1 00:00:02,990 --> 00:00:06,120 Speaker 1: Welcome to Stuff to Blow Your Mind, a production of iHeartRadio. 2 00:00:12,980 --> 00:00:14,940 Speaker 2: Hey, welcome to Stuff to Blow Your Mind. My name 3 00:00:14,980 --> 00:00:15,640 Speaker 2: is Robert Lamb. 4 00:00:16,260 --> 00:00:18,520 Speaker 3: And I am Joe McCormick. And we're back with the 5 00:00:18,640 --> 00:00:22,810 Speaker 3: second part of our discussion about this year's Ig Nobel Prizes. 6 00:00:23,440 --> 00:00:26,160 Speaker 3: If you're not familiar, the IgnoBells are given out once 7 00:00:26,239 --> 00:00:29,400 Speaker 3: every year by a scientific humor magazine called the Annals 8 00:00:29,460 --> 00:00:34,180 Speaker 3: of Improbable Research. You can read more about them at improbable.com. 9 00:00:34,740 --> 00:00:37,270 Speaker 3: And the mission statement of these prizes is to, quote, 10 00:00:37,380 --> 00:00:40,650 Speaker 3: honor achievements that first make people laugh and then make 11 00:00:40,710 --> 00:00:44,150 Speaker 3: them think. We at Stuff to Blow Your Mind are 12 00:00:44,229 --> 00:00:47,450 Speaker 3: not affiliated with the IgnoBells in any way, but we 13 00:00:47,750 --> 00:00:50,410 Speaker 3: usually give them some coverage every year. So most years 14 00:00:50,450 --> 00:00:52,930 Speaker 3: we release an episode or two covering some of the winners. 15 00:00:53,390 --> 00:00:57,280 Speaker 3: The timing's usually awkward for us because they typically have 16 00:00:57,320 --> 00:01:00,660 Speaker 3: the prize ceremony in September. Around the same time, we're 17 00:01:00,680 --> 00:01:04,410 Speaker 3: getting ready for our big slate of Halloween season episodes. 18 00:01:04,790 --> 00:01:07,390 Speaker 3: So like most years, this year we're only getting around 19 00:01:07,430 --> 00:01:10,280 Speaker 3: to talking about the eggs now that we are into November. 20 00:01:11,510 --> 00:01:14,789 Speaker 3: But in the last episode, we already covered the 2026 21 00:01:14,790 --> 00:01:19,560 Speaker 3: Technology Prize, which was awarded for research into something called necroprinting. 22 00:01:19,580 --> 00:01:20,000 Speaker 2: Yeah. 23 00:01:20,280 --> 00:01:24,140 Speaker 3: A very, very interesting concept. A concept for using parts 24 00:01:24,240 --> 00:01:28,040 Speaker 3: of dead mosquitoes as a mechanism in microscale 3D printing. 25 00:01:28,100 --> 00:01:32,190 Speaker 3: That's pretty sick. We talked about the Biomechanics Prize, which 26 00:01:32,340 --> 00:01:39,429 Speaker 3: investigated the phenomenon of mouth-to-mouth kissing across different non-human animal species. 27 00:01:39,959 --> 00:01:43,500 Speaker 3: And it came up with a truly beautiful, moving scientific 28 00:01:43,540 --> 00:01:49,660 Speaker 3: definition of kissing, which was, quote, non-agonistic interactions involving directed 29 00:01:49,820 --> 00:01:55,610 Speaker 3: intraspecific oral-oral contact with some movement of the lips-slash-mouth parts 30 00:01:55,750 --> 00:02:00,730 Speaker 3: and no food transfer. And finally, last time we talked 31 00:02:00,870 --> 00:02:04,730 Speaker 3: about the 2026 Chemistry Prize, which was given to researchers 32 00:02:04,750 --> 00:02:08,540 Speaker 3: who looked into the nutritional value of cockroach milk. So 33 00:02:08,620 --> 00:02:10,670 Speaker 3: we're back today to talk about more. And Rob, if 34 00:02:10,690 --> 00:02:12,649 Speaker 3: you don't mind, I want to kick things off here 35 00:02:12,669 --> 00:02:15,530 Speaker 3: with a very brief look at this year's Ig Nobel 36 00:02:15,590 --> 00:02:16,910 Speaker 3: Prize in Medicine. 37 00:02:17,610 --> 00:02:20,810 Speaker 2: Oh, yeah, yeah, yeah. Let's get into this one, because 38 00:02:20,830 --> 00:02:23,309 Speaker 2: this one, as we were chatting about before we recorded, 39 00:02:23,750 --> 00:02:24,630 Speaker 2: is news you can use. 40 00:02:24,910 --> 00:02:27,600 Speaker 3: That's right. It has some advice for how to manage 41 00:02:27,620 --> 00:02:32,280 Speaker 3: your body fluids correctly. So this was awarded posthumously to 42 00:02:32,540 --> 00:02:35,420 Speaker 3: a Japanese medical doctor and researcher in the field of 43 00:02:35,560 --> 00:02:41,340 Speaker 3: respiratory physiology named named Tokuji Uno. Uno was a professor 44 00:02:41,680 --> 00:02:46,260 Speaker 3: at Asahikawa Medical University in Hokkaido, and he passed away 45 00:02:46,320 --> 00:02:50,100 Speaker 3: in 2022. But the paper that earned him this award 46 00:02:50,160 --> 00:02:51,910 Speaker 3: was from all the way back in 1977. So this 47 00:02:51,930 --> 00:02:55,049 Speaker 3: is one of those deep cuts that they pull out 48 00:02:55,070 --> 00:02:58,630 Speaker 3: of the archives to give some recognition to. And the 49 00:02:58,669 --> 00:03:01,430 Speaker 3: paper was called, are you ready for this? How to 50 00:03:01,550 --> 00:03:06,290 Speaker 3: Blow the Nose, an Aerodynamic Study of the Nose Blowing. 51 00:03:06,970 --> 00:03:09,570 Speaker 3: So do we need to be told how to blow 52 00:03:09,630 --> 00:03:12,830 Speaker 3: our noses? Yes, we do. Just because you've done something 53 00:03:12,870 --> 00:03:14,930 Speaker 3: a lot of times doesn't mean you're doing it the 54 00:03:14,950 --> 00:03:15,950 Speaker 3: best possible way. 55 00:03:16,270 --> 00:03:18,389 Speaker 2: Yeah, this is one of those things I think about 56 00:03:18,430 --> 00:03:21,090 Speaker 2: more and more in part. I think I thought about 57 00:03:21,120 --> 00:03:23,900 Speaker 2: it more and more after I became a parent. But, 58 00:03:24,440 --> 00:03:26,240 Speaker 2: you know, this is one of those things you learn 59 00:03:26,720 --> 00:03:29,940 Speaker 2: as a kid by parents who you eventually learn had 60 00:03:29,960 --> 00:03:33,200 Speaker 2: a lot on their plate and maybe didn't have time 61 00:03:33,260 --> 00:03:37,240 Speaker 2: to walk you through absolutely everything. So This is exactly 62 00:03:37,300 --> 00:03:39,500 Speaker 2: the sort of thing you may be doing wrong because 63 00:03:39,540 --> 00:03:41,740 Speaker 2: you've just been doing it without thinking about it. 64 00:03:41,740 --> 00:03:47,090 Speaker 3: Did you ever have to deal with a snot sucker 65 00:03:47,250 --> 00:03:49,430 Speaker 3: or as it's called in our house, the snot snucker? 