field site or how 00:04:06.300 --> 00:04:09.180 what's the how do you get there and then why do you go to a different one? 00:04:09.260 --> 00:04:10.540 Is it convenience? 00:04:10.700 --> 00:04:16.140 Is it that the question you're asking is well suited to being answered in in that place? 00:04:16.300 --> 00:04:18.860 Is it you know people, all the above? 00:04:19.410 --> 00:04:23.490 Yeah, so I think I think you'd like to say, well, it's you know, new research questions, 00:04:23.570 --> 00:04:27.410 and this was you know uh intentionally chosen for this reason. 00:04:27.650 --> 00:04:32.530 Uh I think the reality for many of us, including me, is that it's often sort of convenience 00:04:32.530 --> 00:04:33.570 and happenstance. 00:04:33.730 --> 00:04:39.490 So I started working with uh Hadza um because my one of my advisors, Kirin 00:04:39.570 --> 00:04:43.730 Apicella, she's an anthropologist in uh psychology at Penn. 00:04:43.890 --> 00:04:47.140 Um She worked with Hadza with her advisor, Frank Marlowe. 00:04:47.220 --> 00:04:51.300 And so at one point we were collaborating on a project and she sent me out there to start 00:04:51.300 --> 00:04:52.740 collecting data. 00:04:53.540 --> 00:04:58.340 And so, you know, the first field experience, there's there's some stories there, but 00:04:58.340 --> 00:05:03.380 started going back out and sort of building, you know, importantly, linguistic skills and 00:05:03.380 --> 00:05:07.700 sort of knowing how to navigate the country and its uh all its administrative and 00:05:07.700 --> 00:05:09.060 bureaucratic stuff. 00:05:09.300 --> 00:05:15.290 And so after um during COVID, uh my postdoc at Penn was running 00:05:15.290 --> 00:05:20.250 out, and this opportunity came up to work with Ann Paiser, who was at Washington State, is 00:05:20.410 --> 00:05:26.170 now at uh Penn State, uh, looking at between community cooperation um among 00:05:26.170 --> 00:05:27.770 fisheries uh along the coast. 00:05:27.850 --> 00:05:32.970 And so I was hired to do that um in part again because I had that experience in Tanzania 00:05:33.050 --> 00:05:36.570 working um with Hadza, uh knew my Key Swahili. 00:05:37.120 --> 00:05:41.680 Um, and then it just sort of starts, you know, the the Kenya site came up from a 00:05:41.680 --> 00:05:42.400 collaboration. 00:05:42.480 --> 00:05:48.400 So here at uh WSU in our School for Global Health, we have an NGO situated in 00:05:48.400 --> 00:05:50.160 Kenya with a lot of infrastructure. 00:05:50.240 --> 00:05:51.680 They have like permanent staff. 00:05:51.840 --> 00:05:56.640 And so collaborating with them to access some of the communities that they've worked with, 00:05:56.720 --> 00:06:01.440 you know, they have this huge like surveillance project for like MERS uh and camels up 00:06:01.440 --> 00:06:01.760 there. 00:06:02.370 --> 00:06:06.050 And so, you know, part of it's like said, sort of happenstance. 00:06:06.130 --> 00:06:09.570 Some of it, you know, is the question makes more sense in these communities. 00:06:09.730 --> 00:06:13.250 You know, the challenge, I don't think, is starting up the field site. 00:06:13.410 --> 00:06:15.250 I mean, you know, connections help. 00:06:15.330 --> 00:06:16.850 It's often maintaining the field site. 00:06:16.930 --> 00:06:21.010 So I wouldn't be working at all these different field sites if I didn't have collaborators 00:06:21.010 --> 00:06:22.850 who are helping maintain these relationships. 00:06:23.010 --> 00:06:27.730 So I haven't been back to Hadza Land since 2019, but I still collaborate with folks like 00:06:27.730 --> 00:06:29.250 Duncan Stibbard Hawks. 00:06:29.650 --> 00:06:29.890 Right. 00:06:30.050 --> 00:06:31.650 And so he's actively working there. 00:06:31.820 --> 00:06:37.660 My colleagues in vetmed working with uh populations in Kenya makes it easier for me to have 00:06:37.740 --> 00:06:39.660 you know these different opportunities. 00:06:39.820 --> 00:06:44.940 Um, but right now I'm hoping, anyways, my main focus will be the the fishery communities uh 00:06:44.940 --> 00:06:45.980 in Tanzania. 00:06:48.300 --> 00:06:48.620 Cool. 00:06:48.860 --> 00:06:50.060 Well, thank you for your service. 00:06:50.220 --> 00:06:53.820 Um exactly. 00:06:53.980 --> 00:06:55.420 Thank you for yeah. 00:06:56.060 --> 00:07:00.910 Um for me, I feel like your your research has um 00:07:01.870 --> 00:07:06.990 changed my mind about a few things in the evolutionary psychology of cooperation. 00:07:07.070 --> 00:07:11.550 And I feel like that's one of the virtues of doing fieldwork is that you know we have our 00:07:11.550 --> 00:07:16.990 our abstract theories and then we try to see if they work in the real world uh in a real 00:07:16.990 --> 00:07:22.260 setting that you know hopefully resembles some aspect of our uh evolutionary history or the 00:07:22.260 --> 00:07:23.620 ancestral environment. 00:07:23.940 --> 00:07:29.780 And our theories just kind of collide with reality and and we are forced to rethink things. 00:07:29.940 --> 00:07:35.380 So what are some of the things that you have had to rethink uh as a result of your work 00:07:35.380 --> 00:07:39.220 with with the Hadza and and with with other communities? 00:07:39.770 --> 00:07:41.690 Yeah, I that's a great question. 00:07:41.850 --> 00:07:46.330 So, you know, originally I wanted to be a pretty standard experimental psychologist. 00:07:46.410 --> 00:07:49.850 I was running my uh experiments in the lab, surveys online. 00:07:50.410 --> 00:07:55.130 Um, and this opportunity to work with uh Hadza came up from uh, you know, Corinne and I 00:07:55.130 --> 00:07:57.050 collaborating on a project together. 00:07:57.210 --> 00:07:59.210 Um and I thought, you know, I should do this. 00:07:59.290 --> 00:08:03.420 I'll uh I I didn't think I would do it forever or make it a core part, but I thought, you 00:08:03.420 --> 00:08:04.940 know, I gotta take this opportunity. 00:08:05.100 --> 00:08:08.220 Um and what ended up changing my mind was some of the findings from that. 00:08:08.380 --> 00:08:13.980 So I was working on we have this finding, Corinne has this finding uh in one of her classic 00:08:13.980 --> 00:08:19.340 papers where if you play a public goods game with Hadza Hunter Gatherers, that is um you 00:08:19.340 --> 00:08:23.820 give them some honey sticks, they can contribute some to uh a public good, and that's 00:08:23.820 --> 00:08:27.020 tripled and then shared with everyone that's living with them in their camp. 00:08:27.150 --> 00:08:30.670 Um, right, classic game to measure cooperation. 00:08:30.910 --> 00:08:36.510 Uh, in two different uh years, she got this finding where uh camps, 00:08:37.070 --> 00:08:40.590 uh, there are significant differences in how much camps cooperated. 00:08:40.750 --> 00:08:44.910 So if you uh look at like how it clusters within camps, some camps are cooperating more, 00:08:44.990 --> 00:08:46.590 some are cooperating less. 00:08:46.750 --> 00:08:52.200 Um, these camps move different locations and different times, they're different people are 00:08:52.200 --> 00:08:53.240 also living these camps. 00:08:53.480 --> 00:08:55.080 These aren't permanent social units. 00:08:55.240 --> 00:08:59.240 And so it doesn't seem like that's easily explained by ecology because it varied from year 00:08:59.240 --> 00:09:01.240 to year or from people. 00:09:01.400 --> 00:09:06.200 And so sort of the thing we wanted to investigate was what explains this clustering. 00:09:06.280 --> 00:09:08.600 And so there's a couple of mechanisms you can think about. 00:09:08.920 --> 00:09:13.080 You could think like reputation and partner choice or people selecting to live with people 00:09:13.080 --> 00:09:13.960 who are more cooperative. 00:09:14.040 --> 00:09:15.880 And that's why you get that clustering in camps. 00:09:16.090 --> 00:09:18.650 Or is it something like norms and punishment, right? 00:09:18.730 --> 00:09:23.610 People, uh, some camps have stronger norms, and so you have more uh sharing in these games. 00:09:23.770 --> 00:09:28.970 And I very much went in expecting partner choice to be like the really important 00:09:28.970 --> 00:09:30.170 mechanism here. 00:09:30.570 --> 00:09:33.850 And um, from the games, that doesn't seem to be the case. 00:09:33.930 --> 00:09:39.850 Uh, we didn't find any sort of uh stable willingness to cooperate across the years 00:09:39.930 --> 00:09:43.980 when we played this game with multiple uh multiple years with the same people. 00:09:44.220 --> 00:09:48.220 Uh, we didn't see people were ending up in more cooperative camps that they were previously 00:09:48.220 --> 00:09:48.940 more cooperative. 00:09:49.100 --> 00:09:52.220 And then we did this task where we asked people to rank their campmates. 00:09:52.300 --> 00:09:55.340 So we go in, we take Polaroid photos of each member of the camp. 00:09:55.420 --> 00:09:58.060 And then privately we we put out all the photos in front of them. 00:09:58.220 --> 00:10:00.540 We ask who's the most generous big person. 00:10:00.700 --> 00:10:02.380 And they repeat this until they rank everyone. 00:10:02.540 --> 00:10:05.350 We do this for things like generosity, uh, productivity. 00:10:05.430 --> 00:10:09.030 So how good of a hunter you are, um, and who do you want to live with, right? 00:10:09.110 --> 00:10:13.030 And so choosing who you want to live with is choosing who you're cooperating with in these 00:10:13.030 --> 00:10:17.510 camps where you have these strong uh inset uh norms to share food, right? 00:10:17.670 --> 00:10:19.750 So we use this as a measure of partner choice. 00:10:19.830 --> 00:10:23.750 And what we found, what I found that first year was that they didn't really care about who 00:10:23.830 --> 00:10:26.390 jet how generous the people they were living with were. 00:10:26.620 --> 00:10:30.140 Instead, they cared about, you know, who were good hunters, who were good gatherers. 00:10:30.300 --> 00:10:35.100 Um, and so that sort of, I I will say that I really did not like my first field season. 00:10:35.180 --> 00:10:36.780 I swore I would never do it again. 00:10:36.940 --> 00:10:41.820 But like digging through that data and having to sort of adjust, you know, what I thought 00:10:41.820 --> 00:10:46.620 was driving cooperation in this population uh really made me excited for it, right? 00:10:46.700 --> 00:10:48.940 In a way that I didn't get from lab experiments. 00:10:49.020 --> 00:10:52.950 So to your point, yeah, that that experience of theories meeting reality. 00:10:53.110 --> 00:10:56.390 Um and you know, doing the field work, you're right there to see it happen, right? 00:10:56.470 --> 00:10:58.310 It's it's sort of happening in real time for you. 00:10:58.390 --> 00:10:58.550 Yeah. 00:10:58.710 --> 00:11:01.750 Uh makes the field work fun and and exciting. 00:11:02.790 --> 00:11:03.030 Wow. 00:11:03.190 --> 00:11:04.070 So interesting. 00:11:04.150 --> 00:11:09.750 So I I want kind of wanna unpack this this result in these findings. 00:11:10.070 --> 00:11:15.360 So um people members of the Hadza are more 00:11:15.360 --> 00:11:20.720 interested in hunting and foraging ability more than uh generosity. 00:11:20.960 --> 00:11:25.680 So really, do you have the skills uh is more important that question is more important than 00:11:25.840 --> 00:11:28.640 are you willing to share the fruits of your labor? 00:11:28.880 --> 00:11:33.040 Uh do you think what might be going on there is that there's just kind of sharing by 00:11:33.040 --> 00:11:33.600 default? 00:11:33.760 --> 00:11:37.570 And so individual variation in sharing willingness just isn't a factor. 00:11:37.650 --> 00:11:42.210 It isn't really important because you're going to get some of the kill uh regardless. 00:11:42.450 --> 00:11:44.370 Or is it or is something else going on? 00:11:44.850 --> 00:11:47.330 Yeah, so that that's a really great way to put put it, right? 00:11:47.410 --> 00:11:52.290 So Hadza, like uh almost every hunter-gatherer that we have data from, really strong food 00:11:52.450 --> 00:11:53.810 sharing norms, especially with meat. 00:11:53.970 --> 00:11:57.330 Any meat that they bring back to camp is something they're expected to share. 00:11:57.490 --> 00:11:58.770 Now they do try to get around it. 00:11:58.850 --> 00:12:03.660 There's some famous stories of Hadza like asking uh researchers to hide like a kill 00:12:03.660 --> 00:12:06.220 underneath their uh truck and come back later for it. 00:12:06.380 --> 00:12:11.020 So it it's not automatic, but in that context where most things are going to be shared 00:12:11.100 --> 00:12:16.060 anyways, then yeah, it makes sense to focus on foraging ability instead, right? 00:12:16.220 --> 00:12:18.300 What what are you going to bring back to the camp? 00:12:18.460 --> 00:12:23.100 And if you look at partner choice models, you see this more formally, right, that the 00:12:23.100 --> 00:12:24.700 variance of traits matter. 00:12:24.860 --> 00:12:29.500 So if there's very little variance on a trait, then the marginal benefit of choosing 00:12:29.500 --> 00:12:31.740 someone higher on that trait is lower. 00:12:31.930 --> 00:12:36.810 And so one thing we find actually is that this effects uh reversed when I came back in 00:12:36.810 --> 00:12:37.610 2019. 00:12:37.770 --> 00:12:42.570 So in 2019, they did place more of an emphasis on generosity than productivity. 00:12:42.810 --> 00:12:47.690 And what we found was that this was really driven by people who had more experience outside 00:12:47.690 --> 00:12:48.570 of Hazeland. 00:12:48.650 --> 00:12:53.610 So if they had worked jobs for cash, if they had uh lived in a village at some point. 00:12:53.850 --> 00:12:59.340 And so now what we find, and Duncan, uh my Duncan Stibbard Hawks has data on this as well. 00:12:59.580 --> 00:13:03.900 A lot of HODs are now moving between uh the bush and villages. 00:13:04.060 --> 00:13:08.780 And when they're in the village, there's less uh sharing norms, there's less uh incentive 00:13:08.780 --> 00:13:10.540 and pressure to share as much. 00:13:10.700 --> 00:13:15.020 Um, in fact, uh, Duncan has pictures, they they have houses that they just store all their 00:13:15.020 --> 00:13:17.580 grain and they don't share any of their grain with anyone. 00:13:17.740 --> 00:13:23.420 Um, and so now when we're asking people who do you want to live with, the reality is 00:13:23.730 --> 00:13:29.090 their social world includes all these people who are also living in villages without these 00:13:29.090 --> 00:13:29.490 norms. 00:13:29.650 --> 00:13:33.890 And so what's happening is that, at least what we think, I never was able to follow up on 00:13:33.890 --> 00:13:39.330 this, is that the variance in sharing, willingness to share, is increasing as they have 00:13:39.330 --> 00:13:42.370 more experience moving between these two different social worlds. 00:13:42.530 --> 00:13:46.530 And so once you have more variance there, now that becomes more important when choosing a 00:13:46.530 --> 00:13:47.570 cooperative partner. 00:13:48.940 --> 00:13:49.580 Interesting. 00:13:49.820 --> 00:13:55.580 So could it be that when you earn wealth outside of Hadza Land, that 00:13:55.580 --> 00:13:59.660 wealth is easier to conceal from your fellow groupmates? 00:13:59.820 --> 00:14:04.780 And whether or not the groupmates get some of that depends more on the person's generosity 00:14:04.940 --> 00:14:08.540 because they can they can hide what whatever they gain, they can hide their cash, they can 00:14:08.540 --> 00:14:09.500 hide their grain. 00:14:09.580 --> 00:14:13.420 Uh and it really depends on how nice or generous that person is. 00:14:13.660 --> 00:14:19.370 Um whereas if you hunt a a a a zebra, it's gonna be pretty hard to hide that 00:14:19.370 --> 00:14:23.930 zebra from the rest of the people in your group and they're gonna uh, you know, pressure 00:14:23.930 --> 00:14:25.530 you uh to get some of that. 00:14:25.690 --> 00:14:30.330 And so could it be that it's the concealability of the resource that might be driving this? 00:14:30.810 --> 00:14:33.690 I I I think uh most likely that's part of it. 00:14:33.850 --> 00:14:38.880 It's easier to to your point, it's easier to hide what you have in terms of wealth, uh, 00:14:39.040 --> 00:14:42.320 you're more able to uh accumulate wealth to begin with, right? 00:14:42.400 --> 00:14:46.640 So if you're in these mobile camps, it's really hard to have a lot of property if you have 00:14:46.640 --> 00:14:47.920 to move every few weeks. 00:14:48.080 --> 00:14:52.320 Um, and then of course, uh again, what what we see is that when they're in these villages, 00:14:52.480 --> 00:14:54.160 they're relying a lot more on grain. 00:14:54.240 --> 00:14:56.720 They they rely on grain in the camps now too. 00:14:56.880 --> 00:15:01.440 Um, but they're relying more on grain, which is also easier to store than meat. 00:15:01.550 --> 00:15:06.990 So I think it's a a combination of these different sort of ecological factors that changing 00:15:06.990 --> 00:15:11.550 how they're able to store food and changing sort of the sharing norms, right? 00:15:11.630 --> 00:15:14.030 And so I think that's sort of the mediating. 00:15:14.110 --> 00:15:18.350 Like we could measure their uh sort of perceived norms. 00:15:18.510 --> 00:15:21.790 I imagine they differ between the camps and the villages. 00:15:21.870 --> 00:15:26.660 And like that would be the mediating factor, is that they're tracking, you know, how how 00:15:26.660 --> 00:15:31.380 much variance is there out in the world in generosity, and that's impacting how much they 00:15:31.540 --> 00:15:36.420 at least emphasis on generosity versus productivity when choosing cooperative partners. 00:15:36.740 --> 00:15:36.980 Yeah. 00:15:37.220 --> 00:15:42.260 One question is so we've been talking about it as sort of the emphasis on productivity as 00:15:42.260 --> 00:15:43.620 opposed to generosity. 