66 00:03:50,080 --> 00:03:50,440 Speaker 2: Yes. 67 00:03:51,020 --> 00:03:53,740 Speaker 3: Basically a machine that blows the child's nose for them. 68 00:03:53,760 --> 00:03:54,560 Speaker 2: Oh, it's a machine? 69 00:03:55,020 --> 00:03:56,900 Speaker 3: Well, it's a little like, it's a little squeezy. 70 00:03:57,220 --> 00:03:58,500 Speaker 2: Oh, okay. Squeezy, I know. 71 00:03:58,520 --> 00:04:01,910 Speaker 3: It's a very simple machine, a little squeezy, simple machine. 72 00:04:01,930 --> 00:04:04,510 Speaker 2: I was imagining there was some sort of like full 73 00:04:04,550 --> 00:04:06,970 Speaker 2: blown device that you have to charge at night. And 74 00:04:07,030 --> 00:04:09,610 Speaker 2: maybe there is, but yes, the squeezy I'm familiar with. 75 00:04:09,850 --> 00:04:10,170 Speaker 3: Okay. 76 00:04:10,210 --> 00:04:11,070 Speaker 2: Yeah. 77 00:04:11,150 --> 00:04:13,530 Speaker 3: For children who are not yet able or willing to 78 00:04:13,570 --> 00:04:17,500 Speaker 3: blow noses of their own accord. Or I guess for adults, 79 00:04:17,540 --> 00:04:20,660 Speaker 3: you know, whoever whoever cannot or will not blow their nose. 80 00:04:21,220 --> 00:04:24,370 Speaker 2: Yeah. After a certain point, it's no longer socially acceptable 81 00:04:24,440 --> 00:04:27,070 Speaker 2: to ask a person of a certain age. Hey, do 82 00:04:27,089 --> 00:04:29,289 Speaker 2: you need to blow that nose? Do you need a tissue? 83 00:04:29,610 --> 00:04:30,910 Speaker 2: I mean, I guess you can still ask if they 84 00:04:30,950 --> 00:04:33,490 Speaker 2: need a tissue, but generally you're not allowed to really 85 00:04:33,650 --> 00:04:35,770 Speaker 2: critique someone's technique. 86 00:04:36,620 --> 00:04:39,850 Speaker 3: Okay, so this article, the original was in Japanese, but 87 00:04:39,880 --> 00:04:42,529 Speaker 3: I found a couple of write-ups, one in the Japan 88 00:04:42,589 --> 00:04:45,950 Speaker 3: Times from September of this year by Spencer Landers and 89 00:04:45,990 --> 00:04:49,909 Speaker 3: another on a site called Sora News 24 by Elliot Hale. 90 00:04:50,510 --> 00:04:53,219 Speaker 3: So putting these two summaries together, I got the gist 91 00:04:53,260 --> 00:04:57,460 Speaker 3: of what the recommendations are. What did this researcher decide 92 00:04:57,520 --> 00:05:00,520 Speaker 3: was the best way to blow your nose? It seems 93 00:05:00,600 --> 00:05:04,469 Speaker 3: to me the most important of the recommendations is blow 94 00:05:04,730 --> 00:05:09,589 Speaker 3: each nostril separately. When you blow both of your nostrils 95 00:05:09,650 --> 00:05:12,989 Speaker 3: at the same time, air tends to take the path 96 00:05:13,010 --> 00:05:16,360 Speaker 3: of least resistance to escape. So you are not getting 97 00:05:16,390 --> 00:05:20,840 Speaker 3: the most mucus clearance per blow. Nostrils are rarely clogged 98 00:05:20,880 --> 00:05:24,440 Speaker 3: the same amount. Usually one is clogged more than the other. 99 00:05:25,000 --> 00:05:27,720 Speaker 3: So the air is, if it's just finding the path 100 00:05:27,760 --> 00:05:30,400 Speaker 3: of least resistance, it's actually mostly going where it is 101 00:05:30,520 --> 00:05:34,890 Speaker 3: least needed. So instead, you should close one nostril at 102 00:05:34,930 --> 00:05:37,130 Speaker 3: a time with your finger and blow the other and 103 00:05:37,230 --> 00:05:40,610 Speaker 3: alternate them. And this will make sure both passages get 104 00:05:40,690 --> 00:05:43,270 Speaker 3: cleaned out. A lot of people probably figured this one 105 00:05:43,330 --> 00:05:45,390 Speaker 3: out for themselves, but not everybody. 106 00:05:45,410 --> 00:05:45,990 Speaker 2: I don't know. 107 00:05:46,170 --> 00:05:48,920 Speaker 3: I'd say I myself, I probably most of the time 108 00:05:48,950 --> 00:05:51,860 Speaker 3: do both nostrils at once. And now I'm going to 109 00:05:51,880 --> 00:05:53,480 Speaker 3: change that behavior moving forward. 110 00:05:54,300 --> 00:05:55,859 Speaker 2: You know, this is one of those things where I 111 00:05:55,980 --> 00:06:00,580 Speaker 2: honestly don't... I like to think that I'm doing it correctly, but... 112 00:06:01,370 --> 00:06:04,210 Speaker 2: generally when I'm engaging in nose blowing, it's, you know, 113 00:06:04,230 --> 00:06:05,750 Speaker 2: it's such a fast sort of, okay, I got to 114 00:06:05,790 --> 00:06:07,100 Speaker 2: do this. I got to get on with it. It's 115 00:06:07,130 --> 00:06:11,880 Speaker 2: not something I'm really being present with. Uh, and however 116 00:06:11,920 --> 00:06:14,440 Speaker 2: I'm doing it, I should be more present with it. Um, 117 00:06:15,460 --> 00:06:17,080 Speaker 2: and I'm not saying you could be, it could be 118 00:06:17,120 --> 00:06:19,520 Speaker 2: a meditative practice though. It is interesting that, you know, 119 00:06:19,600 --> 00:06:23,700 Speaker 2: alternate nostril breathing, um, is, is very much a meditative 120 00:06:23,839 --> 00:06:26,400 Speaker 2: little technique people can use to sort of like, you know, 121 00:06:26,460 --> 00:06:29,870 Speaker 2: come down from mild anxiety and put yourself in the moment. 122 00:06:30,680 --> 00:06:33,659 Speaker 2: And while doing it, you can sometimes notice like, oh, yeah, 123 00:06:33,720 --> 00:06:35,820 Speaker 2: this is a lot easier on one side than the other. 124 00:06:35,920 --> 00:06:37,700 Speaker 2: If you haven't done this before, you know, look up 125 00:06:37,740 --> 00:06:39,760 Speaker 2: the technique online. But it's basically like, you know, close 126 00:06:39,820 --> 00:06:43,520 Speaker 2: one nostril, you know, breathe in, breathe out and then 127 00:06:43,580 --> 00:06:44,680 Speaker 2: go to the other one and so forth. 128 00:06:46,120 --> 00:06:50,090 Speaker 3: OK, so next recommendations in the paper blow powerfully. You know, 129 00:06:50,130 --> 00:06:53,270 Speaker 3: that might be pretty obvious, but they say, you know, 130 00:06:53,310 --> 00:06:56,929 Speaker 3: higher air velocity really does get the secretions discharged better. 131 00:06:57,010 --> 00:06:59,090 Speaker 3: So don't be afraid to give it a good blow. 132 00:07:00,220 --> 00:07:04,250 Speaker 2: Now, that can prove difficult in various social situations or 133 00:07:04,290 --> 00:07:06,190 Speaker 2: if you don't want to make a lot of noise. 134 00:07:06,290 --> 00:07:08,550 Speaker 2: So I could see that being an issue where if 135 00:07:08,570 --> 00:07:11,030 Speaker 2: you're trying to keep it down, you don't want to 136 00:07:11,070 --> 00:07:14,890 Speaker 2: sound too disgusting, you don't have the privacy to really 137 00:07:15,190 --> 00:07:18,470 Speaker 2: do a proper nose blow, then you might not be 138 00:07:18,510 --> 00:07:19,490 Speaker 2: doing it effectively. 139 00:07:20,710 --> 00:07:24,490 Speaker 3: Third element here is to maximize clearance of not just 140 00:07:24,550 --> 00:07:28,400 Speaker 3: the upper but also the lower airways. Start with a 141 00:07:28,660 --> 00:07:32,870 Speaker 3: moderate breath in, moderate inhalation, and then try to do 142 00:07:33,010 --> 00:07:37,750 Speaker 3: a long, steady exhalation through the nostril instead of just 143 00:07:37,810 --> 00:07:40,730 Speaker 3: a short, intense burst. So try to stretch it out 144 00:07:40,790 --> 00:07:43,650 Speaker 3: over time. I think the idea from what I was 145 00:07:43,710 --> 00:07:48,820 Speaker 3: reading is that that will clear deeper down in the airways, which, 146 00:07:48,880 --> 00:07:51,240 Speaker 3: you know, clearing more of the mucus and buildup from 147 00:07:51,280 --> 00:07:53,760 Speaker 3: down there could help prevent disease. 148 00:07:53,780 --> 00:07:54,220 Speaker 2: Hmm. 149 00:07:55,370 --> 00:07:57,230 Speaker 3: So that's all I've got on the nose blowing paper. 150 00:07:57,270 --> 00:07:59,270 Speaker 3: But I thought that this was the rare case where 151 00:07:59,390 --> 00:08:02,310 Speaker 3: an Ig Nobel winning study really is probably going to 152 00:08:02,350 --> 00:08:04,650 Speaker 3: make me change what I do going forward. 153 00:08:04,670 --> 00:08:04,970 Speaker 2: Yeah. 154 00:08:05,430 --> 00:08:05,630 Speaker 1: Yeah. 155 00:08:05,690 --> 00:08:08,670 Speaker 2: That's I mean, this is a good one to highlight because, 156 00:08:08,690 --> 00:08:12,490 Speaker 2: of course, it involves blowing the nose, which is inherently funny. But, yeah, 157 00:08:12,550 --> 00:08:14,550 Speaker 2: it's something that people are going to be doing a 158 00:08:14,600 --> 00:08:16,940 Speaker 2: lot of, especially now that we're into the getting into 159 00:08:16,960 --> 00:08:20,120 Speaker 2: the colder months. So, yeah, take this knowledge with you 160 00:08:20,720 --> 00:08:22,760 Speaker 2: next time you're blowing your nose. Take a moment to 161 00:08:23,300 --> 00:08:27,610 Speaker 2: critique yourself. But be very sparing in critiquing your neighbor. 162 00:08:27,990 --> 00:08:30,590 Speaker 3: Oh, man, this is reminding me to get my flu shot. 163 00:08:30,630 --> 00:08:32,569 Speaker 3: I meant to do that a month ago, and now 164 00:08:32,610 --> 00:08:34,850 Speaker 3: here we are, and it's going to be Thanksgiving soon, 165 00:08:34,890 --> 00:08:36,370 Speaker 3: so I'm going to be doing that this week. 166 00:08:36,870 --> 00:08:38,690 Speaker 2: Yeah, make sure you time it with your Weird House 167 00:08:38,710 --> 00:08:41,160 Speaker 2: selection so that you're watching just the right movie in 168 00:08:41,179 --> 00:08:44,939 Speaker 2: case you get mild flu symptoms from the vaccine. Yeah. 169 00:08:46,360 --> 00:08:49,060 Speaker 3: Okay, but yeah, that's all I've got on nose blowing. 170 00:08:49,820 --> 00:08:51,780 Speaker 2: All right, I want to talk a bit here about 171 00:08:51,820 --> 00:08:55,750 Speaker 2: the Soil Science Prize. Worth noting, they don't always have these, 172 00:08:55,950 --> 00:08:59,970 Speaker 2: these prizes are often, the title is tailored to whatever 173 00:09:00,030 --> 00:09:02,210 Speaker 2: is being honored a given year. And that is the 174 00:09:02,230 --> 00:09:04,929 Speaker 2: case here. This is a, this is something that I 175 00:09:04,970 --> 00:09:09,130 Speaker 2: mentioned briefly in our last episode, because it was, we 176 00:09:09,170 --> 00:09:11,750 Speaker 2: were talking about the sorts of things that get honored 177 00:09:11,790 --> 00:09:14,510 Speaker 2: by the Ig Nobel's and how sometimes it's a serious 178 00:09:14,570 --> 00:09:16,710 Speaker 2: study that just has something funny about it. Other times 179 00:09:16,809 --> 00:09:20,330 Speaker 2: it's more of a tongue in cheek study, the publication 180 00:09:20,370 --> 00:09:23,380 Speaker 2: that they're honoring. And this one is more of a, 181 00:09:24,040 --> 00:09:31,459 Speaker 2: citizen scientist initiative, an educational initiative. And yeah, this won 182 00:09:31,500 --> 00:09:35,950 Speaker 2: the 2026 Ig Nobel Soil Science Prize, honoring a soil 183 00:09:36,010 --> 00:09:39,770 Speaker 2: science citizen scientist initiative to raise awareness in Switzerland. And 184 00:09:39,809 --> 00:09:43,170 Speaker 2: then afterwards, it ends up spreading to like 25 additional 185 00:09:43,210 --> 00:09:50,460 Speaker 2: countries about the importance of soil health. Launched in 2021, 186 00:09:50,460 --> 00:09:54,880 Speaker 2: it entailed the burial and retrieval of identical pairs of 187 00:09:55,000 --> 00:10:00,240 Speaker 2: cotton underpants and tea bags from soils ultimately around the world. 188 00:10:00,720 --> 00:10:02,900 Speaker 2: I don't think any of the in any of the 189 00:10:02,970 --> 00:10:06,309 Speaker 2: experiments took place in the Americas, but still they made 190 00:10:06,350 --> 00:10:10,090 Speaker 2: it to multiple continents besides the Americas. 191 00:10:10,970 --> 00:10:12,890 Speaker 3: Is it okay if I ask at this point, had 192 00:10:12,950 --> 00:10:17,069 Speaker 3: the cotton underpants been worn or were these unworn new 193 00:10:17,150 --> 00:10:18,330 Speaker 3: pairs of cotton underpants? 194 00:10:18,370 --> 00:10:20,590 Speaker 2: I believe these were new because it's essential for them 195 00:10:20,630 --> 00:10:23,550 Speaker 2: to all be in the same state before they're buried. 196 00:10:24,210 --> 00:10:26,360 Speaker 2: Because that's ultimately what you're doing is you're using the 197 00:10:27,000 --> 00:10:31,559 Speaker 2: underpants as a litmus test for soil health. Okay. So 198 00:10:31,640 --> 00:10:35,880 Speaker 2: we're recording this particular episode on October the 34th and 199 00:10:35,900 --> 00:10:38,640 Speaker 2: we're still dealing with the passing of yet another Halloween. 