00:15:43.860 --> 00:15:48.260 And we've been think talking about it from the perspective of why is generosity not being 00:15:48.260 --> 00:15:48.660 used. 00:15:48.820 --> 00:15:52.660 I'd like to invert it because that's been very interesting, but I'd also like to invert it 00:15:52.660 --> 00:15:58.650 and say, what is it in the um you sorry use the word village and then 00:15:58.650 --> 00:15:59.450 what's the other term? 00:15:59.770 --> 00:16:00.170 Bush. 00:16:00.410 --> 00:16:00.650 Bush. 00:16:00.890 --> 00:16:01.050 Okay. 00:16:01.130 --> 00:16:01.290 Yeah. 00:16:01.370 --> 00:16:05.770 So when they're in the bush, or people to the extent that in the prior calibration of being 00:16:05.770 --> 00:16:08.490 in the bush, you're going on productivity. 00:16:09.130 --> 00:16:14.490 It that is that is also in is that the only other positive attribute, or is that actually 00:16:14.490 --> 00:16:20.010 interesting in the sense of that is a sensical, rational allocation 00:16:20.220 --> 00:16:23.820 of resources, what does that mean in the context of the bush? 00:16:23.980 --> 00:16:27.500 And then what does it mean that it's not happening in the village? 00:16:27.660 --> 00:16:32.860 Like, for example, is it that um you're not you're you're 00:16:32.860 --> 00:16:38.620 abandoning what had previously been uh a dimension of status, or is it 00:16:38.860 --> 00:16:40.700 is that reading too much into it? 00:16:41.340 --> 00:16:45.190 That I I I um that might be reading a little too much into it. 00:16:45.270 --> 00:16:47.670 Dun Duncan has done the work of actually visiting. 00:16:47.750 --> 00:16:49.750 I didn't get a chance to visit the villages. 00:16:49.830 --> 00:16:52.310 It was a planned follow-up before COVID. 00:16:52.550 --> 00:16:57.990 Um and so he he would know more, but my understanding is that they're still hunting there. 00:16:58.230 --> 00:17:02.550 Um and so so another way to look at it right here is that the benefits you get from a 00:17:02.550 --> 00:17:06.630 cooperative partner is both their willingness to actually help you and their their ability, 00:17:06.710 --> 00:17:06.950 right? 00:17:07.190 --> 00:17:10.950 Someone who's a total klutz but is really generous is as helpful as someone who's really 00:17:10.950 --> 00:17:12.520 selfish and and really effective, right? 00:17:12.600 --> 00:17:13.640 You need kind of both. 00:17:13.880 --> 00:17:16.280 The question is, you know, how much emphasis to place. 00:17:16.440 --> 00:17:21.640 And so uh another possibility is that there's also less variance in productivity or 00:17:21.640 --> 00:17:25.160 competence in the uh villages than the camps. 00:17:25.320 --> 00:17:29.160 Hunting's a really uh high risk uh activity. 00:17:29.400 --> 00:17:34.040 I think they have like a 3% uh hunting uh success rate, is the classic statistic. 00:17:34.280 --> 00:17:39.450 So, you know, being a little bit better can have a massive effect on productivity there in 00:17:39.450 --> 00:17:43.130 the villages where they're hunting a little bit, but they're also farming a little and 00:17:43.130 --> 00:17:43.930 keeping gardens. 00:17:44.090 --> 00:17:49.770 There might be less variance in um competence there or productivity. 00:17:50.010 --> 00:17:55.130 Gathering's another example where there's still skills involved in gathering and an ability 00:17:55.130 --> 00:18:00.250 to uh endure, but probably less so than um what we find with hunters. 00:18:00.330 --> 00:18:05.000 And there was some kind of a suggestive effect that women placed a little less emphasis on 00:18:05.000 --> 00:18:06.680 other women's uh productivity. 00:18:06.760 --> 00:18:08.520 So that that would also be consistent. 00:18:08.680 --> 00:18:13.400 That again, what they're trying to track is really what's the benefit of switching to a new 00:18:13.400 --> 00:18:14.200 partner here. 00:18:14.360 --> 00:18:17.880 And really there's got to be enough variance for that to really make sense because there's 00:18:17.880 --> 00:18:21.560 costs and moving and and you know trying out new uh cooperative partners. 00:18:21.870 --> 00:18:22.110 Yeah. 00:18:22.270 --> 00:18:24.590 The the variance point is really uh deep. 00:18:24.670 --> 00:18:27.070 And I think we've talked about David and I have talked about that a bunch. 00:18:27.150 --> 00:18:30.830 That, you know, because as you said, Chris, lots of things are skill dependent. 00:18:30.910 --> 00:18:34.110 I mean, even walking is skill dependent, but there's not much variance in that. 00:18:34.270 --> 00:18:39.870 And so I think for a lot of status things, what I'm hearing you say is that for dimensions 00:18:39.870 --> 00:18:45.870 of status, the variance, especially within a market, uh competitive market 00:18:46.030 --> 00:18:51.150 of uh who you're gonna choose as a partner, partner choice, um, variance is really 00:18:51.150 --> 00:18:51.470 important. 00:18:52.120 --> 00:18:52.920 Yeah, I think so. 00:18:53.000 --> 00:18:56.280 And to your point, right, if you then start thinking about different domains and where 00:18:56.280 --> 00:18:58.760 where that variance is, that's gonna impact it. 00:18:58.840 --> 00:19:03.080 And I think folks like Adar uh Eisenberg has some modeling work trying to show how that 00:19:03.080 --> 00:19:06.920 impacts the evolution of cooperation, having these different domains and how much they 00:19:06.920 --> 00:19:09.720 correlate across uh these different domains as well. 00:19:10.200 --> 00:19:10.440 Yeah. 00:19:10.680 --> 00:19:11.800 That's super interesting stuff. 00:19:11.960 --> 00:19:17.160 I mean, uh in some ways it suggests a more nuanced picture of how people are choosing 00:19:17.170 --> 00:19:18.290 cooperative partners. 00:19:18.450 --> 00:19:23.890 And they're not just saying, oh, uh, I I want the the kindest, most uh competent partners. 00:19:24.050 --> 00:19:28.690 It's I'm tracking the variation in these trait attributes. 00:19:28.850 --> 00:19:34.850 And I am strategically uh being choosy on the on the traits that vary in my local ecology. 00:19:35.010 --> 00:19:38.610 And the traits that don't vary as much, I'm going to be less choosy about those traits. 00:19:38.770 --> 00:19:44.530 And that suggests a uh a more sensitive uh uh mind that is uh really picking up on these 00:19:44.530 --> 00:19:47.240 cues of how variable different traits are. 00:19:47.560 --> 00:19:52.440 Um and and also in the in the aspects of the resources themselves, whether they can be 00:19:52.440 --> 00:19:56.360 stored or concealed, or whether they're conspicuous and out in the open. 00:19:57.160 --> 00:20:00.120 All of these factors that you know the mind is sensitive to. 00:20:00.280 --> 00:20:01.800 And I think that's really cool. 00:20:02.360 --> 00:20:08.280 I I want to go back to this uh finding you mentioned about differences in 00:20:08.650 --> 00:20:12.010 um cooperation in a public goods game. 00:20:12.330 --> 00:20:17.050 So you have different sorry, was it different camps that had different cooperation rates? 00:20:17.370 --> 00:20:17.610 Yeah. 00:20:17.770 --> 00:20:22.330 So uh we play the game within the the camp and they're making these decisions in private. 00:20:22.490 --> 00:20:22.810 But yeah. 00:20:23.130 --> 00:20:23.290 Right. 00:20:23.530 --> 00:20:28.410 And so basically they're deciding um whether to uh put a resource, and so in this case a 00:20:28.410 --> 00:20:33.210 honey stick, into the pot to be multiplied and distributed uh among the group. 00:20:33.370 --> 00:20:35.850 So it's basically acting for the good of the group. 00:20:36.170 --> 00:20:36.490 Right. 00:20:37.210 --> 00:20:42.760 Um and with this game, there is the classic free rider problem where everyone is better off 00:20:42.760 --> 00:20:46.920 if everyone else contributes to the pot, but I selfishly free ride off of everyone's 00:20:46.920 --> 00:20:47.160 effort. 00:20:47.240 --> 00:20:50.680 But if everyone thinks that way, then everyone free rides and there's no there's nothing in 00:20:50.680 --> 00:20:51.240 the pot. 00:20:51.400 --> 00:20:56.920 Um and so what you're seeing is in some camps, uh people are contributing uh a lot to the 00:20:56.920 --> 00:21:00.280 pot, and in some they're not contributing much of anything at all. 00:21:01.050 --> 00:21:06.810 And it seems like ecology can't really explain this because there's so much variation 00:21:06.810 --> 00:21:09.610 in the ecology from season to season, from year to year. 00:21:09.690 --> 00:21:13.850 Uh and people are, you know, it's a fission-fusion society, so people are, you know, ending 00:21:13.850 --> 00:21:17.210 up in constantly sort of wandering around to different places. 00:21:17.290 --> 00:21:21.130 So it seems like ecology is not really going to explain this difference. 00:21:21.370 --> 00:21:25.000 So do you have any thoughts about what is explaining this? 00:21:25.080 --> 00:21:29.000 I mean you mentioned norms, but I feel like that just begs the question of why do these 00:21:29.000 --> 00:21:29.960 norms differ. 00:21:30.520 --> 00:21:32.360 Yeah, it's a really good question. 00:21:32.520 --> 00:21:38.360 And, you know, we tried uh to rule out as much as we could things like ecology or had they 00:21:38.360 --> 00:21:38.680 just eaten. 00:21:38.920 --> 00:21:43.160 So I think in one year uh we had asked, you know, when was the last time someone brought in 00:21:43.160 --> 00:21:44.120 a kill or something? 00:21:44.200 --> 00:21:49.150 And uh we couldn't find anything that could explain um these differences in cooperation, 00:21:49.230 --> 00:21:55.230 how much like can you have, or um things like that didn't seem to really predict 00:21:55.230 --> 00:21:56.510 how much people were cooperating. 00:21:56.590 --> 00:22:01.630 It just uh the only reliable predictor was how much everyone else is giving. 00:22:02.030 --> 00:22:07.070 And so the the question rises, you know, I I think to your point, it's easy to invoke norms 00:22:07.070 --> 00:22:07.310 here. 00:22:07.550 --> 00:22:12.480 And so sort of what we kind of suspect happens is that someone moves in and I remember 00:22:12.480 --> 00:22:18.400 those classic uh there's a classic psychology study of the autokinetic effect, uh, where 00:22:18.400 --> 00:22:22.320 you that you shine a light in a dark uh room and it looks like it's moving. 00:22:22.400 --> 00:22:26.080 And so they have a group of people and they shine this light and they ask them, and someone 00:22:26.080 --> 00:22:30.080 says, Oh, it's two inches to the right, and everyone else in the group answers that. 00:22:30.160 --> 00:22:35.760 And then if you take each person out of that group one by one and add a new person in, even 00:22:35.760 --> 00:22:41.330 once there's an entirely new group, they s they're still answering the same uh uh biased 00:22:41.330 --> 00:22:43.010 answer that was originally answered, right? 00:22:43.250 --> 00:22:45.330 They're sort of adopting the norm as they come in. 00:22:45.490 --> 00:22:50.050 We think that's probably something that's happening here is that as they move into this 00:22:50.050 --> 00:22:55.010 camp and they see how much people are sort of uh willing to give uh in day-to-day life, how 00:22:55.090 --> 00:22:59.650 much you know, how hard is it to get them to actually share, that this is uh impacting sort 00:22:59.650 --> 00:23:04.290 of what they believe everyone else's behavior will be, um, and that this is carrying over 00:23:04.290 --> 00:23:05.010 to the game. 00:23:05.340 --> 00:23:07.740 That's the assumption we're looking for. 00:23:08.220 --> 00:23:11.340 We did try to measure those normative expectations. 00:23:11.500 --> 00:23:15.020 So we did try to ask people, this was with Christina Biggier. 00:23:15.180 --> 00:23:18.060 So we tried to ask, you know, what do you think everyone else in your camp will do? 00:23:18.460 --> 00:23:22.300 And what do you think everyone else in your camp thinks other people should do? 00:23:23.020 --> 00:23:25.500 But we couldn't we couldn't get the the method to work. 00:23:25.580 --> 00:23:29.900 It was it's too complex for they couldn't just wrap they couldn't wrap their head around 00:23:29.900 --> 00:23:30.620 the question. 00:23:30.860 --> 00:23:32.810 They couldn't wrap their head around their question the question. 00:23:32.890 --> 00:23:37.210 And even when you do those questions with like US undergrads, it can actually often be 00:23:37.210 --> 00:23:37.610 challenging. 00:23:37.690 --> 00:23:40.570 So that it's kind of a hard question to ask. 00:23:41.370 --> 00:23:46.650 So we'd expect norms, you'd expect there would be some sort of punishment to reinforce 00:23:46.650 --> 00:23:47.130 those norms. 00:23:47.210 --> 00:23:48.410 That's usually the model. 00:23:49.450 --> 00:23:55.130 There's very few examples in the ethnographic literature of any sort of physical punishment 00:23:55.130 --> 00:23:56.010 between the Hadza. 00:23:56.170 --> 00:23:57.450 You'll see scolding. 00:23:57.820 --> 00:24:03.180 And, you know, we often assume scolding has reputational costs that uh influence 00:24:03.180 --> 00:24:04.060 punishment. 00:24:04.780 --> 00:24:09.500 But, you know, my concern there is that there's such strong sharing norms, anyways, that 00:24:09.500 --> 00:24:15.020 even if, you know, there's one guy I was talking with who everyone knew he had murdered his 00:24:15.020 --> 00:24:18.220 wife, like this was common knowledge, no one disputed it. 00:24:18.380 --> 00:24:19.740 But people would still share with him. 00:24:19.820 --> 00:24:22.540 And they would say, like, that's that's what it is to be Hadza is. 00:24:22.620 --> 00:24:23.740 You share with other Hadza. 00:24:23.980 --> 00:24:29.830 And so it's not clear if those scoldings and the reputation actually, you know, translate 00:24:29.830 --> 00:24:31.030 into any real costs. 00:24:31.270 --> 00:24:35.830 So honestly it's a shoulder shrug at like what's actually maintaining this still. 00:24:35.910 --> 00:24:39.990 Uh again, the went in thinking it'd be partner choice and reputation. 00:24:40.310 --> 00:24:43.590 Um and now not so sure about that. 00:24:43.990 --> 00:24:44.310 Wow. 00:24:45.110 --> 00:24:49.750 I love that that anecdote of the guy who everyone knows that he murdered his wife and 00:24:49.750 --> 00:24:51.270 everyone knows that everyone knows that. 00:24:51.430 --> 00:24:56.220 And yet he's still a a member of the community in good standing who gets an equal share of 00:24:56.220 --> 00:24:58.220 the spoils or of the resources. 00:24:58.380 --> 00:25:04.220 Um that is a very alien idea to to to my Western mind, you know, where you know if someone 00:25:04.220 --> 00:25:06.140 murders their wife, they they get imprisoned for life. 00:25:06.300 --> 00:25:08.540 In some cases they'll get sentenced to death. 00:25:08.940 --> 00:25:12.860 And yet in this case they're still a member of the group in in good standing. 00:25:13.580 --> 00:25:19.210 Yeah, I I mean s we think that he was excluded from some camps uh 00:25:19.370 --> 00:25:19.930 initially. 00:25:20.090 --> 00:25:23.370 He was in uh a couple of years after that, he was in some smaller camps. 00:25:23.610 --> 00:25:26.250 Though that could also just be a personal choice of his. 00:25:26.330 --> 00:25:27.450 It's it's hard to tell. 00:25:27.610 --> 00:25:32.170 Um but by the time I was working with him in 2016 and then especially twenty nineteen, so 00:25:32.170 --> 00:25:35.530 that would been I I think it happened in twenty thirteen, so it was like five or six years 00:25:35.530 --> 00:25:36.090 later. 00:25:36.410 --> 00:25:40.650 The aunt of the woman he killed uh was in that camp and really disliked him. 00:25:40.730 --> 00:25:45.820 But everyone else was again, they would talk about it, but they were still willing to share 00:25:45.820 --> 00:25:50.460 with him and still also emphasized his good traits as well, that he was a good hunter, um, 00:25:50.540 --> 00:25:51.660 that he was a funny guy. 00:25:51.820 --> 00:25:57.820 So, you know, uh it it doesn't necessarily mean the stor what I take away 00:25:57.820 --> 00:26:01.820 from that story is that again, reputational costs, we have to be careful and actually see 00:26:01.820 --> 00:26:05.660 what what do those costs really translate to, because there's other mechanisms that could 00:26:05.660 --> 00:26:09.420 be interfering with how that translates into you know real costs for the actors. 00:26:09.740 --> 00:26:09.900 Yeah. 00:26:10.060 --> 00:26:13.550 What does it mean to not share in that community. 00:26:13.790 --> 00:26:14.990 Like, what are the consequences? 00:26:15.070 --> 00:26:16.430 If somebody doesn't share with me, do I die? 00:26:16.590 --> 00:26:18.030 Like, what what are the consequences? 00:26:18.190 --> 00:26:18.430 Yeah. 00:26:18.910 --> 00:26:21.230 If someone doesn't share with you or if you don't share with someone. 00:26:21.470 --> 00:26:23.870 So let's uh if if somebody doesn't share with me. 00:26:23.950 --> 00:26:27.870 So like if everybody decided for this guy we weren't gonna share with him, what would 00:26:27.870 --> 00:26:28.830 happen to him? 00:26:29.630 --> 00:26:32.110 Um that's a good question. 00:26:32.190 --> 00:26:35.920 I I I mean again, so the hunting success rates are really low for Hadza. 00:26:36.160 --> 00:26:40.640 So a single hunter will bring in a kill once a month, about um, and that's probably not 00:26:40.640 --> 00:26:41.760 enough calories. 00:26:41.920 --> 00:26:47.360 Um could probably get by on and this guy was a particularly good hunter, so maybe he would 00:26:47.360 --> 00:26:49.040 have been somewhat fine. 00:26:49.280 --> 00:26:54.160 I think eventually you would he would probably have to move from the bush to maybe one of 00:26:54.160 --> 00:26:54.880 the villages. 00:26:55.040 --> 00:26:58.630 But again, he might actually do better in that village ultimately, right? 00:26:58.710 --> 00:27:02.710 Like we're not even sure if banishment or excluding would necessarily be costly. 