200 00:10:38,660 --> 00:10:41,070 Speaker 2: We're in a little bit of Denial, as always. And 201 00:10:41,530 --> 00:10:43,790 Speaker 2: so out of desperation, I want to point out that 202 00:10:43,809 --> 00:10:47,810 Speaker 2: this topic is also really key to zombie media. We 203 00:10:47,850 --> 00:10:49,849 Speaker 2: talk about the different types of zombies we see in 204 00:10:49,890 --> 00:10:53,490 Speaker 2: our zombie movies. And then what are those zombies wearing 205 00:10:53,570 --> 00:10:55,790 Speaker 2: when they emerge from the soil? What sort of state 206 00:10:55,910 --> 00:10:57,980 Speaker 2: of decay are they in when they climb out of 207 00:10:58,010 --> 00:10:59,500 Speaker 2: the soil? Oh, yeah. 208 00:10:59,520 --> 00:11:03,720 Speaker 3: So we've talked about wet zombies versus dry zombies, sort 209 00:11:03,740 --> 00:11:09,900 Speaker 3: of mucus zombies versus flesh zombies versus soil zombies. Earthy 210 00:11:09,950 --> 00:11:13,930 Speaker 3: zombies are very much a type, especially in certain Italian 211 00:11:13,970 --> 00:11:16,170 Speaker 3: horror movies, the ones that really have the kind of 212 00:11:16,410 --> 00:11:21,050 Speaker 3: mud or clay themed zombies that almost feel more like 213 00:11:21,170 --> 00:11:24,710 Speaker 3: emanations of the earth than remains of human bodies. 214 00:11:25,190 --> 00:11:29,700 Speaker 2: Yeah. Thinking about particularly like the Fulci zombie. And then 215 00:11:30,100 --> 00:11:34,080 Speaker 2: the burial ground zombies, burial ground being a zombie picture 216 00:11:34,300 --> 00:11:36,480 Speaker 2: from Italy that we discussed in Weird House in the past. 217 00:11:37,870 --> 00:11:40,590 Speaker 2: But those, yeah, those zombies have essentially become one with 218 00:11:40,650 --> 00:11:44,270 Speaker 2: both the dirt and I guess their underwear. While on 219 00:11:44,290 --> 00:11:46,150 Speaker 2: the other end of the spectrum, we see like the 220 00:11:46,170 --> 00:11:49,699 Speaker 2: zombie trash in Return of the Living Dead. And she 221 00:11:49,740 --> 00:11:53,780 Speaker 2: emerges from the grave without any underwear at all and 222 00:11:53,860 --> 00:11:56,179 Speaker 2: with very little signs of decay. Hmm. 223 00:11:56,520 --> 00:11:56,640 Speaker 1: Yeah. 224 00:11:57,200 --> 00:12:01,160 Speaker 2: So clearly more zombie-focused study is necessary, but let's go 225 00:12:01,179 --> 00:12:03,459 Speaker 2: ahead and turn back to the prize-winning entry here. 226 00:12:03,820 --> 00:12:04,080 Speaker 3: Okay. 227 00:12:04,380 --> 00:12:07,140 Speaker 2: So the Ig Nobel's single out two different articles, a 228 00:12:07,140 --> 00:12:12,400 Speaker 2: 2025 paper in science and a 2026 paper in plants, people, planet. 229 00:12:13,120 --> 00:12:18,309 Speaker 2: Lead author, Franz Binder and associates attended the ceremony to 230 00:12:18,429 --> 00:12:21,650 Speaker 2: accept the award. And the project here was, again, all 231 00:12:21,690 --> 00:12:25,270 Speaker 2: about soil health. So we've talked about soil on the 232 00:12:25,309 --> 00:12:27,719 Speaker 2: show before, and We've gotten our hands dirty a little 233 00:12:27,750 --> 00:12:31,720 Speaker 2: bit with the topic. What does soil do? Well, healthy 234 00:12:31,780 --> 00:12:36,180 Speaker 2: soil is, of course, a dynamic ecosystem. It's essentially alive. 235 00:12:37,600 --> 00:12:40,020 Speaker 2: And healthy soil does a lot of different things for us. 236 00:12:40,179 --> 00:12:44,320 Speaker 2: It supports plant growth. It filters and regulates our water 237 00:12:44,380 --> 00:12:49,410 Speaker 2: in multiple ways. It stores carbon. It cycles nutrients. And 238 00:12:50,370 --> 00:12:55,630 Speaker 2: in addition to that, we have microorganisms, fungi. Other organisms, 239 00:12:55,690 --> 00:13:00,189 Speaker 2: insects and so forth, worms, you know, everything that crawls 240 00:13:00,250 --> 00:13:03,600 Speaker 2: in and out that helps decompose that waste that ends 241 00:13:03,740 --> 00:13:07,040 Speaker 2: up on or in the soil, which I guess would 242 00:13:07,080 --> 00:13:09,320 Speaker 2: include the zombies. And that's why some of these Italian 243 00:13:09,360 --> 00:13:12,240 Speaker 2: zombies are coming out of the ground with like worms 244 00:13:12,300 --> 00:13:16,260 Speaker 2: and insects crawling on them. Right. For real. Yeah. So 245 00:13:16,320 --> 00:13:20,740 Speaker 2: the science paper, the science publication in the journal Science here, 246 00:13:21,730 --> 00:13:24,390 Speaker 2: throws out some key numbers that I wanted to feature 247 00:13:24,410 --> 00:13:27,469 Speaker 2: here as well, because they point out that 95% of 248 00:13:27,530 --> 00:13:32,030 Speaker 2: our food depends on soil, that soil harbors around 59% 249 00:13:32,030 --> 00:13:36,240 Speaker 2: of global biodiversity, and it's also the second largest carbon 250 00:13:36,250 --> 00:13:40,700 Speaker 2: reservoir on Earth. And in addition to the decomposition, which 251 00:13:40,720 --> 00:13:43,440 Speaker 2: we're about to get back to, a source of antibiotics 252 00:13:43,520 --> 00:13:47,540 Speaker 2: as well. Soil helps suppress pathogens. So healthy soil is 253 00:13:47,600 --> 00:13:52,630 Speaker 2: good for just... healthy everything else, including healthy people. So 254 00:13:52,790 --> 00:13:55,959 Speaker 2: if zombies were real, zombies would probably be a pretty 255 00:13:55,980 --> 00:13:58,839 Speaker 2: good soil indicator. Like what sort of zombies are emerging 256 00:13:58,900 --> 00:14:01,840 Speaker 2: from your soil? What state are they in? And, you know, 257 00:14:01,860 --> 00:14:05,540 Speaker 2: presumably a good Italian dirt zombie would be like, oh yeah, 258 00:14:05,559 --> 00:14:08,140 Speaker 2: that's great. We have some really healthy soil here. While 259 00:14:08,580 --> 00:14:14,589 Speaker 2: your Louisville, Kentucky trash zombie might raise some questions. But 260 00:14:15,010 --> 00:14:19,160 Speaker 2: since we don't have zombies, the researchers here distributed cotton 261 00:14:19,200 --> 00:14:24,550 Speaker 2: underwear and teabags, quote, as proxies for soil biological activity 262 00:14:24,650 --> 00:14:29,130 Speaker 2: and soil health. So, you know, underpants especially seemed like 263 00:14:29,150 --> 00:14:32,790 Speaker 2: the way to go for a number of reasons, including 264 00:14:32,840 --> 00:14:35,120 Speaker 2: just the novelty factor here, because, again, this is about 265 00:14:35,500 --> 00:14:40,800 Speaker 2: getting citizen scientists, regular people excited about soil health so 266 00:14:40,840 --> 00:14:43,390 Speaker 2: that you can educate them about soil health. and get 267 00:14:43,430 --> 00:14:46,040 Speaker 2: them doing something that is novel and fun, which is 268 00:14:46,240 --> 00:14:49,960 Speaker 2: burying and then retrieving underpants from the earth, which was 269 00:14:50,340 --> 00:14:52,420 Speaker 2: so exciting that I was like, I want to do 270 00:14:52,460 --> 00:14:55,560 Speaker 2: this now. I don't think they're actually doing this particular 271 00:14:55,580 --> 00:14:59,570 Speaker 2: study anymore. They have something else that's coming up that 272 00:14:59,590 --> 00:15:03,590 Speaker 2: I'll mention at the end of this, but it just 273 00:15:03,630 --> 00:15:06,010 Speaker 2: sounds like a fun time. Let's get some underpants. Let's 274 00:15:06,070 --> 00:15:09,380 Speaker 2: bury them. Let's dig them back up. Everybody likes to Well, 275 00:15:09,420 --> 00:15:11,800 Speaker 2: maybe not everyone, but there is a pleasure to be 276 00:15:11,860 --> 00:15:16,380 Speaker 2: found in retrieving something from the earth and observing what 277 00:15:16,480 --> 00:15:19,640 Speaker 2: state it's in. I'm not saying it's something disgusting, but 278 00:15:19,660 --> 00:15:23,100 Speaker 2: if you've ever been digging around in your own backyard 279 00:15:23,120 --> 00:15:27,220 Speaker 2: and you find a stuffed animal from decades past, that 280 00:15:27,280 --> 00:15:29,520 Speaker 2: sort of thing, that can be amusing. Yeah, yeah. 281 00:15:30,820 --> 00:15:32,020 Speaker 3: I thought for a second you were going to say 282 00:15:32,040 --> 00:15:34,800 Speaker 3: there's a universal pleasure in burying underpants. 283 00:15:35,380 --> 00:15:39,120 Speaker 2: Well, maybe we're just not doing it enough. You know, 284 00:15:39,260 --> 00:15:40,840 Speaker 2: we don't, I guess we don't have to. We tend to, 285 00:15:41,500 --> 00:15:43,420 Speaker 2: we often throw these things away or we, you know, 286 00:15:43,660 --> 00:15:46,230 Speaker 2: hopefully we're doing some sort of composting, but that's exactly 287 00:15:46,270 --> 00:15:49,150 Speaker 2: what they're doing here is they're doing natural composting of 288 00:15:49,190 --> 00:15:52,730 Speaker 2: the cotton underpants. So the basic idea here is that 289 00:15:53,050 --> 00:15:58,180 Speaker 2: the identical cotton underwears, along with the tea bags, which 290 00:15:58,220 --> 00:16:01,620 Speaker 2: are also identical, are buried for a set period of time. 291 00:16:02,480 --> 00:16:04,830 Speaker 2: So you'll So all this stuff is buried. And then 292 00:16:04,870 --> 00:16:08,410 Speaker 2: after 30 days, like half of the undies and teabags 293 00:16:08,490 --> 00:16:11,330 Speaker 2: are removed from the earth. And then after 60 days, 294 00:16:11,410 --> 00:16:14,650 Speaker 2: the rest are retrieved from the soil as well. And 295 00:16:14,670 --> 00:16:17,600 Speaker 2: the idea here is that the state of underwear and 296 00:16:17,640 --> 00:16:21,240 Speaker 2: teabags will reveal how active and healthy the soil is 297 00:16:21,360 --> 00:16:27,450 Speaker 2: based on the state of the organic matter's decomposition. Because that's, 298 00:16:27,570 --> 00:16:28,990 Speaker 2: of course, key to all of this is that if 299 00:16:29,030 --> 00:16:31,870 Speaker 2: you bury underwear in the soil, if everything's healthy down there, 300 00:16:32,760 --> 00:16:35,380 Speaker 2: you know, it's going to begin to break down. Yeah. 301 00:16:36,520 --> 00:16:39,220 Speaker 2: This is why we keep our active underwear in a 302 00:16:39,280 --> 00:16:42,220 Speaker 2: drawer and not in the ground. That's right. If you're 303 00:16:42,240 --> 00:16:45,800 Speaker 2: bearing your underwear every night, you're doing it wrong. Or 304 00:16:45,820 --> 00:16:50,660 Speaker 2: you're engaging in activities that maybe should be questioned. So 305 00:16:50,680 --> 00:16:52,840 Speaker 2: the way this would work then is that everything is 306 00:16:53,180 --> 00:16:55,380 Speaker 2: dug up, gets dried out, and then they would mail 307 00:16:55,440 --> 00:17:00,350 Speaker 2: it back to AgroScope. This is the Swiss Agricultural Research Center. 308 00:17:00,950 --> 00:17:03,950 Speaker 2: And then it would undergo analysis. They were able to 309 00:17:03,970 --> 00:17:07,369 Speaker 2: build out a data set of not only the Swiss 310 00:17:07,390 --> 00:17:10,429 Speaker 2: soil health, but also essentially global soil health with some 311 00:17:10,470 --> 00:17:15,870 Speaker 2: of these other far-flung locations like other places in Europe, Japan, 312 00:17:16,850 --> 00:17:21,130 Speaker 2: also in Africa. And not only is this, again, about 313 00:17:21,170 --> 00:17:23,810 Speaker 2: the gathering of data, but it's also a way to 314 00:17:23,910 --> 00:17:27,470 Speaker 2: reach new audiences and get them excited about something that 315 00:17:27,560 --> 00:17:28,980 Speaker 2: might otherwise not seem exciting. 316 00:17:29,260 --> 00:17:29,359 Speaker 1: Hmm. 317 00:17:30,590 --> 00:17:34,450 Speaker 2: The science article in particular really breaks down the whole process, though, 318 00:17:34,510 --> 00:17:38,190 Speaker 2: including the drying, the cleaning, and the visual analysis of 319 00:17:38,210 --> 00:17:42,150 Speaker 2: the resurrected underwear. Like the idea is that, you know, 320 00:17:42,550 --> 00:17:44,290 Speaker 2: how much of the underwear is still there is something 321 00:17:44,310 --> 00:17:47,810 Speaker 2: that can be figured out visually. And they actually have 322 00:17:47,850 --> 00:17:50,810 Speaker 2: like a whole equation. There are actually multiple equations related 323 00:17:50,850 --> 00:17:54,209 Speaker 2: to underwear breakdown in this paper that I'm not going 324 00:17:54,230 --> 00:17:57,790 Speaker 2: to attempt to regurgitate here, but you can look them up. 325 00:17:57,830 --> 00:18:01,990 Speaker 2: This is a free article to access. But they write, quote, 326 00:18:02,190 --> 00:18:05,750 Speaker 2: area loss was calculated relative to the area of new 327 00:18:05,830 --> 00:18:09,450 Speaker 2: underpants and expressed as percentage decomposition. 