00:27:02.870 --> 00:27:06.390 Because another thing that would happen is that he would be expected to share less as well, 00:27:06.470 --> 00:27:06.710 right? 00:27:06.870 --> 00:27:11.190 So he might actually benefit from not having those obligations. 00:27:11.350 --> 00:27:17.350 So again, I I I m the thing I took away from this is that we want to be we don't want to 00:27:17.350 --> 00:27:22.740 assume reputation necessarily has a cost without actually Yeah. 00:27:22.900 --> 00:27:28.900 I mean what what I'm hearing you say, maybe one interpretation is the making a living 00:27:28.900 --> 00:27:34.900 in a particular ecology really sets up like costs and benefits that 00:27:34.900 --> 00:27:37.300 are have a lot of momentum. 00:27:37.380 --> 00:27:43.380 Um and like the variability between people, it's important, but you you know, you really 00:27:43.380 --> 00:27:49.070 have to understand the um the the way of making a living and if sharing is 00:27:49.070 --> 00:27:49.710 really important. 00:27:49.950 --> 00:27:52.990 I mean I mean it sounds like in this particular case, like yeah, the guy would probably 00:27:52.990 --> 00:27:54.030 have been fine or better. 00:27:54.190 --> 00:27:59.630 But like if it was like, you know, a mom whose partner died or a kid, you know, like they 00:27:59.630 --> 00:28:00.030 would probably die. 00:28:00.190 --> 00:28:00.670 You know, I don't know. 00:28:00.910 --> 00:28:06.190 Maybe I'm putting words in your mouth, but like yeah, it's it's it's the if thinking about 00:28:06.190 --> 00:28:10.030 all the phenotypes that would be affected by this blanket policy, it sounds like some of 00:28:10.030 --> 00:28:11.870 them it would be a really bad situation. 00:28:12.030 --> 00:28:12.350 Yeah. 00:28:12.820 --> 00:28:12.980 Yeah. 00:28:13.140 --> 00:28:14.740 I I think that's the the right way to put it. 00:28:14.820 --> 00:28:19.540 So we can think about like between populations, what's the variation in ecology, 00:28:19.700 --> 00:28:24.260 subsistence, and norms and institutions that fit that particular an environment. 00:28:24.660 --> 00:28:27.780 But then also to your point, variation within those populations, right? 00:28:27.860 --> 00:28:31.620 That some people are going to be more affected or less affected. 00:28:31.780 --> 00:28:33.940 Um and so tending to that variation. 00:28:34.020 --> 00:28:37.860 And and really that's what I've come to love about field work is understanding that 00:28:37.860 --> 00:28:38.420 variation. 00:28:38.580 --> 00:28:42.650 So, you know, I think the first time I started working with Hadza, I I I did emphasize, 00:28:42.730 --> 00:28:46.570 like, oh, sort of the ancestral relevance that you know they're hunter-gatherers. 00:28:46.810 --> 00:28:48.730 Now I've sort of moved away from that. 00:28:48.810 --> 00:28:53.290 And uh many anthropologists where I I think the emphasis instead is like this is one way 00:28:53.290 --> 00:28:54.010 humans have lived. 00:28:54.090 --> 00:28:58.250 There are other ways, and we need to understand that that full variation rather than 00:28:58.250 --> 00:29:02.810 necessarily assuming you know, hunter-gatherers are some sort of you know stand-in for 00:29:02.810 --> 00:29:04.170 ancestral hunter-gatherers. 00:29:04.410 --> 00:29:04.570 Right. 00:29:04.730 --> 00:29:04.970 Right. 00:29:05.210 --> 00:29:09.420 Yeah, no, I think that's an increasingly important insight that anthropologists have made 00:29:09.500 --> 00:29:14.700 that we're in some ways we are overstating the importance of the few remaining 00:29:14.700 --> 00:29:19.020 hunter-gatherer populations that still exist as a window into the ancestral past. 00:29:19.660 --> 00:29:24.140 In all likelihood, the ancestral past was extremely variable with extremely many different 00:29:24.140 --> 00:29:26.620 ways of making a living, many different ecologies. 00:29:27.500 --> 00:29:32.940 And it's it's important not to, you know, overgeneralize from a 00:29:32.940 --> 00:29:37.330 particular culture or a particular ecology to humanity in general. 00:29:37.410 --> 00:29:41.330 And to see this as one of many possible ways that humans can live. 00:29:41.810 --> 00:29:42.050 Yeah. 00:29:42.290 --> 00:29:42.450 Yeah. 00:29:42.530 --> 00:29:47.410 And I think one way to put it is it's just like you would treat an undergrad population, 00:29:47.570 --> 00:29:53.250 which is any outcome is a result of contingency in the 00:29:53.250 --> 00:29:53.970 phenotype. 00:29:54.130 --> 00:29:59.980 And so even for a hunter-gatherer community or sample, you don't want to 00:29:59.980 --> 00:30:03.100 say, well, then this is just the essence of humanity, right? 00:30:03.180 --> 00:30:09.020 Like this level of conflict or this level of extra pair uh copulations 00:30:09.100 --> 00:30:13.500 or anything, you know, like that's that's humanity, like that's essentializing, right? 00:30:13.580 --> 00:30:19.100 I think the point is any sample of any human behavior is the result of the evolved 00:30:19.100 --> 00:30:21.990 phenotype interacting with the local circumstances. 00:30:22.070 --> 00:30:27.190 And so you you have to think about like this: what's the design underlying this outcome, 00:30:27.350 --> 00:30:30.870 not just that this outcome is sort of the essence of human nature? 00:30:31.350 --> 00:30:32.790 Yeah, I I couldn't put it better. 00:30:32.870 --> 00:30:34.230 Uh I totally agree with that, right? 00:30:34.390 --> 00:30:37.270 Thinking again about how those mechanisms are interacting. 00:30:37.590 --> 00:30:41.670 We know, right, on the surface of it, you just look around and we know humans vary, right? 00:30:41.750 --> 00:30:46.020 We can look from different countries, even within countries, we see all this variation uh 00:30:46.100 --> 00:30:50.820 in human phenotype, which I always point out to my bioanthro students is amazing because 00:30:50.820 --> 00:30:55.140 when we compare genetic diversity, we're leaf less genetically diverse than all the other 00:30:55.140 --> 00:30:55.940 great apes, right? 00:30:56.500 --> 00:31:01.700 Um and so thinking about how do we build a human science that accounts for that variation 00:31:01.860 --> 00:31:06.290 and essentializing uh in any aspect is probably gonna be the wrong way, right? 00:31:06.370 --> 00:31:10.610 Instead of thinking about those interacting mechanisms between mind, culture, and ecology. 00:31:10.850 --> 00:31:15.490 Yeah, I love Brett Beheim had uh in his in our long format episode with him, had a great 00:31:15.490 --> 00:31:19.090 saying it was that um genes are smooth, culture's crunchy. 00:31:19.410 --> 00:31:21.330 Oh, like the variability, yeah, exactly. 00:31:21.650 --> 00:31:22.450 Yeah, exactly. 00:31:22.690 --> 00:31:27.650 It's like a nice slogan for exactly that point that we're genetically so similar, uh, but 00:31:27.650 --> 00:31:28.610 we're just so different. 00:31:28.770 --> 00:31:33.620 And you just you it an alien looking at us would be like, oh yeah, no, no, like the effect 00:31:33.620 --> 00:31:35.940 of culture is very big. 00:31:36.020 --> 00:31:40.820 Um, even very close by people are acting differently, as you're finding even in different 00:31:40.980 --> 00:31:43.860 uh um collectives, basically in the bush. 00:31:44.020 --> 00:31:44.260 You know. 00:31:44.660 --> 00:31:45.700 Yeah, exactly. 00:31:46.100 --> 00:31:51.620 So I'm I'm curious, have you witnessed any kind of social cost being 00:31:51.620 --> 00:31:56.260 inflicted on someone in in your field work, whether it's punishment or exclusion or 00:31:56.260 --> 00:32:02.130 ostracism or collective um I I I I know you know Richard 00:32:02.130 --> 00:32:06.050 Rangham has work arguing that you know occasionally people will gang up on someone and and 00:32:06.050 --> 00:32:09.250 kill them in you know a a small scale society. 00:32:09.410 --> 00:32:15.330 Um have you witnessed any kind of social costs being inflicted on anyone for any reason? 00:32:16.690 --> 00:32:18.690 Not with the Hadza really. 00:32:18.770 --> 00:32:23.250 Uh part of that is is how I was doing my field work with them, going you know, going to a 00:32:23.250 --> 00:32:26.930 bunch of different camps means you're not staying there for a long time and and getting 00:32:26.930 --> 00:32:28.440 into you know the meat of it. 00:32:28.600 --> 00:32:28.840 Yeah. 00:32:28.920 --> 00:32:32.360 You know, they have a guess they're gonna be on better behavior, right? 00:32:32.520 --> 00:32:38.200 Um I have in some of the villages, in the fishing villages, uh I've worked with where I I 00:32:38.200 --> 00:32:40.120 would spend more time in each village. 00:32:40.200 --> 00:32:44.040 And so you get more into like the thread of the the fabric of the community. 00:32:44.200 --> 00:32:49.000 And you know, you'll see things, uh I I think probably the biggest blow up I saw was a 00:32:49.350 --> 00:32:55.110 woman, really really a girl refusing to marry a particular older man. 00:32:55.350 --> 00:33:00.950 Um, and there was some conflict between uh, you know, the parents wanted her to marry him, 00:33:01.110 --> 00:33:06.950 she didn't want to, and so there was and this comes up in like uh Zach and Manveer 00:33:07.030 --> 00:33:10.310 and Leo have talked about like really don't see a lot of punishment, which you see is 00:33:10.310 --> 00:33:10.710 mediation. 00:33:10.790 --> 00:33:16.300 And so they got the imam involved, uh the village executive officer, and they weren't 00:33:16.300 --> 00:33:20.140 trying to punish the but they were trying to sort of negotiate, try to convince her, or you 00:33:20.140 --> 00:33:22.780 know, try try to smooth over the situation. 00:33:23.180 --> 00:33:28.780 Um I, you know, I suspect imposing social costs are costly, and so the 00:33:28.780 --> 00:33:33.580 mediation is probably easier and the the more desired outcome usually. 00:33:33.660 --> 00:33:39.660 So I think I I I haven't seen a lot of like just clear cut cases of here here's a social 00:33:39.660 --> 00:33:40.620 cost being imposed. 00:33:40.780 --> 00:33:43.900 But again, that that just might be how I'm doing my field work. 00:33:44.750 --> 00:33:45.150 Interesting. 00:33:45.310 --> 00:33:50.750 I mean, could it be that, you know, each member of the community is so valuable and they're 00:33:50.750 --> 00:33:52.030 so interdependent with each other? 00:33:52.110 --> 00:33:56.750 So such that, you know, excluding anyone really inflicts a huge cost on the rest of us. 00:33:56.910 --> 00:34:01.310 Because if we have like a 3% hunting return, having an extra hunter in the group who's a 00:34:01.310 --> 00:34:03.710 good hunter is like a huge benefit to all of us. 00:34:03.870 --> 00:34:06.510 And excluding that person is a huge cost to all of us. 00:34:06.670 --> 00:34:10.510 And so it may be that the you know each member is just so integral to the community and so 00:34:10.510 --> 00:34:15.720 interdependent that the costs of inflicting any kind of exclusion or punishment on a person 00:34:15.720 --> 00:34:19.800 that could put you know break up the community or break up a cooperative relationship, that 00:34:19.800 --> 00:34:23.320 that's just too too big of a cost to experience. 00:34:24.200 --> 00:34:26.280 Could that be part of what's going on? 00:34:26.600 --> 00:34:30.920 Yeah, I I think that's uh that's a perfectly reasonable thing to think about as as you 00:34:30.920 --> 00:34:33.560 mentioned and an idea that he he was a good hunter, right? 00:34:33.640 --> 00:34:36.600 So uh losing him could be particularly costly. 00:34:36.760 --> 00:34:39.480 And we talk about this in like partner choice models all the time, right? 00:34:39.560 --> 00:34:43.510 Like the value, your value that you're bringing to the table uh predicts like your 00:34:43.510 --> 00:34:45.030 willingness to leave relationships, right? 00:34:45.190 --> 00:34:49.990 So if uh it's less costly to end a relationship because there are other options available, 00:34:50.230 --> 00:34:54.470 because um, you know, you're a high-value partner and you'll have access to those options, 00:34:54.630 --> 00:34:56.870 then it's easier to cut that relationship off. 00:34:57.030 --> 00:35:01.510 But yeah, maybe if it's so small that there's not enough other folks, or this person's 00:35:01.510 --> 00:35:06.420 particularly valuable because he's a good hunter, then it's just it's even costlier to 00:35:06.420 --> 00:35:07.380 impose those costs. 00:35:07.460 --> 00:35:12.660 And so again, maybe you try to negotiate uh through other means ways for them to improve 00:35:12.660 --> 00:35:16.820 their behavior so you can still get the benefits that they're bringing to the group. 00:35:17.300 --> 00:35:17.700 Interesting. 00:35:17.860 --> 00:35:22.820 I mean it it suggests, you know, a possible explanation for the extreme differences we see 00:35:22.820 --> 00:35:26.180 between Western societies uh and the Hadza, for example. 00:35:26.340 --> 00:35:31.690 So in a Western society, we live in these huge, massive populations, and we have these huge 00:35:31.690 --> 00:35:36.570 social networks, so many people we could potentially form cooperative relationships with. 00:35:36.810 --> 00:35:42.010 And the cost of excluding someone from my social network to me is extremely low. 00:35:42.170 --> 00:35:44.250 I could easily replace them with someone else. 00:35:44.650 --> 00:35:50.170 There's a huge social marketplace and many different people for me for me to choose from. 00:35:50.490 --> 00:35:56.410 And it doesn't hurt me at all if I, you know, say goodbye to a friend or a colleague or 00:35:57.290 --> 00:35:58.090 whatever. 00:35:58.480 --> 00:36:04.240 So in that case, if someone say murders their wife, I could say fine, put them away in 00:36:04.240 --> 00:36:04.720 prison forever. 00:36:04.800 --> 00:36:05.360 What do I care? 00:36:05.440 --> 00:36:08.080 You know, like I'll I'll find someone else to cooperate with. 00:36:08.240 --> 00:36:11.520 But in the Hadza, that's gonna be a much costlier thing to do. 00:36:11.760 --> 00:36:15.280 And so do you buy this this kind of relational mobility, the size of the social 00:36:15.280 --> 00:36:19.200 marketplace, that this might be an important factor regulating to what extent different 00:36:19.200 --> 00:36:21.440 transgressions are punished? 00:36:22.430 --> 00:36:24.830 Yeah, I I I think it definitely matters. 00:36:24.990 --> 00:36:28.430 I think the story gets complicated if you look at so there's uh you mentioned relational 00:36:28.430 --> 00:36:29.070 mobility, right? 00:36:29.230 --> 00:36:33.950 So there's ecological psychologists who have sort of their different uh measurements have 00:36:33.950 --> 00:36:38.590 sort of uh calculated for each country sort of their relational mobility level. 00:36:38.990 --> 00:36:41.310 And there's some cross-cultural analyses. 00:36:41.390 --> 00:36:45.470 Um I but I think when you dig into that literature, there's some contradictions where 00:36:45.470 --> 00:36:51.440 sometimes having more relational mobility increases cooperation because you have 00:36:51.440 --> 00:36:55.680 to compete more because people can leave you, but other times it seems to decrease 00:36:55.680 --> 00:36:59.360 cooperation because uh uh there's less incentive to. 00:36:59.520 --> 00:37:02.720 And so I I'm a little skeptical of some of those analyses. 00:37:03.440 --> 00:37:08.560 And there's folks who have redone the analyses trying to you know control for uh distance 00:37:08.560 --> 00:37:13.280 and and other uh confounds, and you know these effects seem to be um 00:37:14.690 --> 00:37:17.490 It's sort of difficult to wrap your head around, I think. 00:37:17.570 --> 00:37:23.010 Um, but uh more generally the idea that like uh yeah, who's in your network, how large your 00:37:23.010 --> 00:37:26.770 network is, uh, I think matters also what other institutions you have. 00:37:26.930 --> 00:37:31.010 I mean, the reality is if I need help, I don't usually go to a friend, right? 00:37:31.090 --> 00:37:33.970 I might go to my bank, my credit card, insurance, right? 00:37:34.050 --> 00:37:39.410 We have all these other institutions that also reduce our interdependence in some ways. 00:37:39.570 --> 00:37:43.250 And so we can think about what impacts that might also have, though, on our, you know, 00:37:43.330 --> 00:37:48.800 friendship uh psychologies um you know having these other uh institutions to buffer 00:37:48.960 --> 00:37:49.360 risk. 00:37:49.760 --> 00:37:50.000 Right. 00:37:50.160 --> 00:37:53.360 It seems like everyone is very replaceable in in the Western world. 00:37:53.600 --> 00:37:58.000 Whereas in the in the in the Hadza, you know, basically everyone is irreplaceable. 00:37:58.160 --> 00:38:02.400 Um or maybe I'm I'm I'm oversimplifying there, but I that seems to be one difference that 00:38:02.400 --> 00:38:03.440 might might matter. 00:38:03.920 --> 00:38:06.230 Yeah, I I think that's that's that's a good way to put it. 00:38:06.390 --> 00:38:06.630 Yeah. 00:38:06.710 --> 00:38:09.270 The people are are more replaceable here. 00:38:09.350 --> 00:38:12.870 Um and so that's gonna impact how we cooperate with one another. 00:38:13.190 --> 00:38:16.550 Does that I mean just could we'll and we'll move on, but I'm just curious like per 00:38:16.710 --> 00:38:22.070 interpersonally or anecdotally, when you go to Hadza Land or you have that impression, and 00:38:22.070 --> 00:38:26.790 that's a big difference between your your here here meaning like where you are right now 00:38:26.950 --> 00:38:28.240 and when you're there. 00:38:28.400 --> 00:38:33.600 Uh, do you notice uh what effect that has um 00:38:34.240 --> 00:38:35.440 on life? 00:38:35.680 --> 00:38:40.160 That the replaceable I mean, obviously there's other there's many other confounding things, 00:38:40.240 --> 00:38:45.680 but I'm just curious like if you have some anecdotal impression of that difference or yeah, 00:38:45.760 --> 00:38:50.960 I I mean the the the other surface differences are so big that it would be hard. 00:38:51.040 --> 00:38:53.760 But I think David Lawson put this in a nice way. 00:38:54.160 --> 00:38:59.570 Um struggle new student new anthropology students sometimes have in the the first time 00:38:59.570 --> 00:39:02.850 they're in the field uh is that they don't do enough. 00:39:03.010 --> 00:39:06.210 So when you're in the field, you have to also be cooperating. 00:39:06.290 --> 00:39:11.250 So whether that's contributing by like cleaning dishes or whatever, and it be it becomes 00:39:11.250 --> 00:39:15.810 really clear how important it is to contribute in that situation. 00:39:16.050 --> 00:39:20.290 Um where even even, you know, if I'm paying research assistants where, you know, here in 00:39:20.290 --> 00:39:23.180 the US, if I'm paying you, you know, that means that's your job. 00:39:23.260 --> 00:39:25.020 I'm not supposed to to help. 00:39:25.180 --> 00:39:27.820 Um you know, if I did that, that that wouldn't work, right? 00:39:27.900 --> 00:39:29.820 That would that would start fraying relationships. 00:39:29.900 --> 00:39:32.540 Um and so you feel it doing the actual work. 00:39:32.620 --> 00:39:37.260 It's like, oh, I have to be a member of this community and I have to really make sure that 00:39:37.260 --> 00:39:39.500 I'm contributing, that I'm I'm not replaceable. 00:39:39.660 --> 00:39:45.180 So that's how that's how I would say I I'd feel uh that difference really um you know it's 00:39:45.260 --> 00:39:48.430 it's never I I don't want to paint a picture of like a utopia. 00:39:48.510 --> 00:39:51.150 I mean Hadza have a very hard life. 00:39:51.230 --> 00:39:53.790 Um, you know, there's lots of dangers. 00:39:53.950 --> 00:39:58.990 Um, so it it's not like again a social utopia and there's all sorts of conflicts still that 00:39:58.990 --> 00:40:03.150 pop up, but uh there's definitely a difference in how you approach those relationships. 00:40:04.430 --> 00:40:04.670 Yeah. 00:40:06.110 --> 00:40:06.430 Cool. 00:40:06.560 --> 00:40:06.880 Yeah. 00:40:06.960 --> 00:40:11.040 I wonder, well, yeah, that's another I'll I'll leave it at that. 00:40:11.120 --> 00:40:16.240 It's just it's curious, it's an interesting thing to uh because uh obviously there's like a 00:40:16.240 --> 00:40:21.520 lot of advertising or sort of cultural um uh history of sort of 00:40:22.240 --> 00:40:26.880 uh you don't have to do the manual labor because you're higher class, right? 00:40:27.040 --> 00:40:32.880 Um and I think I even even sort of from working class to like working to uh white 00:40:33.040 --> 00:40:35.770 collar, that's a there's a difference there as well. 00:40:35.930 --> 00:40:41.690 Um and there's even ethnographies um like of just social class that sound very similar even 00:40:41.690 --> 00:40:42.170 within the West. 00:40:42.410 --> 00:40:46.810 So it's just an interesting it's interesting to kind of think about that similarity even if 00:40:46.810 --> 00:40:48.010 you even within the West. 00:40:48.170 --> 00:40:48.410 Yeah. 00:40:48.730 --> 00:40:49.290 Yeah, yeah. 00:40:49.370 --> 00:40:49.850 I agree. 00:40:50.010 --> 00:40:50.650 Yeah. 00:40:51.210 --> 00:40:55.930 Um I wanna there's another thing that that stuck with me that you mentioned, which is that 00:40:55.930 --> 00:41:01.860 people's cooperation levels um aren't really stable and that I might 00:41:01.860 --> 00:41:03.940 cooperate in one context, but not another context. 00:41:04.020 --> 00:41:08.900 And there's not like enduring character traits that you might have otherwise expected. 00:41:09.540 --> 00:41:14.740 You know, in the Western world, we really care a lot about character and like whether 00:41:14.740 --> 00:41:16.020 someone is a good person or not. 00:41:16.180 --> 00:41:20.820 And we view that as kind of an essence that's internal to that person and endures over 00:41:20.820 --> 00:41:21.140 time. 00:41:21.860 --> 00:41:26.190 And and what you're what you seem to be finding among the Hadza is that that's not really 00:41:26.190 --> 00:41:30.030 the case, that there aren't these enduring differences in in cooperativeness. 00:41:30.270 --> 00:41:33.630 Is that is that an oversimplification or is there more to it than that? 00:41:34.190 --> 00:41:36.510 It it gets a little more complicated. 00:41:36.670 --> 00:41:40.270 So uh with a public good game, we find no correlation across time. 00:41:40.510 --> 00:41:43.870 We do find a a moderate one when we play like a dictator game. 00:41:43.950 --> 00:41:46.670 So in that game, we've discovered that later. 00:41:46.830 --> 00:41:49.950 Um so it it part depends on how you measure. 00:41:50.030 --> 00:41:53.120 I mean, these are one-shot games, so there's al always a question like, what are they 00:41:53.120 --> 00:41:53.920 really measuring? 00:41:54.080 --> 00:41:58.560 We've also asked, so like when we rank people on, ask people to rank each other on 00:41:58.560 --> 00:42:02.400 something like generosity, you can also look at the agreement between judges. 00:42:02.480 --> 00:42:07.440 And so this is a method from personality psychology that if you get more agreement between 00:42:07.440 --> 00:42:10.960 people, that means they're behaving consistently across situations. 00:42:11.120 --> 00:42:13.520 And so we get really low consensus as well. 00:42:13.680 --> 00:42:18.480 So that that at least sort of triangulates that we do think that um cooperation, at least 00:42:18.640 --> 00:42:20.720 how they perceive it, might not be very stable. 00:42:20.990 --> 00:42:25.710 And so I did run a study, because you can think about interesting questions that that might 00:42:25.710 --> 00:42:30.430 raise, that if you don't have this belief that character is essential, how that might 00:42:30.430 --> 00:42:30.990 impact things. 00:42:31.150 --> 00:42:33.230 I mean, maybe punishment doesn't make sense, right? 00:42:33.390 --> 00:42:37.310 If you think uh people behave relative to the situation. 00:42:37.390 --> 00:42:42.110 And maybe some of the things again, like what Man Vier and Leo are arguing about uh sort of 00:42:42.110 --> 00:42:48.100 third party compensation and and uh sort of uh uh right reconciliation rather 00:42:48.100 --> 00:42:48.900 than punishment. 00:42:49.380 --> 00:42:55.140 Um and so I did run a study uh wanted to follow this up, where we 00:42:55.140 --> 00:43:00.900 asked folks, we gave them a situation, so something like um someone has a 00:43:01.300 --> 00:43:05.060 uh pot of honey and they walk away because they had to go take care of something. 00:43:05.220 --> 00:43:09.630 And when they come back, their honey's gone, and it's either two people took the honey. 00:43:09.710 --> 00:43:14.910 It was someone who's never stolen before but is really hungry, or someone who has stolen 00:43:14.910 --> 00:43:16.430 before but is very satiated. 00:43:16.510 --> 00:43:21.310 And we also had uh a flip side of like someone dropped, you know, gave he was really 00:43:21.310 --> 00:43:24.190 hungry, someone gave him honey and was someone who shared before. 00:43:24.350 --> 00:43:26.590 Um, you know, so we we sort of crossed that. 00:43:26.750 --> 00:43:32.620 And what we found was that for positive traits, so things like sharing, helping out, people 00:43:32.620 --> 00:43:34.780 did seem to have essentialist beliefs. 00:43:34.860 --> 00:43:38.060 So if we asked them who did it, they would say it was the person who has previously been 00:43:38.060 --> 00:43:38.780 helpful. 00:43:39.100 --> 00:43:45.100 For the negative behaviors, uh, it flips where people were more willing to attribute it to 00:43:45.100 --> 00:43:45.660 the situation. 00:43:45.740 --> 00:43:49.820 They were more likely to say it was this person who hasn't stolen before but is very 00:43:49.820 --> 00:43:50.460 hungry. 00:43:50.620 --> 00:43:54.810 Um, so it's sort of interesting that it really depends on, you know, sort of the polarity 00:43:54.810 --> 00:43:56.250 that you're asking about. 00:43:56.410 --> 00:44:00.250 Um, and and always wanted to follow that up to see, you know, what are the downstream 00:44:00.250 --> 00:44:04.890 effects of that on sort of willingness to punish or or willing to, you know, reconciliate 00:44:04.890 --> 00:44:05.450 with folks. 00:44:05.770 --> 00:44:09.610 That's that's really cool because I mean because I'm doing the free will stuff right now, 00:44:09.770 --> 00:44:10.810 going through the literature. 00:44:10.890 --> 00:44:16.010 And in a Western uh context, um it's the it's the opposite, right? 00:44:16.250 --> 00:44:20.520 Where um if somebody does something negative, it's it's attributed to their personality. 00:44:20.600 --> 00:44:25.720 And I mean, I I would view all of this the the underlying consistency is it's all about 00:44:25.720 --> 00:44:28.200 intervention and the practicality of intervention, right? 00:44:28.280 --> 00:44:33.640 So, like if you can, as David said, everybody's replaceable, you can like sort of leverage 00:44:33.640 --> 00:44:36.440 costs to be like, David, you really should do that differently. 00:44:36.520 --> 00:44:42.190 I can't change the circumstances, but if you can't do that, um, or if the b better way to 00:44:42.190 --> 00:44:47.870 change the situation is the the kind of context in which they were in, um, then that would 00:44:47.870 --> 00:44:49.550 be the the other pattern. 00:44:50.110 --> 00:44:50.270 Right. 00:44:50.510 --> 00:44:50.590 Right. 00:44:50.830 --> 00:44:55.630 So I I thought about those classic like the fundamental attribution uh misattribution 00:44:55.630 --> 00:44:56.190 error, right? 00:44:56.270 --> 00:44:58.670 Or uh right, uh it's the flip. 00:44:58.750 --> 00:45:01.870 People are attribute uh bad behaviors to to the personality. 00:45:02.110 --> 00:45:06.270 I wonder if you could do something like a cross-cultural study with relational mobility 00:45:06.350 --> 00:45:12.020 where maybe you can see the strength of that ref effect or the whether it reverses based on 00:45:12.020 --> 00:45:14.900 how replaceable folks are using that relational mobility measure. 00:45:15.220 --> 00:45:16.660 Yeah, or just any cost benefit. 00:45:16.900 --> 00:45:20.660 I mean, it's a little bit hand wavy, but I mean I would think that the argument would be 00:45:20.660 --> 00:45:25.060 that there's in the ecology, there's sort of every agent is doing this cost benefit 00:45:25.060 --> 00:45:30.470 analysis of say, if somebody cheats, what are the costs and benefits of doing something 00:45:30.470 --> 00:45:35.910 about that by trying to recalibrate them and saying, You're a bad person, you should have 00:45:35.990 --> 00:45:41.990 you should do differently in the future, versus in this situation, this person did this. 00:45:42.150 --> 00:45:44.950 The thing that needs to change is the situation. 00:45:45.110 --> 00:45:49.670 Um, you know, like and I think yeah, I think that's even true for us too. 00:45:49.830 --> 00:45:52.950 Like there's just certain situations where you look at somebody and you're like, I'm not 00:45:52.950 --> 00:45:54.950 gonna be able to change that person's decision. 00:45:55.140 --> 00:45:58.900 we're gonna have to change the context versus we're gonna change the con, you know, so um, 00:45:59.060 --> 00:46:00.660 or I can change their their mind. 00:46:00.740 --> 00:46:05.940 And I think there's just costs and benefits uh cross-culturally, cross uh with the across 00:46:05.940 --> 00:46:07.060 people, like even in our lives. 00:46:07.140 --> 00:46:10.180 There's probably people you're like, Well, I'm not gonna change their mind, I'm gonna 00:46:10.180 --> 00:46:12.580 change the situation, you know, even for us. 00:46:12.660 --> 00:46:12.980 Yeah. 00:46:13.540 --> 00:46:13.700 Yeah. 00:46:14.100 --> 00:46:14.340 Yeah. 00:46:14.420 --> 00:46:16.660 I mean, it makes me think of some of the anger work, right? 00:46:16.740 --> 00:46:22.730 Uh, the idea that like the more uh the the higher expected WTR rate uh you 00:46:22.730 --> 00:46:26.410 have that you expect people to treat you better, you get angrier when you don't. 00:46:26.570 --> 00:46:30.330 I do wonder if that also means you'll get differences in like expressions of anger, right? 00:46:30.410 --> 00:46:35.370 If people have different methods to calibrate in different ecologies based on 00:46:35.370 --> 00:46:39.290 replaceability, then you might see differences in how anger is expressed towards these 00:46:39.290 --> 00:46:43.460 things as well, because you know, they're not going to recalibrate by imposing costs, but 00:46:43.460 --> 00:46:44.340 by doing something else. 00:46:44.420 --> 00:46:48.340 And so you might see differences even in how anger is expressed. 00:46:48.660 --> 00:46:51.300 But again, via these sort of universal mechanisms, right? 00:46:51.380 --> 00:46:54.260 That uh are just interacting with their local ecology. 00:46:54.580 --> 00:46:55.460 Yeah, that's super interesting. 00:46:55.700 --> 00:46:58.420 It's a great, yeah, it's a great example of the contingency point, right? 00:46:58.500 --> 00:46:58.820 Yeah. 00:46:59.220 --> 00:46:59.460 Right. 00:46:59.620 --> 00:47:00.980 I mean, uh, it's interesting. 00:47:01.060 --> 00:47:05.790 I I interpreted this um slightly differently, I mean this probably comes from my 00:47:05.790 --> 00:47:09.230 background, but um there's there's a lot of literature showing that people have 00:47:09.230 --> 00:47:13.470 attributional biases uh contingent on group membership or or alliances. 00:47:13.710 --> 00:47:18.750 So um if a fellow group member or ally uh does something bad, I'm going to attribute it to 00:47:18.750 --> 00:47:19.230 the situation. 00:47:19.310 --> 00:47:23.470 But if an outgroup or a rival does something bad, I'm going to attribute it to their 00:47:23.470 --> 00:47:24.430 personality, right? 00:47:24.510 --> 00:47:28.350 And you could see that as a kind of strategic bias where I want to, you know, mobilize 00:47:28.350 --> 00:47:31.310 opposition to my enemies and support for my allies. 00:47:31.470 --> 00:47:36.560 And it could be that in a tight knit community like the Hadza, everyone views uh every 00:47:36.560 --> 00:47:40.960 other member as a kind of, you know, crucial ally or at least highly interdependent. 00:47:41.040 --> 00:47:44.640 And that might cause these strategic biases to come into play where they're willing to 00:47:44.640 --> 00:47:47.840 discount or um uh minimize the transgression. 00:47:48.000 --> 00:47:51.280 At least that's that's where my mind went in in in hearing about this stuff. 00:47:51.520 --> 00:47:55.750 It would be interesting to see if they have similar attributional biases about, say, um a 00:47:55.830 --> 00:47:59.190 an outgroup or or a view that they've a group that they view negatively. 00:47:59.270 --> 00:48:03.430 I don't know if that exists on in in Hadza land, but it would be an interesting question to 00:48:03.430 --> 00:48:03.910 ask. 00:48:04.230 --> 00:48:07.030 Yeah, uh I I think that's a good point, right? 00:48:07.110 --> 00:48:09.910 And you can think of sort of the different mediating mechanisms here, right? 00:48:09.990 --> 00:48:14.070 So like first comes like group uh membership and identification and then you're making 00:48:14.150 --> 00:48:15.910 making your uh attributions that way. 00:48:15.990 --> 00:48:20.710 And and to your point, like I think all Hadza see all other Hadza as in group members, even 00:48:20.950 --> 00:48:21.830 if they're in different camps. 00:48:21.910 --> 00:48:26.400 These aren't really important social groupings, but maybe some of their neighboring 00:48:26.400 --> 00:48:28.320 populations, we could we could test that, right? 00:48:28.400 --> 00:48:32.960 And see if they're uh switching those biases, which would be super fascinating. 00:48:33.360 --> 00:48:35.120 Yeah, for sure. 00:48:35.440 --> 00:48:40.640 You also mentioned the WTR, the the this idea of the welfare trade-off ratio where the 00:48:40.640 --> 00:48:45.680 amount of costs I'm willing to inflict on you to get a benefit for myself is this this 00:48:45.680 --> 00:48:50.800 variable, and anger is a response to a low welfare trade-off ratio where you inflict a 00:48:50.800 --> 00:48:55.670 really big cost on me to get a really small benefit for you, like say I have a really fancy 00:48:55.670 --> 00:48:59.750 tie uh uh and you take my tie and you wipe the ketchup off your face with it. 00:48:59.910 --> 00:49:02.870 Like you're getting a really small benefit for yourself and you're ruining my tie. 00:49:02.950 --> 00:49:04.870 I would get really pissed off, right? 00:49:05.190 --> 00:49:10.470 Um at least that's my favorite example of of a of an anger-inducing situation. 00:49:10.710 --> 00:49:16.480 Um but i has anyone tried to measure uh welfare trade-off ratios 00:49:16.480 --> 00:49:21.120 in uh either either you know the Hadza or small scale society or any any place outside the 00:49:21.120 --> 00:49:21.600 Western world? 00:49:21.760 --> 00:49:25.600 Because I know this method has become increasingly common in evolutionary psychology of 00:49:25.600 --> 00:49:27.120 measuring these WTRs. 00:49:27.200 --> 00:49:30.800 Has anyone l tried to extend this to to different cultures and ecologies? 00:49:31.280 --> 00:49:37.230 I think Andy Delton has a paper with um I 00:49:37.230 --> 00:49:38.350 think it's among the Schwar. 00:49:38.670 --> 00:49:40.830 He's it's an anthropologist that works. 00:49:41.470 --> 00:49:44.590 It's in the 2020 uh weird special issue of EHB. 00:49:44.830 --> 00:49:47.230 Oh you I've also seen it. 00:49:47.310 --> 00:49:50.030 It's not, you know, it that uh task. 00:49:50.190 --> 00:49:53.790 So usually the the task used to measure welfare trade off ratio, right, is to ask like, 00:49:53.950 --> 00:49:58.430 would you rather have X amount of dollars yourself or Y amount of dollars for this other 00:49:58.430 --> 00:49:58.750 person? 