328 00:18:09,930 --> 00:18:13,820 Speaker 3: OK, so they had a quantitative method of visual analysis, 329 00:18:13,890 --> 00:18:16,860 Speaker 3: not just looking at them and getting a vibe like, yeah, 330 00:18:16,920 --> 00:18:17,620 Speaker 3: pretty gross. 331 00:18:18,040 --> 00:18:21,200 Speaker 2: Yeah, because otherwise you're I mean, if they had not 332 00:18:21,240 --> 00:18:22,580 Speaker 2: done that, I guess it would still would have been 333 00:18:22,900 --> 00:18:25,300 Speaker 2: fun outreach. But the idea is like this was they 334 00:18:25,340 --> 00:18:28,859 Speaker 2: determined the best way to get usable data out of 335 00:18:28,920 --> 00:18:30,000 Speaker 2: this whole experiment. 336 00:18:30,260 --> 00:18:30,389 Speaker 1: Mm hmm. 337 00:18:31,590 --> 00:18:34,710 Speaker 2: So they point out that one of the biggest factors 338 00:18:34,840 --> 00:18:40,100 Speaker 2: concerning like how healthy any given area studied here turned 339 00:18:40,119 --> 00:18:43,120 Speaker 2: out to be was land use. They said, quote, land 340 00:18:43,240 --> 00:18:47,480 Speaker 2: use was the most important predictor of decomposition processes, followed 341 00:18:47,520 --> 00:18:51,650 Speaker 2: by soil chemical parameters. Private gardens, the land use type 342 00:18:51,670 --> 00:18:54,770 Speaker 2: with the highest levels of soil, organic carbon and nutrients 343 00:18:55,170 --> 00:18:59,490 Speaker 2: exhibited the greatest biological activity. Whereas lawns showed the lowest 344 00:18:59,790 --> 00:19:05,150 Speaker 2: with crop lands and grasslands falling in between. So, and 345 00:19:05,190 --> 00:19:07,550 Speaker 2: there's some, I guess, some good data here as well. 346 00:19:07,570 --> 00:19:09,030 Speaker 2: Like if you were going to do your own version 347 00:19:09,070 --> 00:19:11,729 Speaker 2: of this for purely your own amusement, if you were 348 00:19:11,750 --> 00:19:16,790 Speaker 2: to bury identical undies in your front yard, in your garden, 349 00:19:16,810 --> 00:19:20,790 Speaker 2: and in your garden in the backyard, presumably, like you 350 00:19:20,830 --> 00:19:24,169 Speaker 2: would probably see a difference between the two based on 351 00:19:24,609 --> 00:19:25,919 Speaker 2: just how active the soil is. 352 00:19:27,580 --> 00:19:31,420 Speaker 3: Now, I do kind of wonder how how does the 353 00:19:31,619 --> 00:19:35,230 Speaker 3: differential land use manifest in these different soil conditions? Like 354 00:19:35,270 --> 00:19:38,889 Speaker 3: they mentioned, the organic carbon and nutrients like is that 355 00:19:38,910 --> 00:19:44,510 Speaker 3: going to be because of using like pre-prepared or nutrient 356 00:19:44,530 --> 00:19:46,830 Speaker 3: filled soils in a garden? Or is it because of 357 00:19:46,890 --> 00:19:49,290 Speaker 3: what happens in a garden, the types of plants that 358 00:19:49,330 --> 00:19:50,860 Speaker 3: grow there? Do you know that? 359 00:19:52,160 --> 00:19:53,940 Speaker 2: My understanding is that, yeah, a lot of it is 360 00:19:53,960 --> 00:19:55,859 Speaker 2: going to be based on like, you know, what's going 361 00:19:56,000 --> 00:20:00,000 Speaker 2: on in a basic background garden is you're probably having 362 00:20:00,040 --> 00:20:03,860 Speaker 2: multiple different plants. There's more of an emphasis on having 363 00:20:03,900 --> 00:20:07,710 Speaker 2: quality soil. You know, it's not going to be a 100% 364 00:20:07,710 --> 00:20:12,550 Speaker 2: like natural plant. like wild situation, but it's going to 365 00:20:12,570 --> 00:20:16,149 Speaker 2: be better than like a monocrop situation. And it's going 366 00:20:16,170 --> 00:20:20,020 Speaker 2: to be better than just like a tightly controlled lawn environment, obviously. 367 00:20:20,760 --> 00:20:23,139 Speaker 2: So it's just, it's just thriving a lot more, at 368 00:20:23,220 --> 00:20:26,920 Speaker 2: least seasonally. Yeah. So yeah, I just thought it was 369 00:20:26,980 --> 00:20:29,860 Speaker 2: a fun little idea. If you want to learn more 370 00:20:29,920 --> 00:20:33,080 Speaker 2: about what they've been up to, you can go to soilproof.org. 371 00:20:33,780 --> 00:20:36,300 Speaker 2: There's a great deal more information, including a map of 372 00:20:36,320 --> 00:20:38,770 Speaker 2: the sites. You can pull up like a a local 373 00:20:39,050 --> 00:20:41,090 Speaker 2: map and then like a whole world map to show 374 00:20:41,130 --> 00:20:45,560 Speaker 2: like where these studies were conducted. And again, I don't 375 00:20:45,619 --> 00:20:51,060 Speaker 2: think the underpants program is still going on and they didn't, 376 00:20:51,140 --> 00:20:54,359 Speaker 2: I don't think they did anything in the Americas. But 377 00:20:54,400 --> 00:20:57,540 Speaker 2: while that study is finished, they are, I believe, open 378 00:20:57,560 --> 00:21:01,340 Speaker 2: to participants in the upcoming soil bodies effort. You know, 379 00:21:01,380 --> 00:21:03,750 Speaker 2: do look into, I don't know exactly how wide, if 380 00:21:03,790 --> 00:21:05,729 Speaker 2: they're really going for a global thing or if it's, 381 00:21:05,890 --> 00:21:08,810 Speaker 2: they're starting more regional or what, But they're exploring, quote, 382 00:21:08,910 --> 00:21:12,050 Speaker 2: how different textiles break down in various types of soil. 383 00:21:12,530 --> 00:21:14,950 Speaker 2: And it's apparently going to have both a scientific and 384 00:21:15,080 --> 00:21:18,800 Speaker 2: artistic approach. So it's going to be where fiber arts 385 00:21:19,060 --> 00:21:24,080 Speaker 2: meets soil science meets rotting underwear in the ground. So 386 00:21:24,380 --> 00:21:26,100 Speaker 2: check out their website to learn more about that if 387 00:21:26,140 --> 00:21:27,639 Speaker 2: that interests you. 388 00:21:28,580 --> 00:21:32,139 Speaker 3: I'm curious what percentage of buried underpants never got dug up. 389 00:21:32,480 --> 00:21:34,960 Speaker 3: You know, you always have some drop off in experiments 390 00:21:34,980 --> 00:21:36,860 Speaker 3: like people who begin but don't finish. 