00:49:58.910 --> 00:50:03.060 You know, that's also known as other things in the literature, so like social discounting. 00:50:03.140 --> 00:50:07.060 So, like Dan Harushka has done social discounting, I know, in Bangladesh. 00:50:07.300 --> 00:50:10.820 Um, and I remember he had challenges adapting that protocol. 00:50:10.980 --> 00:50:16.180 He has a couple of papers talking about that that challenge of adapting the protocol um and 00:50:16.180 --> 00:50:17.860 how people were understanding it. 00:50:17.940 --> 00:50:21.060 And I think he doesn't find the usual effect. 00:50:21.220 --> 00:50:25.060 So usually what you find is that people have the highest welfare trade-off ratios for 00:50:25.060 --> 00:50:26.790 people that they feel closest to. 00:50:27.030 --> 00:50:29.030 Um, I think he doesn't actually find that. 00:50:29.110 --> 00:50:32.790 I think need uh overrides the effect in those communities. 00:50:32.950 --> 00:50:34.950 So people are more willing to help those. 00:50:35.110 --> 00:50:39.830 And so again, I think the way to think about that is that the method, the measurement is 00:50:39.830 --> 00:50:41.590 interacting with the ecology as well. 00:50:41.830 --> 00:50:46.550 And has some of this too with some of the parochial altruism stuff, finding that in some 00:50:46.550 --> 00:50:52.360 communities, because there are the stereotypes of some uh communities being more or less 00:50:52.440 --> 00:50:58.440 uh high higher or lower SES or more need, that you'll get people sharing more cross-group 00:50:58.440 --> 00:51:01.960 boundaries, but really what's driving it is this perception of of need. 00:51:02.120 --> 00:51:06.920 Um so yeah, again, thinking that there's a lot of care that has to go into adapting these 00:51:06.920 --> 00:51:11.800 methods to make sure that they're understood the same way we think they're understanding 00:51:11.800 --> 00:51:12.120 it. 00:51:12.690 --> 00:51:13.170 Yeah. 00:51:13.410 --> 00:51:15.250 Why does why do things have to be so complicated? 00:51:17.490 --> 00:51:19.650 Well that that's what makes humans so interesting, right? 00:51:19.970 --> 00:51:20.370 I know. 00:51:20.690 --> 00:51:21.330 I know. 00:51:21.810 --> 00:51:23.330 Yeah, no, I mean it makes sense. 00:51:33.020 --> 00:51:36.940 pretty easy to think about, you know, I'm going to give up some money for my friend to get 00:51:36.940 --> 00:51:37.420 some money. 00:51:37.660 --> 00:51:41.900 Whereas if you're living at subsistence, you know, and you're talking about a critical 00:51:41.900 --> 00:51:45.340 resource, uh, the the game is is just totally different, right? 00:51:45.820 --> 00:51:49.820 Yeah, well I I think if there's there's even more to that even within so one of my first 00:51:49.820 --> 00:51:54.940 research research experiences was working with Dan Harushka on this social discounting task 00:51:55.020 --> 00:52:01.020 and he wanted to test it in community members uh in Phoenix and Tempe uh as sort of just 00:52:01.020 --> 00:52:01.890 to get a feel for it. 00:52:01.970 --> 00:52:06.770 So I'd go out to do these surveys where you give them these welfare trade-off ratio tasks. 00:52:06.850 --> 00:52:11.650 So they they rank who they feel like first, second, fifth, and tenth closest, I think, 00:52:11.730 --> 00:52:13.010 maybe went out further. 00:52:13.170 --> 00:52:16.290 They do this welfare trade-off ratio task. 00:52:16.930 --> 00:52:21.570 And I remember interviewing one woman who was pregnant and she had a young child with her 00:52:21.570 --> 00:52:22.130 as well. 00:52:22.450 --> 00:52:26.980 The person she felt closest to was her fetus, which makes total sense. 00:52:27.060 --> 00:52:30.340 She's like literally physically closest to this person. 00:52:30.740 --> 00:52:34.100 Um, and of course, she gives nothing to the fetus because that would be silly and 00:52:34.100 --> 00:52:35.620 ridiculous to do. 00:52:35.860 --> 00:52:40.340 Um, and so she doesn't have she didn't have this really clean social discounting line 00:52:40.500 --> 00:52:43.540 because uh, you know, she's considering other variables here. 00:52:43.700 --> 00:52:48.820 I remember one uh guy I interviewed, he ranked his cat as the twentieth closest person. 00:52:49.060 --> 00:52:50.870 Um it's very specific. 00:52:51.190 --> 00:52:54.790 Well, I I and and you know, I I thought about it and I was like, I'd probably put my pets 00:52:54.790 --> 00:52:57.110 around there too, maybe maybe even a little closer. 00:52:57.270 --> 00:53:00.470 And again, he gave nothing to his cat because that would be. 00:53:00.870 --> 00:53:02.390 Yeah, what's the cat gonna do with the money? 00:53:02.550 --> 00:53:02.710 Yeah. 00:53:02.950 --> 00:53:03.190 Yeah. 00:53:03.350 --> 00:53:05.910 Um opposable, no opposable thumbs. 00:53:06.630 --> 00:53:11.830 Uh uh, maybe you could operate the keyboard and order something off Amazon, but uh right, 00:53:11.900 --> 00:53:12.140 right. 00:53:12.300 --> 00:53:17.020 So even you don't have to go to another culture, even when we, you know, we're so used, I 00:53:17.020 --> 00:53:22.300 think, to interacting with undergraduates and participants online who in some ways are 00:53:22.300 --> 00:53:25.180 professional participants who are used to doing all these tasks. 00:53:25.340 --> 00:53:28.060 Um, that I think it impacts how they're interpreting that. 00:53:28.140 --> 00:53:33.260 And I again taking the time to see how are people understanding that task, even when you're 00:53:33.260 --> 00:53:36.780 working within your own cultures, I I think really key. 00:53:37.310 --> 00:53:37.550 Yeah. 00:53:37.630 --> 00:53:42.670 I mean, do you think it's uh has something to do with the level of abstraction and 00:53:42.670 --> 00:53:47.710 hypotheticality that we're accustomed to in in the Western world, where we have this 00:53:47.710 --> 00:53:52.190 education system that we're put through where we're we're forced to sort of decouple things 00:53:52.190 --> 00:53:57.230 from their concrete reality and think about, you know, abstractions and hypothetical 00:53:57.230 --> 00:54:01.480 arrangements of different things, And all of our questionnaires sort of rely on this to 00:54:01.560 --> 00:54:06.840 like entertain this hypothetical situation that may not ever happen in in real life and to 00:54:06.840 --> 00:54:11.720 sort of uh extrapolate, you know, what you would do in this hypothetical situation. 00:54:11.880 --> 00:54:15.560 And when you try to bring that into the Hadza land, they they're they're thinking about the 00:54:15.560 --> 00:54:17.960 concrete realities that they have to deal with. 00:54:18.120 --> 00:54:21.550 And you know if you ask them, you know, how much money are you going to give to your fetus? 00:54:21.630 --> 00:54:22.830 They're like, what are you talking about? 00:54:22.910 --> 00:54:24.910 Like my fetus, you can't spend any money. 00:54:25.150 --> 00:54:28.910 Like, whereas in the Western world, be like, oh yeah, in a hypothetical world, I would give 00:54:28.910 --> 00:54:29.790 the most to my fetus. 00:54:29.950 --> 00:54:34.030 But no, like they're thinking about you know their concrete realities and taking the the 00:54:34.030 --> 00:54:36.830 measures that you're giving them at face value and taking them literally. 00:54:36.990 --> 00:54:42.830 Um could that you know um explain potentially some of these difficulties 00:54:42.910 --> 00:54:47.390 and and just the the the level of comfort with these kind of abstract hypothetical 00:54:47.390 --> 00:54:48.030 questions? 00:54:48.640 --> 00:54:53.120 Yeah, or or putting numbers to fillings, which I think is actually really weird and we do 00:54:53.120 --> 00:54:54.080 it all the time. 00:54:54.320 --> 00:54:59.520 Uh yeah, I I think there are folks who are working on this problem of like how education is 00:54:59.520 --> 00:55:03.440 impacting cog obviously there are people working on that, but I think there's evolutionary 00:55:03.440 --> 00:55:06.800 anthropologists who are trying to think about like what what does this really mean? 00:55:06.960 --> 00:55:08.880 What what does the impact of schooling have? 00:55:09.120 --> 00:55:14.470 I'll say that it is so easy to know who has had some schooling in Hadza Land and who 00:55:14.630 --> 00:55:17.030 doesn't based on how they interact with the tasks. 00:55:17.190 --> 00:55:22.630 And some of it's not just abstraction, it's the very idea of sitting down to do a task that 00:55:22.630 --> 00:55:27.190 doesn't have any real impact uh you know in their lives. 00:55:27.510 --> 00:55:30.710 Um so I I definitely think that's that's part of it. 00:55:30.870 --> 00:55:35.110 Uh I've heard I've heard stories from so many folks uh in the field when they've tried to 00:55:35.110 --> 00:55:40.640 do tasks and they totally get an unexpected result because they they just understood it 00:55:40.640 --> 00:55:46.480 differently or they were thinking about a very specific context um from you know folks who 00:55:46.480 --> 00:55:48.640 are asked to give money to like friends. 00:55:48.880 --> 00:55:54.640 Uh and this was another interview at ASU where uh two people came in, they they and 00:55:54.640 --> 00:55:56.480 one person was completely selfish. 00:55:56.640 --> 00:56:00.960 But then immediately after, like we overheard him saying, like, Oh, I'm gonna pay for your 00:56:00.960 --> 00:56:01.360 lunch. 00:56:01.440 --> 00:56:03.280 Uh let's let's go grab lunch together. 00:56:03.520 --> 00:56:07.710 And it it's, you know, is I I think a lot of evolutionary psychologists are like, well, 00:56:07.790 --> 00:56:08.910 there's some status signaling, right? 00:56:08.990 --> 00:56:12.190 They want to be able to like control where those those resources are going. 00:56:12.350 --> 00:56:15.630 But also it does seem kind of generous, uh, on the other hand. 00:56:15.790 --> 00:56:17.390 So uh interesting. 00:56:17.630 --> 00:56:21.950 Yeah, again, I I just rather than giving the money to his friend directly, he took it for 00:56:21.950 --> 00:56:23.790 himself and then took his friend out to lunch. 00:56:24.110 --> 00:56:24.510 Exactly. 00:56:24.590 --> 00:56:24.830 Yeah. 00:56:25.150 --> 00:56:25.710 Interesting. 00:56:26.020 --> 00:56:29.780 Um which, you know, again, probably, you know, you get some control over what food you get, 00:56:29.860 --> 00:56:32.180 you get some of the reputation benefit you might not get. 00:56:32.340 --> 00:56:37.700 But um yeah, just that that people are are complicated, right? 00:56:37.780 --> 00:56:39.540 Uh as they think about these tasks. 00:56:39.700 --> 00:56:44.580 And um I I find it fun to hear these stories and think about how people are thinking about 00:56:44.580 --> 00:56:47.460 these different uh you know experiments that they're doing. 00:56:47.850 --> 00:56:48.810 Yeah, for sure. 00:56:48.970 --> 00:56:52.650 As if people, yeah, as if the the challenge of understanding complicated humans weren't 00:56:52.650 --> 00:56:53.290 challenging enough. 00:56:53.610 --> 00:56:57.130 We also have this problem of measurement and like how we measure the things that we're 00:56:57.130 --> 00:57:01.610 actually trying to measure, uh, particularly in a very different culture that isn't used to 00:57:01.610 --> 00:57:06.090 being uh to sitting down and doing a task that doesn't have any immediate practical 00:57:06.090 --> 00:57:06.650 benefit. 00:57:06.730 --> 00:57:08.010 Um it's it's a huge challenge. 00:57:08.090 --> 00:57:11.690 It's amazing that you know we've we've gotten stuff done at all and we've learned anything 00:57:11.690 --> 00:57:11.930 at all. 00:57:12.090 --> 00:57:15.770 Like it's uh it's a real credit to the to the work that you and others have have been 00:57:15.770 --> 00:57:16.410 doing. 00:57:17.260 --> 00:57:21.260 Yeah, and I think it's a benefit of taking an evolutionary approach and doing anthropology 00:57:21.340 --> 00:57:21.580 too. 00:57:21.660 --> 00:57:25.580 I mean, that's just to follow up on what David is saying is that I think there's a lot of 00:57:25.580 --> 00:57:30.620 areas in psychology where the measure becomes the data, becomes the theory. 00:57:31.020 --> 00:57:36.380 And so you just sort of you just say, like this number as a result of this method is the 00:57:36.380 --> 00:57:37.420 psychology. 00:57:37.570 --> 00:57:41.970 Um, and if you don't have an idea of, well, we're trying to figure out the evolved 00:57:41.970 --> 00:57:45.730 psychology, or you don't have this idea of I'm gonna go to the field and see, you know, I 00:57:45.730 --> 00:57:49.890 can't just assign this a number, like the kids gotta eat, the person's gotta live, they 00:57:50.050 --> 00:57:50.610 gotta move. 00:57:50.690 --> 00:57:53.650 Um, you know, like what are the what does the measure actually mean? 00:57:53.730 --> 00:57:55.490 Um, it kind of keeps you honest. 00:57:55.650 --> 00:58:01.090 Um and yeah, I think a lot of the history of psychology has been codifying 00:58:01.090 --> 00:58:06.930 measures as uh as like real things as opposed to um, you 00:58:06.980 --> 00:58:10.500 know, guesses or clues about the underlying psychology. 00:58:10.580 --> 00:58:15.380 And it's really bad just to like just to just to like because a lot of times people will 00:58:15.380 --> 00:58:16.420 will operationalize. 00:58:16.580 --> 00:58:20.580 I operationalize a construct of like selfishness with like, do they cooperate in this like 00:58:20.580 --> 00:58:21.540 prisoner's dilemma? 00:58:21.700 --> 00:58:25.460 And then they'll report the studies like people are more selfish here than this, and then 00:58:25.460 --> 00:58:29.780 that's what people pick up on, as opposed to no, it's that in this game among these 00:58:29.780 --> 00:58:30.660 participants. 00:58:30.900 --> 00:58:35.300 So, like, even just like the the the labels or the inference, it's like a game of 00:58:35.300 --> 00:58:36.260 telephone. 00:58:37.310 --> 00:58:37.550 Yeah. 00:58:37.710 --> 00:58:38.590 Uh and to your point. 00:58:38.670 --> 00:58:42.510 And right, we'll cite it later, like, oh, people cooperate X and then as you go through the 00:58:42.510 --> 00:58:47.310 citations and then you go back and read it and you're like, oh, that this was not like and 00:58:47.390 --> 00:58:51.470 maybe you don't even think it's a measurement of cooperation now where the theory's taken 00:58:51.470 --> 00:58:51.630 us. 00:58:51.870 --> 00:58:54.510 And and yeah, to your point, I I I think that's important. 00:58:54.830 --> 00:59:00.510 Um I I'm less interested in theory development right now myself compared to where I was in 00:59:00.510 --> 00:59:05.280 grad school, but it's still really important in thinking about this research, uh, because 00:59:05.520 --> 00:59:08.000 you could also easily get lost in the field, right? 00:59:08.080 --> 00:59:12.400 If you have all these different observations, still having a strong theoretical background, 00:59:12.480 --> 00:59:13.760 especially in evolution. 00:59:13.840 --> 00:59:18.800 I guess we're preaching to the choir here, um, is really important for helping to organize 00:59:18.800 --> 00:59:19.120 that. 00:59:19.280 --> 00:59:23.200 Um, you know, I still want to be open to discovery while I'm doing field work. 00:59:23.280 --> 00:59:27.870 And, you know, I I've had have this chapter in the Oxford handbook where I make the case 00:59:27.870 --> 00:59:33.070 that we don't want to have theory blind us and not just realize that there might be domains 00:59:33.070 --> 00:59:36.830 of psychology that we're just not even thinking about because we're only thinking about 00:59:36.830 --> 00:59:38.830 undergrads and and hunter-gatherers. 00:59:39.070 --> 00:59:43.870 Um, but uh still keeping in mind that, you know, psychology is functional. 00:59:44.030 --> 00:59:47.870 It has a very particular kind of function, and thinking about what that function is is is 00:59:47.950 --> 00:59:51.310 still helpful for organizing all those different observations. 00:59:51.640 --> 00:59:52.680 Yeah, I like that a lot. 00:59:52.760 --> 00:59:57.320 I also would put it as like there's a difference between theory as tradition versus theory 00:59:57.320 --> 01:00:01.560 as the ability to say, hey, hang on, we haven't looked at X or Y or Z. 01:00:01.960 --> 01:00:05.880 And I think that those are very different uh kinds of theorizing. 01:00:06.040 --> 01:00:11.560 And I think especially psychology has not done a good job of accepting 01:00:11.560 --> 01:00:17.310 speculation or like people saying, look, we haven't accounted for X, Y, or Z because 01:00:17.310 --> 01:00:18.590 there's no data for it, right? 01:00:18.910 --> 01:00:19.070 Right. 01:00:19.230 --> 01:00:20.590 There's no fancy data. 01:00:21.150 --> 01:00:26.910 And so this is another one of my soapboxes, which is that if theory is the stuff 01:00:26.910 --> 01:00:32.030 that has data and lots of evidence, then you're never going to actually look at the missing 01:00:32.030 --> 01:00:32.430 pieces. 01:00:32.510 --> 01:00:32.990 Yeah. 01:00:33.390 --> 01:00:33.630 Yeah. 01:00:33.710 --> 01:00:37.710 I I think there's formal modeling work in like philosophy of science trying to show like 01:00:37.710 --> 01:00:40.700 it's it's um uh streetlight effect, right? 01:00:40.780 --> 01:00:42.220 Like exactly your theory, your theory. 01:00:42.620 --> 01:00:43.340 Yeah, that's great. 01:00:43.420 --> 01:00:47.660 I actually knew after this episode, you have to like please send me that reference because 01:00:47.820 --> 01:00:49.820 uh uh yeah, that would be great. 01:00:50.060 --> 01:00:50.780 Yeah, of course. 01:00:50.860 --> 01:00:51.100 Yeah. 01:00:51.260 --> 01:00:55.340 Um it it's that old joke like uh the the drunk looking for their keys under the 01:00:55.340 --> 01:00:55.980 streetlight, right? 01:00:56.140 --> 01:01:01.650 So if theory focuses too quickly, then you're not uh open to sort of the 01:01:01.650 --> 01:01:03.490 possibilities about other observations. 01:01:03.890 --> 01:01:04.210 Exactly. 