391 00:21:36,980 --> 00:21:40,280 Speaker 2: But yeah. Yeah, yeah. I don't have the numbers in 392 00:21:40,340 --> 00:21:42,060 Speaker 2: front of me, but there was, I believe there was 393 00:21:42,100 --> 00:21:46,359 Speaker 2: some drop off, you know, that's referenced in the totals. 394 00:21:47,660 --> 00:21:49,140 Speaker 3: Some of the undies are still out there. 395 00:21:49,640 --> 00:21:52,200 Speaker 2: Yeah, yeah. And since they're out of sync with the 396 00:21:52,240 --> 00:21:54,000 Speaker 2: other undies, you know, they're not really going to tell 397 00:21:54,040 --> 00:21:54,480 Speaker 2: us anything. 398 00:21:54,880 --> 00:21:56,820 Speaker 3: Yeah. Or they're still out there if the soil hasn't 399 00:21:57,000 --> 00:22:10,489 Speaker 3: finished them. Okay, are you ready to talk about this 400 00:22:10,530 --> 00:22:12,370 Speaker 3: year's Ig Nobel Peace Prize? 401 00:22:12,750 --> 00:22:15,850 Speaker 2: Yeah, yeah, this is always a fun category. I remember 402 00:22:15,910 --> 00:22:20,590 Speaker 2: some past award winners for the Peace Prize, and there's 403 00:22:20,670 --> 00:22:23,530 Speaker 2: usually some sort of satirical twist to everything. 404 00:22:23,930 --> 00:22:27,399 Speaker 3: Usually the Peace Prize is awarded to some kind of 405 00:22:27,480 --> 00:22:29,960 Speaker 3: study that involves people behaving badly. 406 00:22:30,140 --> 00:22:30,300 Speaker 1: Yes. 407 00:22:31,590 --> 00:22:34,790 Speaker 3: So the prize this year was awarded to Jamie Arona Krems, 408 00:22:35,070 --> 00:22:41,859 Speaker 3: Rebecca Honnell-Peters, Lorian Mary, Keela Williams, and Daniel Schneiser, quote, 409 00:22:42,040 --> 00:22:45,639 Speaker 3: for documenting that we value friends who are vicious to 410 00:22:45,680 --> 00:22:50,740 Speaker 3: people we dislike. So the prize-winning research appeared in a 411 00:22:50,780 --> 00:22:53,869 Speaker 3: paper published in the journal Evolution and Human Behavior in 412 00:22:53,910 --> 00:22:57,960 Speaker 3: the year 2023. I dug up the full text of 413 00:22:58,000 --> 00:23:00,919 Speaker 3: the paper and was quite pleased by the epigraph that 414 00:23:00,960 --> 00:23:03,859 Speaker 3: they chose to put up top. It was about a 415 00:23:03,940 --> 00:23:08,770 Speaker 3: resolution passed by the City Council of Philadelphia in 2018, 416 00:23:08,770 --> 00:23:13,730 Speaker 3: welcoming the Philadelphia Flyers, at the time, new mascot, Gritty. 417 00:23:13,790 --> 00:23:14,650 Speaker 2: You know Gritty, Rob. 418 00:23:15,510 --> 00:23:20,370 Speaker 3: The text of this resolution included the sentence, Gritty may 419 00:23:20,430 --> 00:23:23,710 Speaker 3: be a hideous monster, but he is our hideous monster. Yeah. 420 00:23:25,190 --> 00:23:29,020 Speaker 3: So the authors begin by talking about the state of 421 00:23:29,280 --> 00:23:32,820 Speaker 3: scientific research on the nature of friendship. And they note 422 00:23:32,859 --> 00:23:35,980 Speaker 3: that the majority of research on the friend relationship is 423 00:23:36,040 --> 00:23:39,280 Speaker 3: focused on what they call the dyad, meaning the direct 424 00:23:39,380 --> 00:23:44,169 Speaker 3: relationship between the friend and the self. Therefore, most of 425 00:23:44,230 --> 00:23:48,630 Speaker 3: the research on how people want their friends to behave 426 00:23:49,109 --> 00:23:51,750 Speaker 3: is really focused on how people want their friends to 427 00:23:51,810 --> 00:23:55,369 Speaker 3: behave toward them. In other words, I want a friend 428 00:23:55,430 --> 00:23:59,550 Speaker 3: who treats me well. And a large body of research 429 00:23:59,609 --> 00:24:03,570 Speaker 3: confirms exactly what we would suspect about this. The majority 430 00:24:03,590 --> 00:24:06,570 Speaker 3: of people, of course, want friends who are kind to them, 431 00:24:06,770 --> 00:24:09,169 Speaker 3: and they do not want friends who are cruel or 432 00:24:09,230 --> 00:24:12,790 Speaker 3: vicious to them. Not a huge surprise. The study doesn't 433 00:24:12,830 --> 00:24:15,710 Speaker 3: really go into this here, but it did raise this 434 00:24:16,390 --> 00:24:19,750 Speaker 3: an issue, a related issue for me. Obviously, very few 435 00:24:19,790 --> 00:24:22,909 Speaker 3: people are going to actually prefer friends who are mean 436 00:24:22,950 --> 00:24:25,720 Speaker 3: to them. But I started to wonder, what are the 437 00:24:25,760 --> 00:24:30,459 Speaker 3: conditions that tend to make people tolerate friends that are 438 00:24:30,500 --> 00:24:33,659 Speaker 3: mean to them? One example here is I think it's 439 00:24:33,680 --> 00:24:37,010 Speaker 3: a pretty common experience for people in, say, elementary school 440 00:24:37,170 --> 00:24:40,320 Speaker 3: or middle school age. to have some friends who are 441 00:24:40,359 --> 00:24:43,080 Speaker 3: just nasty to you most of the time. But for 442 00:24:43,160 --> 00:24:47,570 Speaker 3: some reason, even though they're mean, like you'd still voluntarily 443 00:24:47,619 --> 00:24:50,709 Speaker 3: spend time with them. My guess is that on average, 444 00:24:50,770 --> 00:24:53,690 Speaker 3: this kind of relationship gets less common as people get 445 00:24:53,810 --> 00:24:55,870 Speaker 3: older and you kind of realize like, I don't have 446 00:24:55,910 --> 00:24:58,790 Speaker 3: to hang out with this type of person. But yeah, 447 00:24:58,970 --> 00:25:01,679 Speaker 3: I don't know. I'm just wondering like why, why in 448 00:25:01,780 --> 00:25:05,820 Speaker 3: some cases do those friend relationships persist and not in others? 449 00:25:05,840 --> 00:25:05,919 Speaker 1: Yeah. 450 00:25:06,430 --> 00:25:08,409 Speaker 2: Yeah, I mean, I guess it gets complicated when you 451 00:25:08,430 --> 00:25:11,369 Speaker 2: think about like larger friend groups, when you start thinking 452 00:25:11,430 --> 00:25:15,270 Speaker 2: about social groups that maybe have some things in common 453 00:25:15,290 --> 00:25:18,629 Speaker 2: with friend groups, but maybe are a little broader than that. And, 454 00:25:18,650 --> 00:25:20,110 Speaker 2: you know, makes us think of just sort of the 455 00:25:22,210 --> 00:25:27,200 Speaker 2: deeper dynamics of human social groups where like there is 456 00:25:27,240 --> 00:25:31,540 Speaker 2: a survival incentive in sticking with the group. And is 457 00:25:31,600 --> 00:25:36,480 Speaker 2: it worth potentially being kicked out of the group? you know, 458 00:25:36,500 --> 00:25:40,679 Speaker 2: to voice your displeasure with your treatment by one of 459 00:25:40,740 --> 00:25:43,540 Speaker 2: the people in that group. Yeah. So it gets a 460 00:25:43,560 --> 00:25:44,620 Speaker 2: little complicated, I guess. 