01:01:04.370 --> 01:01:07.970 And so to your point, is like if you're in the field and you're like, look, our theories 01:01:07.970 --> 01:01:09.570 are blinding us to this whole other thing. 01:01:09.730 --> 01:01:14.130 I would argue like that's a kind of theory, but it's a very different kind of theory than 01:01:14.130 --> 01:01:15.570 the theory that was blinding you. 01:01:15.730 --> 01:01:15.810 Right. 01:01:16.130 --> 01:01:16.290 Right. 01:01:16.610 --> 01:01:17.890 Yeah, I think that's a good way to put it. 01:01:18.290 --> 01:01:18.370 Right. 01:01:18.610 --> 01:01:22.690 And uh the similar problem with, you know, we're only looking at the stuff that is easy to 01:01:22.690 --> 01:01:27.180 measure or convenient to measure rather than the full range of stuff that we're interested 01:01:27.180 --> 01:01:27.340 in. 01:01:27.420 --> 01:01:29.900 You know, we're looking at the stuff that we can put a number on. 01:01:30.060 --> 01:01:34.460 Um, but not everything of interest uh is that easily measurable. 01:01:34.620 --> 01:01:39.820 And the stuff that we have, you know, well-tested measures for is not the full range of of 01:01:39.820 --> 01:01:42.140 stuff that exists in the world. 01:01:43.180 --> 01:01:46.780 So yeah, I think to that point, like I think just the value of just straight-up 01:01:46.780 --> 01:01:51.750 ethnography, just people living in a community and just writing qualitatively about their 01:01:51.750 --> 01:01:55.590 experiences and reporting on anecdotes like the anecdotes that you shared with us. 01:01:55.750 --> 01:01:59.190 I think that is uh tremendously valuable and underrated, I think. 01:01:59.670 --> 01:02:03.590 Yeah, it's it's definitely uh something I I'm trying to push in that chapter I mentioned 01:02:03.670 --> 01:02:09.190 that we should ha be more open to uh ethnographic approaches in cross-cultural 01:02:09.190 --> 01:02:11.990 psychology, especially cross-cultural evolutionary psychology. 01:02:12.150 --> 01:02:15.740 And again, you don't want to fall into the trap of cultural anthropologists who will only 01:02:15.740 --> 01:02:17.500 do thick description, right? 01:02:17.580 --> 01:02:22.860 You still want to eventually move this to a frame, a generalizable theoretical framework. 01:02:23.180 --> 01:02:27.900 But yeah, I mean, I've I've got a couple of projects in the pipeline right now that are 01:02:28.140 --> 01:02:31.820 it's crazy for me to think about this that are just completely qualitative, that it was 01:02:31.820 --> 01:02:33.420 interviews and focus groups. 01:02:33.500 --> 01:02:37.820 Um, especially as someone who like has prided himself on some of my statistics. 01:02:37.980 --> 01:02:41.500 Uh, it's really weird to be writing these papers where, because again, to your point, like 01:02:41.580 --> 01:02:46.070 sometimes you can't get an accurate measurement, and sometimes the observation itself can 01:02:46.070 --> 01:02:51.270 be a value and you know maybe we'll develop that measurement later maybe you know uh 01:02:51.590 --> 01:02:56.230 whatever but uh at least having those observations out there uh in the first place can be 01:02:56.230 --> 01:02:56.950 really helpful. 01:02:57.270 --> 01:03:01.590 Yeah I feel like I've learned more from just the anecdotes that anthropologists have told 01:03:01.590 --> 01:03:04.150 me about you know life in the field and with these people. 01:03:04.310 --> 01:03:08.140 I've just learned more and and developed better intuitions about it than with any 01:03:08.140 --> 01:03:09.100 particular data point. 01:03:09.420 --> 01:03:13.260 Not to say the data isn't valuable, but I think it ought to be balanced with, you know, 01:03:13.420 --> 01:03:15.100 real life experience as well. 01:03:15.500 --> 01:03:15.740 Yeah. 01:03:16.060 --> 01:03:19.660 Well, I've I've had the experience uh on the fisheries work. 01:03:19.820 --> 01:03:25.740 I visited, I did, I think like 200 interviews down south in Tanzania 01:03:25.820 --> 01:03:27.020 as like pilot work. 01:03:27.180 --> 01:03:31.370 And then we did like 1400 surveys and another 200 interviews. 01:03:31.850 --> 01:03:36.570 And what we were testing was whether or not having more friendships in villages that access 01:03:36.570 --> 01:03:40.250 the same fisheries, if you're more likely to participate in fishery management. 01:03:40.330 --> 01:03:45.610 The idea being that you create stake both in your friend and in the resource you share. 01:03:45.770 --> 01:03:48.970 And so you're more willing to protect it was the basic idea. 01:03:49.210 --> 01:03:54.580 And I remember we did all these interviews, and I wasn't surprised when the survey came 01:03:54.580 --> 01:03:59.060 back supporting that view because it it came out in the interviews all the time. 01:03:59.300 --> 01:04:02.660 Now, you know, the careful measurement means we we were able to compare different effect 01:04:02.660 --> 01:04:03.060 sizes. 01:04:03.220 --> 01:04:04.900 There's other things that are really important. 01:04:05.140 --> 01:04:07.700 We got some specificity that it's not all friends. 01:04:07.780 --> 01:04:10.260 It is specifically friends in these other communities. 01:04:10.340 --> 01:04:11.860 Um there's benefit to that. 01:04:11.940 --> 01:04:16.010 But even again, it was just weird that the the surveys felt like, oh, I have to do this to 01:04:16.010 --> 01:04:20.410 prove it to other people, but the interviews I I was already uh fairly convinced it was was 01:04:20.490 --> 01:04:22.730 gonna pop up and and that happens a lot. 01:04:23.050 --> 01:04:23.290 Yeah. 01:04:23.450 --> 01:04:24.890 No, that that's the best kind of work. 01:04:24.970 --> 01:04:28.650 That's you know, you have you have the data for there who for for people who are, you know, 01:04:28.890 --> 01:04:32.810 picky and skeptical, but you know, just it it's it's built on the foundation of actually 01:04:32.810 --> 01:04:36.570 talking to people and and listening to their experiences and so that you know that it's the 01:04:36.570 --> 01:04:41.580 data aren't, you spurious or a result of some bad measurement, like you actually have you 01:04:41.580 --> 01:04:45.980 know a real connection to the people and understand what's going on at the ground level as 01:04:45.980 --> 01:04:46.300 well. 01:04:46.860 --> 01:04:48.220 So yeah. 01:04:48.380 --> 01:04:52.860 I blame uh having to have deliverables to funding agencies. 01:04:53.020 --> 01:04:55.820 We should say, I don't know what I'm gonna do. 01:04:56.220 --> 01:05:01.660 Uh um and if I have an agenda, uh you should be suspicious of me. 01:05:01.820 --> 01:05:02.460 Yeah. 01:05:03.660 --> 01:05:07.850 Uh I I mean th this comes up a lot in training anthropology students. 01:05:07.930 --> 01:05:12.410 Uh I I've had conversations with students who who feel that way who also want to do like 01:05:12.410 --> 01:05:13.370 community engaged work. 01:05:13.450 --> 01:05:17.530 And so in anthropology, there's a real push to like actually work with the community to 01:05:17.530 --> 01:05:22.730 identify research questions that matter to them as well as your own research questions. 01:05:22.890 --> 01:05:27.300 And so a lot of students are like, well, how do I go to the granting agencies without a 01:05:27.300 --> 01:05:27.620 plan. 01:05:28.020 --> 01:05:31.380 And it's the reality is you still do have a plan, right? 01:05:31.700 --> 01:05:37.140 Uh um and so trying to train students that like the the plan has to be, you know, 01:05:37.380 --> 01:05:40.820 morph and and and adjustable, but you need a plan going in. 01:05:41.140 --> 01:05:45.940 Um if you you really can't just go out there into the community and just sit there and 01:05:45.940 --> 01:05:46.340 learn. 01:05:46.420 --> 01:05:48.330 Like the you need some direction. 01:05:48.490 --> 01:05:53.210 But uh to your point though, I think uh outside of anthropology granting agencies, they 01:05:53.210 --> 01:05:57.610 want a bit more specificity in like what hypotheses you're testing and things of that 01:05:57.610 --> 01:05:58.170 nature. 01:05:58.650 --> 01:05:59.290 Yes. 01:06:01.130 --> 01:06:01.450 Cool. 01:06:01.610 --> 01:06:06.730 Uh so there's um So the the wife murderer uh keeps keeps sticking in my head. 01:06:07.530 --> 01:06:09.210 Maybe I'm just like obsessed with true crime. 01:06:09.370 --> 01:06:11.690 I think the when we had the Brenda Bowser episode, I could start. 01:06:12.010 --> 01:06:13.130 Oh, the death by Phantasm. 01:06:13.690 --> 01:06:14.570 Yeah, that was great. 01:06:14.860 --> 01:06:19.020 Any any story of of murder in in one of these communities always just sticks with me. 01:06:19.180 --> 01:06:24.300 Um, but uh I I remember you mentioned, you know, work with um uh Leo Fatucci and Man 01:06:24.460 --> 01:06:29.500 Versing on compensation and conflict mediation as an alternative to punishment. 01:06:29.660 --> 01:06:33.180 And especially in a community where everyone is really interdependent and vital, it's much 01:06:33.180 --> 01:06:38.060 more important to repair uh the the cooperation between the two disputants than it is to 01:06:38.060 --> 01:06:42.140 punish or exclude one of the disputants because that, you know, uh excludes a really 01:06:42.140 --> 01:06:43.020 valuable partner. 01:06:43.190 --> 01:06:47.270 And so it's much more important to restore cooperation, mediate the conflict, bring people 01:06:47.270 --> 01:06:51.270 together, uh, than it is to inflict costs, which is what we're so used to in the Western 01:06:51.270 --> 01:06:55.270 world where we just send people off to prison or or whatever, so we don't have to deal with 01:06:55.270 --> 01:06:55.510 them. 01:06:55.750 --> 01:06:58.470 Um so back to the wife murderer. 01:06:58.950 --> 01:07:04.790 Did did his did did the um did the per the wife who was murdered did was 01:07:04.950 --> 01:07:07.110 there any compensation given to the family? 01:07:07.270 --> 01:07:11.750 Um was there any kind of conflict mediation as a result of this, or do you not remember the 01:07:11.750 --> 01:07:12.470 details? 01:07:13.260 --> 01:07:14.780 I'm not aware of the details. 01:07:14.860 --> 01:07:17.580 So I didn't ask too many questions about this. 01:07:18.060 --> 01:07:20.780 I wasn't sure if it was appropriate or not. 01:07:20.860 --> 01:07:23.900 And so a lot of this is hearing from other folks. 01:07:26.540 --> 01:07:31.900 Like I said, the aunt of the mother of the woman who was murdered was very upset. 01:07:32.060 --> 01:07:35.580 Like she in the interview was like, this guy's terrible. 01:07:36.630 --> 01:07:39.350 The uncle actually did not have strong feelings. 01:07:39.830 --> 01:07:42.070 Funny enough, was the aunt specifically. 01:07:43.350 --> 01:07:46.150 And that was a genetic relationship with the aunt. 01:07:47.030 --> 01:07:50.310 Yeah, I I'm not sure is the answer. 01:07:50.630 --> 01:07:51.190 Yeah. 01:07:51.510 --> 01:07:55.910 Because yeah, it's one might expect that, you know, perhaps the family was compensated in 01:07:55.910 --> 01:08:00.150 some way and there was some kind of mediation thing that that resolved it, or I I don't 01:08:00.150 --> 01:08:00.470 know. 01:08:00.950 --> 01:08:04.950 I I haven't heard of that before, and I I think the challenge with the Hadza is that they 01:08:04.950 --> 01:08:07.080 don't accumulate wealth really easily. 01:08:07.400 --> 01:08:08.760 Again, that might be changing. 01:08:09.080 --> 01:08:11.880 Um, but they don't accumulate a lot of wealth, so it would be hard. 01:08:11.960 --> 01:08:17.960 I mean, so the classic example actually is from Polly Wiesner's work on Papu Nugini, where 01:08:17.960 --> 01:08:23.000 they have these elaborate courts and they're giving like livestock uh to harm to victims 01:08:23.000 --> 01:08:23.400 and stuff. 01:08:23.560 --> 01:08:27.880 So I I think you would need at least some sort of sense of property or accumulation of 01:08:27.880 --> 01:08:32.530 wealth that would work for compensation or or maybe forms of labor. 01:08:32.610 --> 01:08:36.290 There's other right uh societies that do uh labor exchanges. 01:08:36.370 --> 01:08:39.730 But with the Hodza, I I'm not sure what that would look like. 01:08:40.130 --> 01:08:44.450 But I I I want to be careful here because uh someone else might have more experience that 01:08:44.450 --> 01:08:46.690 and would be able to talk about that more. 01:08:48.370 --> 01:08:48.930 For sure. 01:08:49.090 --> 01:08:54.370 Yeah I guess it's just a perfect storm of of you know factors that would cause you know a 01:08:54.370 --> 01:08:59.660 murderer to be continued, you know, to be a member of the community and that they can't 01:08:59.660 --> 01:09:02.140 really compensate the victim's family. 01:09:02.300 --> 01:09:05.340 Uh they're integral to the community and they can't really be excluded. 01:09:05.420 --> 01:09:07.980 And so this is just what happens as a result. 01:09:08.540 --> 01:09:11.980 Yeah, I I I I think that's the right way to put it, yeah. 01:09:13.820 --> 01:09:14.380 Cool. 01:09:14.620 --> 01:09:20.450 Um so we've been dwelling a lot on on the Hadza and and less so on the the fishing 01:09:20.450 --> 01:09:23.970 communities and the work that you're doing with and uh Pizer. 01:09:24.450 --> 01:09:30.210 Are there any uh interesting differences you've noted between your field work and the Hadza 01:09:30.450 --> 01:09:33.010 versus your work in these fishing communities? 01:09:33.170 --> 01:09:38.370 Um what what are you uh observing there that that is particularly exciting you or 01:09:38.370 --> 01:09:39.250 interesting you? 01:09:39.810 --> 01:09:45.500 Yeah, so uh like I said that the one interesting thing about this project to begin with is 01:09:45.500 --> 01:09:46.860 that it's a bit more applied. 01:09:46.940 --> 01:09:51.420 So one thing I wanted I've and been moving more in my work is thinking about like how can 01:09:51.420 --> 01:09:57.100 we translate these theories to application or at least test them in ways that is adjacent 01:09:57.180 --> 01:09:58.220 where maybe we could do something. 01:09:58.380 --> 01:10:02.540 So part of this work is collaborating with an NGO that uh is helping fisheries management 01:10:02.540 --> 01:10:03.180 in the area. 01:10:03.420 --> 01:10:07.580 And like I said, so the the motivating question is that you have all these uh villages, 01:10:07.740 --> 01:10:10.970 like if you imagine a bay, you'll have like four or five villages around it, and they're 01:10:10.970 --> 01:10:13.850 all accessing the reef in the middle for the fisheries. 01:10:14.090 --> 01:10:18.570 And so classically, you'll get these community based uh institutions. 01:10:19.050 --> 01:10:23.690 This is from like Eleanor Ostrom's work, where the community works together to like create 01:10:23.690 --> 01:10:24.890 rules and enforce them. 01:10:25.050 --> 01:10:28.410 But the issue here, of course, is that it's four different villages, right? 01:10:28.490 --> 01:10:30.650 These communities have to work together. 01:10:30.810 --> 01:10:35.690 Um, and really it's uh a collective action problem where you need individuals in each 01:10:35.690 --> 01:10:40.380 village who are willing to report legal fishing, help clean the beach, develop landing 01:10:40.380 --> 01:10:41.580 sites, things like that. 01:10:41.820 --> 01:10:46.620 And so we're interested in whether or not these relationships between these villages could 01:10:46.620 --> 01:10:49.340 help drive participation in here. 01:10:49.420 --> 01:10:53.260 And again, the idea here is that there's some involved stake here. 01:10:53.340 --> 01:10:57.740 So one thing we find is that these what we're calling long-distance relationships between 01:10:57.740 --> 01:11:01.580 villages are really important for accessing loans for like new boats. 01:11:01.740 --> 01:11:05.590 And the only way you're going to get that loan back is if they're able to keep fishing, 01:11:05.670 --> 01:11:05.830 right? 01:11:05.990 --> 01:11:10.390 And so once you have this sort of stake in other people in other communities accessing the 01:11:10.390 --> 01:11:14.550 fishery, this creates, you know, this is more benefit for you in participation. 01:11:14.710 --> 01:11:17.270 So sort of classic cooperation problem, right? 01:11:17.430 --> 01:11:22.550 Um, and so we find that long distance friends encourage participation in these fisheries 01:11:22.550 --> 01:11:22.870 management. 01:11:22.950 --> 01:11:23.990 We replicated that effect. 01:11:24.070 --> 01:11:26.470 So we did this in 2022 and 2023. 01:11:26.550 --> 01:11:27.590 Uh so that was really nice. 01:11:27.670 --> 01:11:31.270 And again, we also replicated that it was specifically these long distance friends. 01:11:31.350 --> 01:11:34.880 So it wasn't how many friends or family you have in your village with you and wasn't f uh 01:11:34.960 --> 01:11:35.920 family in other villages. 01:11:36.000 --> 01:11:38.320 So very specifically these long distance friends. 01:11:38.560 --> 01:11:44.400 What we just we have a preprint out now where we find uh even interest in having more long 01:11:44.480 --> 01:11:50.400 distance friends, independent of having these uh friendships realized, also predicts 01:11:50.400 --> 01:11:51.120 participation. 01:11:51.360 --> 01:11:55.680 So we created this measurement uh we're calling long distance orientation or LDO. 01:11:55.840 --> 01:12:01.170 So basically asking people do you like hearing about uh people's lives in other villages. 01:12:01.330 --> 01:12:03.330 Do you like visiting people in other villages? 01:12:03.810 --> 01:12:05.490 And in the US, we tested this. 01:12:05.650 --> 01:12:09.970 This is distinct from things like extroversion or openness to new experiences. 01:12:10.130 --> 01:12:12.690 They correlate, but we can distinctly measure them. 01:12:13.090 --> 01:12:18.210 And interestingly enough, uh LDO positively predicts having more long distance friends. 01:12:18.370 --> 01:12:23.330 And once that's in the model, extroversion negatively predicts having more long distance 01:12:23.330 --> 01:12:26.450 friends or predicts fewer long distance friends. 01:12:26.530 --> 01:12:29.010 So there does seem to be some distinctiveness here. 01:12:29.220 --> 01:12:34.900 And so we find in these fishing villages that people with higher LDO are more 01:12:34.900 --> 01:12:37.140 willing to participate in these fisheries management. 01:12:37.220 --> 01:12:41.060 And the idea here is that if you want to, if you're interested in building more 01:12:41.060 --> 01:12:44.020 long-distance friends, you have to be a good cooperative partner yourself. 01:12:44.100 --> 01:12:48.580 And so we think this is a partner choice mechanism where uh interest in long-distance 01:12:48.580 --> 01:12:53.870 relationships is sort of upregulating cooperation in these long-distance settings and 01:12:53.870 --> 01:12:54.510 situations. 01:12:55.230 --> 01:12:59.550 So that pretty excited about that because it's a nice mix of some of my psychology 01:12:59.710 --> 01:13:04.190 background and anthropology and really bring them together in an interesting way. 01:13:04.750 --> 01:13:08.910 That's interesting, especially the when you add LDO and extroversion to the model, 01:13:09.070 --> 01:13:10.350 extroversion predicts it negatively. 01:13:10.430 --> 01:13:16.420 I mean, could it be that what's going on there is that extroversion is um predicting 01:13:16.580 --> 01:13:20.740 sort of uh indiscriminate socializing to independent of the community. 01:13:20.820 --> 01:13:25.220 And so you're gonna socialize more with the people in your in your group who are close and 01:13:25.220 --> 01:13:30.820 also potentially um outsiders, whereas LDO is a disproportionate interest in outsiders 01:13:30.820 --> 01:13:31.780 relative to insiders. 01:13:31.940 --> 01:13:36.340 And so once you control for that, um extroversion is going to be predicting this uh 01:13:36.420 --> 01:13:41.170 interest in uh insiders and that's going to negatively predict uh uh could something like 01:13:41.170 --> 01:13:45.010 that be going on i i i feel like i should have more conversations with you about my 01:13:45.010 --> 01:13:50.450 research because you you put it uh so well um but yeah i i think that's that's one way to 01:13:50.450 --> 01:13:55.250 think about it um is that uh extroversion you want to hang out with people more generally 01:13:55.410 --> 01:14:00.280 um and so that's probably gonna be people closer to you and LDO and I without it in the 01:14:00.280 --> 01:14:04.680 model, I think uh extroversion like weekly positively predicts long distance friends. 01:14:04.760 --> 01:14:07.400 Um, in the and this is only in the US sample. 01:14:07.480 --> 01:14:12.280 We weren't able to adapt the big five uh to the Tanzanian setting. 01:14:12.520 --> 01:14:17.480 Um the other thing it could be this going back to again measurement sort of reifying 01:14:17.640 --> 01:14:18.200 theory. 01:14:18.440 --> 01:14:24.250 If you look at the questions for extroversion, there are often things like I like to go to 01:14:24.250 --> 01:14:29.690 parties uh with lots of friends, or I like to a lot of it's very close, uh 01:14:29.850 --> 01:14:31.050 immediate socializing. 01:14:31.130 --> 01:14:36.970 And so it could be the psychology that that's tapping might actually be more specific or or 01:14:36.970 --> 01:14:42.890 less specific, but the way it's being asked, I think is in part sort of uh pushing it to 01:14:42.890 --> 01:14:44.490 where it negatively predicts, right? 01:14:44.570 --> 01:14:48.730 So in the US, like when we look at like some of the comments from the surveys, a lot of 01:14:48.730 --> 01:14:51.620 people are talking about meeting long distance friends like online and stuff. 01:14:51.700 --> 01:14:55.540 And so you're probably probably also picking up a difference there where, you know, people 01:14:55.540 --> 01:15:00.660 who are a bit more introverted are more willing to in interact online and are picking up 01:15:00.660 --> 01:15:01.540 long distance friends. 01:15:01.700 --> 01:15:05.620 But the more interesting one is the one you said where like maybe there's a real difference 01:15:05.620 --> 01:15:09.860 in that psychology, but can't rule out, you know, it's something about the the measurement 01:15:09.860 --> 01:15:11.300 itself in this case. 01:15:12.190 --> 01:15:13.070 That's cool. 01:15:13.390 --> 01:15:19.390 Um I'm asking you to speculate here, but um, do you think this is a 01:15:19.390 --> 01:15:24.670 kind of personality trait where like some people are just inherently more interested in 01:15:24.670 --> 01:15:27.870 socializing with distant community members and some people aren't? 01:15:28.110 --> 01:15:32.830 Or is is there a different story at play, like where maybe people who are more anxious 01:15:32.830 --> 01:15:37.340 about resource shortfalls really are more motivated to form these long distance connections 01:15:37.420 --> 01:15:40.540 to buffer themselves against risk and that is what's driving it. 01:15:40.620 --> 01:15:45.260 So what what do you think is is going on here with this this variation in interest and and 01:15:45.420 --> 01:15:46.780 long distance ties? 01:15:47.980 --> 01:15:53.100 We Ann and I went back and forth on whether we call this a personality trait, an internal 01:15:53.100 --> 01:15:57.340 regulatory variable, um, or you know, something else. 01:15:57.740 --> 01:16:01.180 I'm I'm less interested in that sort of taxonomy to be honest. 01:16:01.420 --> 01:16:03.340 What I this is speculation. 01:16:03.500 --> 01:16:08.930 What we think it's probably a fairly consistent trait, but one that can 01:16:09.170 --> 01:16:11.650 move as you adjust situations. 01:16:11.810 --> 01:16:16.290 So, you know, one thing that will probably impact this is like cost and convenience of long 01:16:16.370 --> 01:16:17.330 distance traveling. 01:16:17.570 --> 01:16:19.730 So uh, you know, I live in Pullman. 01:16:19.890 --> 01:16:21.970 This is eight miles from the town of Moscow. 01:16:22.130 --> 01:16:23.410 There's no bus between the two. 01:16:23.490 --> 01:16:27.820 So if you only have a bike in Pullman, then Moscow feels like a really long distance. 01:16:27.980 --> 01:16:29.900 That's a trip you have to plan for. 01:16:30.060 --> 01:16:34.540 But once you buy a car, then maybe you know your idea of distance now changes, right? 01:16:34.620 --> 01:16:37.980 And so this would be related to like some of the psychological distance literature where 01:16:37.980 --> 01:16:41.900 you find that, you know, people's perceptions of like time and space are all sort of 01:16:41.900 --> 01:16:42.780 wrapped together. 01:16:43.020 --> 01:16:44.780 And so we kind of suspected some of that. 01:16:44.860 --> 01:16:50.070 So as the costs and benefits of uh traveling, of maintaining these relationships, as you 01:16:50.070 --> 01:16:54.630 said, like if there's more need for risk buffering, um, then that could help. 01:16:54.790 --> 01:17:00.150 So again, in our society, we usually rely on financial institutions for a lot of our risk 01:17:00.150 --> 01:17:00.790 buffering, right? 01:17:00.870 --> 01:17:05.990 More so, I think, than uh friends, especially people here in uh a higher uh 01:17:06.230 --> 01:17:06.950 SES. 01:17:07.430 --> 01:17:11.510 Uh, but in Tanzania, right, they are relying on their friends a lot for help. 01:17:11.590 --> 01:17:17.110 And so one interesting thing is that they used to, before phone scams became a problem, 01:17:17.660 --> 01:17:22.860 favorite activity would be uh calling like their number neighbors and like uh interacting 01:17:22.860 --> 01:17:26.460 with someone far away and maintaining relationships. 01:17:26.540 --> 01:17:32.220 And it could be that because they don't have these other risk-buffering institutions, um, 01:17:32.460 --> 01:17:37.020 that they're more interested in uh relationships in general and maybe long distance 01:17:37.020 --> 01:17:41.820 relationships in particular to help with those sort of community-wide uh shocks. 01:17:44.790 --> 01:17:45.430 Yeah. 01:17:45.830 --> 01:17:49.830 Um so so I again I think I think it's another great way to put my research. 01:17:51.350 --> 01:17:51.750 Cool. 01:17:51.990 --> 01:17:53.350 I mean fascinating stuff. 01:17:53.510 --> 01:17:58.150 Um so I mean we're uh approaching you know an hour and a half now, and I want to make sure 01:17:58.150 --> 01:18:02.470 that we've covered the topics that that you are personally most excited about. 01:18:02.550 --> 01:18:06.550 Is there anything that we haven't covered that you're particularly interested in? 01:18:06.710 --> 01:18:10.870 Uh uh new new directions, new ideas that that are stewing in you? 01:18:11.380 --> 01:18:11.380 own. 01:18:12.020 --> 01:18:15.700 Early enough on tenure track, I should have a lot of uh new ideas, right? 01:18:16.020 --> 01:18:21.860 Uh one project I didn't talk about that I'm thinking about how to follow up on. 01:18:22.020 --> 01:18:25.540 It was uh one of the casualties of some of the grant cancellations. 01:18:25.700 --> 01:18:31.300 Uh, but this was my uh work in collaboration with some of the uh epidemiologists in our vet 01:18:31.540 --> 01:18:32.180 med school here. 01:18:32.340 --> 01:18:36.020 So we're interested in uh climate sensitive diseases, right? 01:18:36.100 --> 01:18:40.830 So diseases, um, especially vector-borne diseases, so those that are carried by mosquitoes, 01:18:41.070 --> 01:18:46.270 ticks, sandflies, et cetera, as the climate changes, right, their ecology changes. 01:18:46.350 --> 01:18:48.270 And so their range and behavior will change. 01:18:48.350 --> 01:18:53.390 And so there's a lot of diseases that have been identified that as climate's changing, the 01:18:53.390 --> 01:18:55.630 epidemiology of these diseases are expected to change. 01:18:55.790 --> 01:18:57.790 So we're looking here at Rift Valley Fever. 01:18:57.870 --> 01:19:03.390 It's a hemorrhagic fever that primarily impacts livestock, but can uh jump over to 01:19:03.390 --> 01:19:08.990 humans either by directly interacting with uh blood from the uh animal or from mosquito 01:19:09.240 --> 01:19:09.720 bites. 01:19:09.880 --> 01:19:14.840 And so historically, what you used to find is that you'd get Rift Valley Fever epidemics in 01:19:14.840 --> 01:19:19.160 this area in northern Kenya with the El Nino southern oscillation. 01:19:19.240 --> 01:19:24.520 There would be massive rainstorms that would flood these dry lands that would then 01:19:25.160 --> 01:19:29.880 create breeding grounds for mosquitoes, and they you'd get epidemics following the uh the 01:19:29.880 --> 01:19:30.840 mosquito storms. 01:19:31.270 --> 01:19:36.150 What we found is that as the precipitation is changing, so you can actually track 01:19:36.150 --> 01:19:39.750 precipitation change over several decades and temperature change. 01:19:39.910 --> 01:19:43.110 What we're finding in the area is you're getting more extreme flooding. 01:19:43.190 --> 01:19:46.710 So you get more rain on average, but fewer rainy days. 01:19:46.790 --> 01:19:48.790 So it's coming more extreme. 01:19:49.030 --> 01:19:53.030 And so what we're finding now is that there's more outbreaks happening between the 01:19:53.030 --> 01:19:55.670 southern, between the El Nino southern oscillation. 01:19:55.830 --> 01:19:59.700 And so we were interested in well, how are people adapting to these changes, right? 01:19:59.780 --> 01:20:03.540 So what climate change adaptations are people developing in these communities? 01:20:04.340 --> 01:20:05.780 And this was an interesting project. 01:20:05.860 --> 01:20:08.180 So what we found was that they're really not. 01:20:08.580 --> 01:20:12.580 What's happening is that they have so many different threats posed by climate change. 01:20:12.660 --> 01:20:17.460 So they have to deal with, you know, decreased precipitation and increased droughts. 01:20:17.620 --> 01:20:22.100 They have to deal with more conflict with these other communities in response to that 01:20:22.100 --> 01:20:22.660 drought. 01:20:22.820 --> 01:20:28.570 That, you know, what they used to do to avoid their animals getting sick would be to move 01:20:28.570 --> 01:20:30.810 away from the floods where the mosquitoes were. 01:20:30.970 --> 01:20:34.970 But now they're sort of more sedentary, they're settling around these permanent boreholes, 01:20:35.050 --> 01:20:36.650 they can't move to new regions. 01:20:36.810 --> 01:20:41.930 And so what we're finding is that these different threats posed by climate change are 01:20:41.930 --> 01:20:44.170 really impacting people's to adapt to it. 01:20:44.330 --> 01:20:50.260 And so what I'm hoping to follow up with this is really look at how people are sort of 01:20:50.260 --> 01:20:54.900 uh representing and conceptualizing this sort of threat landscape of climate change and how 01:20:54.900 --> 01:20:56.420 how are they able to respond to it? 01:20:56.500 --> 01:21:02.420 Like, can they see past the near future of say uh a drought and look into the 01:21:02.420 --> 01:21:06.180 long term about like, okay, how can we actually adapt to these different challenges? 01:21:06.340 --> 01:21:09.700 Um, and so I'm really excited about following up on that work. 01:21:09.940 --> 01:21:15.860 Um, again, in part because it really has some real-world implications for the folks we're 01:21:15.860 --> 01:21:18.820 working with, and um, you know, that excites me quite a bit. 01:21:20.370 --> 01:21:21.170 That's fascinating. 01:21:21.250 --> 01:21:25.970 Well, what what things are you are you looking to measure with with regard to people's 01:21:25.970 --> 01:21:30.850 ability to adapt to a changing climate and potentially a changing pathogen environment? 01:21:31.250 --> 01:21:34.770 What are some of the variables that you're that you're interested in in looking at? 01:21:35.330 --> 01:21:38.370 So we try to measure perceived climate change. 01:21:38.450 --> 01:21:41.250 So we'd ask people how much you think climate's changing. 01:21:41.410 --> 01:21:43.410 And it turns out this is a really hard question to ask. 01:21:43.570 --> 01:21:47.810 Other people have reported having challenges where people have a hard time seeing past 01:21:47.810 --> 01:21:48.930 seasonal variability. 01:21:49.180 --> 01:21:52.220 And the other thing that's happening is that, you know, there's a ton of NGOs that are 01:21:52.220 --> 01:21:53.100 working in this area. 01:21:53.180 --> 01:21:55.420 And so they'll come and talk to them about climate change. 01:21:55.500 --> 01:22:00.300 And so even when we translate it, we have to be careful if we use the same language the 01:22:00.300 --> 01:22:03.980 NGOs use, then it sort of triggers like, oh, I know I'm supposed to talk about how 01:22:03.980 --> 01:22:04.780 difficult this is. 01:22:05.020 --> 01:22:09.820 So we're trying to measure like um, you know, and and part of this still goes back to long 01:22:09.900 --> 01:22:13.180 distance relationships and sort of buffering against these community wide shocks. 01:22:13.350 --> 01:22:13.590 right? 01:22:13.670 --> 01:22:18.230 So if you think the climate's changing, maybe you'll make more intergroup relationships, 01:22:18.310 --> 01:22:19.110 for example. 01:22:19.350 --> 01:22:23.510 Um, so we're trying to measure uh originally sort of different aspects of climate 01:22:23.510 --> 01:22:24.150 variability. 01:22:24.390 --> 01:22:30.230 So um if you look, you can uh in actual weather data, you can break out different kinds 01:22:30.230 --> 01:22:33.670 of variation, trying to see if people psychologically match that. 01:22:34.020 --> 01:22:37.780 Our first go-around didn't seem to work well, so we'll have to get around it. 01:22:37.940 --> 01:22:41.300 But also sort of mapping out like these different kinds of threats. 01:22:41.460 --> 01:22:47.460 So do they see uh these changes in climate associated with changes in predators and 01:22:47.460 --> 01:22:52.900 changes in conflict and changes in pathogens, and see do they have a couple model in their 01:22:52.900 --> 01:22:57.890 head of this connection between climate change and you know you would think that'd be sort 01:22:57.890 --> 01:23:01.490 of the necessary first step in thinking about how they would adapt to these, right? 01:23:01.570 --> 01:23:03.730 Is how do they actually map out these threats? 01:23:03.890 --> 01:23:08.290 Um something I'm I'm thinking about about how how can we measure this um in these 01:23:08.290 --> 01:23:08.850 communities. 01:23:09.810 --> 01:23:13.810 So the first step is just seeing if they're aware that the stuff is going on and aware of 01:23:13.810 --> 01:23:15.890 the different ecological changes. 01:23:16.050 --> 01:23:20.130 And then once you have that nailed down you could potentially see if awareness of these 01:23:20.130 --> 01:23:25.820 ecological changes is affecting other variables like uh perhaps um cooperation with um 01:23:25.820 --> 01:23:29.580 long-distance uh people in other in other communities. 01:23:30.220 --> 01:23:31.100 Yeah, exactly. 01:23:31.260 --> 01:23:36.140 And like you said, this was we had a grant from a subgrant through these centers for 01:23:36.140 --> 01:23:37.900 research in emerging infectious disease. 01:23:38.060 --> 01:23:43.820 This was a uh IH NIAD-funded um uh network of research 01:23:43.820 --> 01:23:44.460 centers. 01:23:44.700 --> 01:23:50.110 It was canceled in part um with a lot of the other cancellations, 01:23:50.590 --> 01:23:53.070 and so wasn't able to follow up on that yet. 01:23:53.150 --> 01:23:56.910 So still thinking about how I'll get back out there and follow up. 01:23:57.230 --> 01:24:01.310 And you know, this is the reality of doing maybe not even just field work, but science in 01:24:01.310 --> 01:24:01.710 general, right? 01:24:01.790 --> 01:24:06.590 Is that very often we uh outside circumstances push us in one direction or another. 01:24:06.750 --> 01:24:12.600 But um you know to the to the extent that I the will to research what I want, um, would 01:24:12.760 --> 01:24:13.880 would love to follow up on this. 01:24:13.960 --> 01:24:14.280 Yeah. 01:24:14.520 --> 01:24:14.760 Yeah. 01:24:14.920 --> 01:24:18.920 When we were in Morocco, you told me that the mosquitoes there we wouldn't need to worry 01:24:18.920 --> 01:24:19.160 about. 01:24:19.240 --> 01:24:25.080 You were saying you were you have expertise in mosquito uh taxonomizing for for good 01:24:25.080 --> 01:24:25.720 reason. 01:24:26.120 --> 01:24:27.000 Yeah, yeah. 01:24:27.160 --> 01:24:31.350 Um and I remember when we got the grant proposal uh feedback. 01:24:31.510 --> 01:24:34.470 That was the only feedback we got was that someone was really upset we didn't talk more 01:24:34.470 --> 01:24:35.110 about mosquitoes. 01:24:35.190 --> 01:24:36.230 And I thought, oh, that's silly. 01:24:36.390 --> 01:24:41.110 And then actually reading up on the different uh genus of mosquitoes and what they spread. 01:24:41.190 --> 01:24:42.710 And so, like Riff Valley fever. 01:24:42.950 --> 01:24:47.350 So most uh diseases they're going to be spread by one specific genus or another. 01:24:47.510 --> 01:24:50.630 Um, and you you can tell there are pretty visible differences. 01:24:50.710 --> 01:24:53.990 Uh Riff Alley fever spread by just about everything, really. 01:24:54.070 --> 01:24:59.860 We found uh all three genus of mosquitoes that spread it, um ticks have been known to 01:24:59.860 --> 01:25:04.260 spread it, sand flies, and so it's been kind of crazy diving into this virus literature and 01:25:04.340 --> 01:25:09.620 like realizing how scary it can be when you have a disease like this that can spread 01:25:09.620 --> 01:25:11.620 through all these different kinds of vectors. 01:25:11.860 --> 01:25:12.260 Yeah. 01:25:13.780 --> 01:25:15.060 Which oh good. 01:25:15.700 --> 01:25:20.850 Yeah, no, I I was just curious, um in terms of how these communities are conceptualizing 01:25:20.850 --> 01:25:21.330 these changes. 01:25:21.410 --> 01:25:25.490 Cause, you know, we obviously think about it in terms of meteorological changes in the germ 01:25:25.490 --> 01:25:29.970 theory of disease, but they might not be exposed to those ideas or or are they? 01:25:30.050 --> 01:25:30.290 I don't know. 01:25:30.370 --> 01:25:33.090 I mean, do they have a different way of conceptualizing these changes? 01:25:33.730 --> 01:25:37.090 They do have some exposure to the germ theory of disease. 01:25:37.250 --> 01:25:41.970 Um, and it it varied between uh a couple of different villages we visited, how much they 01:25:41.970 --> 01:25:43.090 bought into it. 01:25:43.330 --> 01:25:45.970 Uh one community was very insistent. 01:25:46.120 --> 01:25:50.840 This is like uh a response to us abandoning our traditional ways. 01:25:51.000 --> 01:25:53.480 Like it was very much not germ theory of disease. 01:25:53.800 --> 01:25:54.040 Interesting. 01:25:54.840 --> 01:25:59.000 Sort of being punished by a supernatural agent for true in the US too. 01:25:59.080 --> 01:25:59.240 Yeah. 01:25:59.480 --> 01:25:59.640 Yeah. 01:25:59.720 --> 01:25:59.880 Yeah. 01:26:00.200 --> 01:26:02.040 I mean we we certainly get some of that as well as well. 01:26:02.760 --> 01:26:04.440 That's like exactly true here. 01:26:04.520 --> 01:26:04.840 Yeah. 01:26:05.080 --> 01:26:05.240 Yeah. 01:26:05.480 --> 01:26:05.880 Yeah. 01:26:06.040 --> 01:26:08.120 Um but it to your point, right? 01:26:08.200 --> 01:26:12.280 It matters how they think what's causing this because if you did want to design an 01:26:12.280 --> 01:26:16.010 intervention, you know it's it's going to impact how they they buy into it. 01:26:16.090 --> 01:26:19.610 If, you know, now they they interact with a lot of like vet techs. 01:26:19.850 --> 01:26:23.690 The govern Kenyan government does do vaccine um campaigns. 01:26:23.770 --> 01:26:29.530 So they have some exposure and for some diseases, they like like malaria, you know, 01:26:29.610 --> 01:26:33.450 they they don't know the details, but they're pretty certain that's spread by mosquitoes 01:26:33.530 --> 01:26:36.170 and that they're they buy that there's some sort of parasite. 01:26:36.730 --> 01:26:38.490 So it depends on the specifics. 01:26:38.570 --> 01:26:44.520 For Rift Valley fever, um that one they tended to buy more into the germ theory of 01:26:44.520 --> 01:26:47.160 disease for a lot of those explanations. 01:26:47.400 --> 01:26:49.160 Um yeah. 01:26:49.800 --> 01:26:50.200 Cool. 01:26:50.440 --> 01:26:56.040 Do they have any awareness of um industry being behind climate change or uh 01:26:56.920 --> 01:26:59.800 is that has that not gotten around? 01:27:00.440 --> 01:27:03.640 They tend to blame local changes. 01:27:03.800 --> 01:27:09.130 Um so they would talk about their own tree cutting, and and it's hard to tell, you know, do 01:27:09.130 --> 01:27:13.690 they think this is having a larger impact on the climate versus like you can see the effect 01:27:13.690 --> 01:27:17.530 of cutting trees meant there's massive dust storms because there's nothing catching the 01:27:17.530 --> 01:27:17.850 dust. 01:27:17.930 --> 01:27:19.690 And so people would complain about that that. 01:27:20.170 --> 01:27:25.930 Um you know, and and this is sort of a challenge of doing sort of more applied work in 01:27:25.930 --> 01:27:31.290 these settings, is that the reality is that they're gonna be the most impacted by climate 01:27:31.290 --> 01:27:33.370 change, but have done the least to contribute. 01:27:33.770 --> 01:27:39.280 But you do get like NGO scolds who'll be like, well, you need to, you know, sequester more 01:27:39.280 --> 01:27:41.040 carbon or however they would put it. 01:27:41.200 --> 01:27:44.320 And it's like these guys did not cause the problem. 01:27:44.480 --> 01:27:49.360 Like, you know, um, so it's trying to balance that that line. 01:27:49.680 --> 01:27:50.320 Yeah. 01:27:51.840 --> 01:27:53.120 Fascinating. 01:27:54.160 --> 01:27:54.800 All right. 01:27:55.520 --> 01:28:00.000 Well, um I think you know, we we would done an hour and a half. 01:28:00.080 --> 01:28:01.920 I think that's pretty good. 01:28:02.080 --> 01:28:02.480 Yeah, Chris. 01:28:02.800 --> 01:28:04.400 This is a really fun conversation. 01:28:04.480 --> 01:28:06.720 Thanks for uh chatting with us, Chris. 01:28:07.090 --> 01:28:08.050 Yeah, appreciate it. 01:28:08.210 --> 01:28:11.730 Really uh enjoyed talking, especially about things like methods and and measurements and 01:28:11.810 --> 01:28:13.970 you know, how can we do that better cross-culturally? 01:28:14.050 --> 01:28:15.570 Uh this was a really fun conversation. 01:28:15.730 --> 01:28:15.970 Yeah. 01:28:16.290 --> 01:28:22.130 I hope that you uh get all your funding back and uh and that you uh how do you avoid 01:28:22.130 --> 01:28:23.810 mosquitoes in the field? 01:28:24.290 --> 01:28:25.570 Uh not well. 01:28:25.730 --> 01:28:31.660 Uh uh you know, uh repellent uh if you 01:28:31.660 --> 01:28:32.860 can get a mosquito net. 01:28:33.100 --> 01:28:35.660 Um, but like I was staying at one guest house. 01:28:35.820 --> 01:28:39.020 The mosquito net was clearly not treated, bunch of holes. 01:28:39.180 --> 01:28:43.660 I woke up the next morning with literally dozens of mosquitoes in my net, and you know, I 01:28:43.660 --> 01:28:48.140 was killing them, and it's just like splotches of my blood, and I'm you know, very upset 01:28:48.140 --> 01:28:48.460 about it. 01:28:49.020 --> 01:28:54.220 Um It was it's a mosquito net that just keeps your mosquitoes with you, is really the way 01:28:54.220 --> 01:28:54.540 it works. 01:28:55.020 --> 01:28:56.460 That that's what ended up happening. 01:28:56.540 --> 01:28:56.860 Yeah. 01:28:57.020 --> 01:29:02.850 So um fortunately I haven't gotten anything fun or exciting in 01:29:02.850 --> 01:29:03.890 terms of diseases. 01:29:03.970 --> 01:29:05.410 Uh so hopefully that will continue. 01:29:05.490 --> 01:29:11.170 But yeah, thank you for your service, 01:29:11.330 --> 01:29:11.650 Chris. 01:29:11.970 --> 01:29:13.890 Yes, thank you for your service and and Godspeed. 01:29:14.050 --> 01:29:17.250 Hope I hope you don't get any fun and interesting diseases. 01:29:18.130 --> 01:29:18.930 Yeah, thank you so much. 01:29:19.330 --> 01:29:21.250 Your diseases stay very very boring. 01:29:22.280 --> 01:29:23.320 As as do we all. 01:29:23.400 --> 01:29:25.160 Uh yeah, thank you so much. 01:29:29.800 --> 01:29:32.120 David, you are still here. 01:29:32.680 --> 01:29:35.720 I'm still here, and you the listener are still listening. 01:29:36.280 --> 01:29:37.400 You might not be. 01:29:37.560 --> 01:29:39.320 Uh but you're not hearing us. 01:29:39.560 --> 01:29:45.410 Although at the very least, our yeah, I mean it could be is that someone left their phone 01:29:45.490 --> 01:29:48.610 and when and they're not actually listening, but it's just it kept playing. 01:29:48.850 --> 01:29:52.130 Well, somebody uh might have listened and then stopped listening. 01:29:52.210 --> 01:29:54.050 So in that never mind, it's okay. 01:29:54.210 --> 01:29:56.850 Or they could just be spacing out, you think? 01:29:57.410 --> 01:30:01.490 Well, I was thinking about somebody who listens to the episode but then stops at the outro 01:30:01.650 --> 01:30:06.370 because they know that what's gonna happen in the outro is not is missable, is missable, 01:30:06.450 --> 01:30:06.690 yeah. 01:30:06.940 --> 01:30:07.260 Yeah. 01:30:07.500 --> 01:30:08.620 And so are they a listener? 01:30:08.700 --> 01:30:10.300 They're not listening, but it doesn't matter. 01:30:10.380 --> 01:30:11.900 It's really, really yeah. 01:30:11.980 --> 01:30:14.540 I I I I might cut this out myself. 01:30:15.580 --> 01:30:17.740 Anyway, uh, you're here, David. 01:30:17.820 --> 01:30:19.340 The listener is here. 01:30:19.660 --> 01:30:20.300 Uh yeah. 01:30:20.620 --> 01:30:24.860 We could give our song and dance routine of supporting us, Patreon, social media, leave us 01:30:24.860 --> 01:30:30.140 a kind review, but we usually we've been doing kind of banter in in the outros instead, 01:30:30.380 --> 01:30:30.700 right? 01:30:31.100 --> 01:30:32.380 Uh I think so. 01:30:32.910 --> 01:30:34.030 Do you have any banter? 01:30:34.670 --> 01:30:35.550 I think I just did it. 01:30:35.630 --> 01:30:36.430 That's all I have at the end. 01:30:36.590 --> 01:30:36.990 You just did it? 01:30:37.070 --> 01:30:37.870 That was the banter? 01:30:38.030 --> 01:30:38.190 Yeah. 01:30:38.430 --> 01:30:42.270 I'm st honest, I'm still not a hundred percent from HBus. 01:30:44.190 --> 01:30:44.990 Yeah, I know. 01:30:45.070 --> 01:30:48.270 You're still cup recovering from the sickness, whatever it is. 01:30:50.910 --> 01:30:53.390 So David, thank you for carrying this episode today. 01:30:54.220 --> 01:30:55.660 Yeah, no, absolutely. 01:30:55.820 --> 01:30:57.580 Um, sickness is a is a real thing. 01:30:57.740 --> 01:30:58.860 Lastitude's a real thing. 01:30:59.020 --> 01:31:00.380 Uh stay tuned for for Josh. 01:31:01.340 --> 01:31:02.140 Oh, there you go, David. 01:31:02.220 --> 01:31:02.540 There you go. 01:31:02.620 --> 01:31:03.900 That's why they pay you the big bucks. 01:31:04.060 --> 01:31:09.660 I'm drinking coffee to just sort of perk myself up, but that was a great segue into Josh 01:31:09.660 --> 01:31:12.380 Schnodgrass is going to be our upcoming guest. 01:31:12.540 --> 01:31:17.900 So this is a um a teaser for Josh Schnodgrass about the 01:31:18.860 --> 01:31:24.510 the emotion of of being sick and how it depletes you and it even depletes your 01:31:24.510 --> 01:31:27.550 banter ability apparently. 01:31:27.870 --> 01:31:28.270 Yes. 01:31:28.910 --> 01:31:31.390 I think that and that was one of the first previews we've done. 01:31:31.470 --> 01:31:33.150 So but um yeah. 01:31:33.710 --> 01:31:34.030 Yeah. 01:31:34.190 --> 01:31:36.830 Should we do a trailer for the next one at the end? 01:31:37.390 --> 01:31:39.870 Uh I can do I can do my trailer voice. 01:31:40.110 --> 01:31:41.230 I want to hear your trailer voice. 01:31:41.550 --> 01:31:41.950 No words. 01:31:42.110 --> 01:31:42.510 Please do it. 01:31:45.300 --> 01:31:51.140 One man dares to ask the questions to 01:31:51.140 --> 01:31:51.860 a scholar. 01:31:52.260 --> 01:31:53.860 Well uh is that pretty good? 01:31:54.260 --> 01:31:55.140 That's really good. 01:31:55.300 --> 01:31:57.700 Um is it Will Arnett? 01:31:57.780 --> 01:32:01.380 Is that who's uh the guy who does a lot of um he's not rust rust? 01:32:01.940 --> 01:32:04.740 No, it's not Will Arnett, although he has a verse. 01:32:05.140 --> 01:32:05.860 No, Will Arnett. 01:32:06.020 --> 01:32:08.020 No, but Will Arnett does uh voiceovers. 01:32:08.420 --> 01:32:12.660 He does, but he doesn't think he does like Oh, he doesn't do when in a world though, yeah. 01:32:12.740 --> 01:32:13.140 Who does that? 01:32:14.260 --> 01:32:15.410 I forget his name. 01:32:15.490 --> 01:32:17.410 I think his name is like Don something. 01:32:18.770 --> 01:32:19.010 Okay. 01:32:19.410 --> 01:32:19.650 Anyway. 01:32:19.970 --> 01:32:20.530 Um in a world. 01:32:20.850 --> 01:32:22.770 They don't do those kinds of movie trailers anymore. 01:32:22.850 --> 01:32:23.490 I miss them. 01:32:23.810 --> 01:32:26.050 They don't have a voiceover actor doing the trailers. 01:32:26.370 --> 01:32:27.730 Don LaFontaine. 01:32:28.130 --> 01:32:29.490 Yeah, Don Lafontaine. 01:32:29.570 --> 01:32:29.890 That's the guy. 01:32:30.130 --> 01:32:30.370 Yeah. 01:32:30.530 --> 01:32:33.570 Maybe we can get him to do our intros and that'd be really fun. 01:32:33.890 --> 01:32:34.850 That would be great. 01:32:35.040 --> 01:32:35.600 Yeah. 01:32:35.920 --> 01:32:39.280 Is he still I mean he probably he's he hasn't gotten a lot of work. 01:32:39.520 --> 01:32:43.280 You know, there he they don't do voiceovers anymore for trailers. 01:32:43.520 --> 01:32:45.360 There's um I miss them. 01:32:45.680 --> 01:32:46.320 Yeah. 01:32:47.280 --> 01:32:48.720 He's still alive. 01:32:48.880 --> 01:32:54.800 I feel like that that's one the that's one of um the things that I miss from the 90s and 01:32:54.800 --> 01:32:57.120 early 2000s is the movie trailer voice. 01:32:57.520 --> 01:33:01.920 And the other thing I miss is film scores that have a damn melody. 01:33:02.690 --> 01:33:06.930 Everything is just drones and completely devoid of melody these days. 01:33:07.090 --> 01:33:12.050 I miss the John Williams memorable melody that's that stays with you after the movie and 01:33:12.050 --> 01:33:12.530 gets it. 01:33:12.770 --> 01:33:18.210 Jurassic Park, I I still listen to Jurassic Park, you know, it's gorgeous pie that 01:33:18.210 --> 01:33:20.770 soundtrack is really gorgeous piece of music. 01:33:20.930 --> 01:33:23.090 And you know, film scores just don't do that anymore. 01:33:23.170 --> 01:33:24.210 They're just drones. 01:33:24.610 --> 01:33:25.650 It's really disappointing. 01:33:25.730 --> 01:33:27.330 Yeah, we've regressed as a crossing. 01:33:27.650 --> 01:33:28.930 Drones and green screens, yeah. 01:33:29.010 --> 01:33:29.250 Yeah. 01:33:29.600 --> 01:33:33.200 Drones, green screens, yeah, electronic screens. 01:33:33.680 --> 01:33:38.080 Yeah, I mean, I don't you know, don't get me wrong, I like a good drone as much as the next 01:33:38.080 --> 01:33:41.200 guy, but also you gotta have a melody, you know? 01:33:41.600 --> 01:33:42.800 You preach, David. 01:33:43.200 --> 01:33:44.000 Yeah, all right, all right. 01:33:44.160 --> 01:33:48.720 So all of you folks who are doing um s uh Hollywood um 01:33:49.360 --> 01:33:50.320 composition. 01:33:51.130 --> 01:33:51.770 Yeah. 01:33:52.250 --> 01:33:53.290 Take notice. 01:33:53.610 --> 01:33:57.530 Take notice and uh, you know, enjoy some some John Williams. 01:33:57.930 --> 01:34:00.330 Yeah, enjoy the melody on the way out here, too. 01:34:00.490 --> 01:34:00.810 Yeah. 01:34:00.970 --> 01:34:01.210 Yeah. 01:34:01.370 --> 01:34:01.770 David. 01:34:02.090 --> 01:34:05.050 Jurassic Park, Indiana Jones, Star Wars, whatever does it for you. 01:34:05.210 --> 01:34:08.730 Listen to it, get it in your head, it'll provide a nice soundtrack to your life. 01:34:08.970 --> 01:34:12.890 Are we allowed to play Jurassic Park as our outro for this episode? 01:34:13.660 --> 01:34:16.700 Um, I think we might have to get them the rights. 01:34:17.500 --> 01:34:20.300 But I I no one's gonna sue us, so I'll probably do it. 01:34:20.700 --> 01:34:21.740 We'll call Sam Neil. 01:34:22.060 --> 01:34:24.460 That that would be hilarious if somebody sued us. 01:34:26.220 --> 01:34:31.420 Well, uh we probably won't get to it, but imagine Jurassic Park uh for it. 01:34:32.060 --> 01:34:34.620 I could just hum the theme to Jurassic Park. 01:34:35.420 --> 01:34:40.990 David, you're on you don't need any would that be the new that that yeah. 01:34:41.710 --> 01:34:42.270 Can you work on that? 01:34:42.350 --> 01:34:44.990 Can you do a mashup of Manafort and Jurassic Park? 01:34:45.310 --> 01:34:46.350 Oh, that's a good idea. 01:34:46.590 --> 01:34:46.830 Okay. 01:34:46.990 --> 01:34:47.550 I'll work on it. 01:34:47.710 --> 01:34:47.870 All right. 01:34:47.950 --> 01:34:48.510 You're two. 01:34:48.590 --> 01:34:51.870 We can slightly modify the um intro and outro. 01:34:51.950 --> 01:34:52.830 So all right. 01:34:52.910 --> 01:34:57.150 Uh everybody, thank you for listening for all three of you who who've stick stuck through 01:34:57.150 --> 01:34:58.110 it this long. 01:34:58.270 --> 01:35:00.110 Um I'll see you. 01:35:00.190 --> 01:35:01.230 We'll see you next week. 01:35:01.580 --> 01:35:03.260 Thank you for your service, listener. 01:35:03.420 --> 01:35:03.740 Yeah. 01:35:04.060 --> 01:35:04.460 Exactly. 01:35:05.180 --> 01:35:05.820 Bye, David. 01:35:05.900 --> 01:35:06.380 See you next week. 01:35:06.460 --> 01:35:06.780 That was great. 01:35:07.020 --> 01:35:07.500 Take it easy. 01:35:07.580 --> 01:35:08.460 All right, bye.