461 00:25:44,920 --> 00:25:45,620 Speaker 3: I think that's right. 462 00:25:45,660 --> 00:25:45,880 Speaker 2: Yeah. 463 00:25:45,900 --> 00:25:49,369 Speaker 3: And I think that that'll interact with an idea that 464 00:25:49,390 --> 00:25:52,369 Speaker 3: the authors will bring up in a minute. But so 465 00:25:52,410 --> 00:25:55,470 Speaker 3: the authors mentioned in their intro that some what are 466 00:25:55,490 --> 00:26:00,280 Speaker 3: called cooperative accounts of friendship predict that because we want 467 00:26:00,359 --> 00:26:04,310 Speaker 3: friends who treat us well, we in general will seek 468 00:26:04,369 --> 00:26:08,890 Speaker 3: out friends who display high pro-sociality overall. In other words, 469 00:26:09,310 --> 00:26:12,430 Speaker 3: we want our friends to be nice people, people who 470 00:26:12,690 --> 00:26:16,000 Speaker 3: generally treat other people well, at least in part because 471 00:26:16,040 --> 00:26:19,260 Speaker 3: that's a predictor of how they will treat us. But 472 00:26:19,300 --> 00:26:23,200 Speaker 3: the authors complicate this account by using what they call 473 00:26:23,340 --> 00:26:30,169 Speaker 3: an embedded dyadic framework, which, quote, emphasizes that dyads, e.g. friend-pairs, 474 00:26:30,950 --> 00:26:36,359 Speaker 3: exist embedded in wider and often densely interconnected social networks, 475 00:26:36,820 --> 00:26:41,159 Speaker 3: wherein one's friends inevitably interact with other people. So this 476 00:26:41,200 --> 00:26:43,200 Speaker 3: is kind of what you were just saying, Rob. It's 477 00:26:43,300 --> 00:26:47,109 Speaker 3: recognizing that you can't really study friendship just as a 478 00:26:47,190 --> 00:26:51,230 Speaker 3: dyad in isolation. It's a relationship between two people that 479 00:26:51,290 --> 00:26:54,550 Speaker 3: also exists in relation to a bunch of other people. 480 00:26:54,570 --> 00:26:54,649 Speaker 2: Yeah. 481 00:26:56,290 --> 00:26:59,780 Speaker 3: And so you not only are you affected by the 482 00:26:59,820 --> 00:27:03,920 Speaker 3: ways that your friends treat you directly, you're also affected 483 00:27:03,980 --> 00:27:06,960 Speaker 3: by the way that your friends treat other people in 484 00:27:06,980 --> 00:27:10,119 Speaker 3: your broader social circle. And by the way, other people 485 00:27:10,220 --> 00:27:15,510 Speaker 3: treat your friends. Those interactions affect you indirectly in complex ways. 486 00:27:16,590 --> 00:27:20,490 Speaker 3: And the author's right, quote, because one's friends also interact 487 00:27:20,510 --> 00:27:24,619 Speaker 3: with other people, including one's rivals. we suggest that people 488 00:27:24,720 --> 00:27:28,960 Speaker 3: might sometimes prefer friends who behave with greater monstrousness than 489 00:27:29,020 --> 00:27:33,320 Speaker 3: brotherly love. And this would challenge accounts of friendship that 490 00:27:33,359 --> 00:27:36,820 Speaker 3: claim we are mainly looking for friends who are maximally 491 00:27:36,880 --> 00:27:42,480 Speaker 3: pro-social overall. So why might we want friends to be 492 00:27:42,770 --> 00:27:46,090 Speaker 3: good to us but bad to others versus friends who 493 00:27:46,130 --> 00:27:50,900 Speaker 3: are just good to everyone, including us? Hypothetically, it could 494 00:27:50,980 --> 00:27:55,680 Speaker 3: be adaptive to value friends who are generally unprincipled but 495 00:27:55,810 --> 00:27:58,070 Speaker 3: loyal to you. So you can think up lots of 496 00:27:58,770 --> 00:28:03,370 Speaker 3: situations where this might be a benefit. Here's an example. 497 00:28:03,430 --> 00:28:07,530 Speaker 3: Like an enemy of yours says to your friend, I'll 498 00:28:07,570 --> 00:28:09,770 Speaker 3: tell you something if you promise to keep it a secret. 499 00:28:10,290 --> 00:28:12,910 Speaker 3: They promise. And then the enemy tells them of some 500 00:28:13,010 --> 00:28:16,320 Speaker 3: plan they have to do something nasty to you. So 501 00:28:16,480 --> 00:28:20,280 Speaker 3: a friend there who keeps their promises and is perfectly 502 00:28:20,340 --> 00:28:23,530 Speaker 3: trustworthy now cannot tell you what they know because they 503 00:28:23,570 --> 00:28:27,870 Speaker 3: promise not to tell. In that situation, you actually want 504 00:28:27,910 --> 00:28:31,790 Speaker 3: a friend who will be untrustworthy to your enemy, who 505 00:28:31,830 --> 00:28:34,869 Speaker 3: will break the promise and who will warn you. And 506 00:28:34,910 --> 00:28:37,990 Speaker 3: you can imagine other scenarios like this. You want a 507 00:28:38,050 --> 00:28:42,520 Speaker 3: friend who is kind and generous, but do people always 508 00:28:42,560 --> 00:28:45,830 Speaker 3: want a friend who is just generally kind and generous. 509 00:28:45,890 --> 00:28:48,930 Speaker 3: What if that universal generosity means they end up giving 510 00:28:49,010 --> 00:28:51,600 Speaker 3: more to others than they give to you, their friend? 511 00:28:53,130 --> 00:28:53,800 Speaker 2: Yeah. 512 00:28:53,860 --> 00:28:54,040 Speaker 1: Yeah. 513 00:28:54,130 --> 00:28:57,900 Speaker 2: I feel like there was, um, there was, there was 514 00:28:57,940 --> 00:29:00,459 Speaker 2: a sitcom I was watching recently where that was, that 515 00:29:00,480 --> 00:29:02,400 Speaker 2: was kind of like a wrinkle in a friend group 516 00:29:02,420 --> 00:29:04,620 Speaker 2: where they realized, Oh, this guy's great. And he's a 517 00:29:04,640 --> 00:29:06,700 Speaker 2: part of the, you know, they think he's just a 518 00:29:06,720 --> 00:29:09,100 Speaker 2: great friend, but then they start observing that, Oh, he's 519 00:29:09,180 --> 00:29:11,720 Speaker 2: kind of, he's great to everybody. And maybe that makes 520 00:29:11,780 --> 00:29:16,810 Speaker 2: my friendship a little less, um, less special. Yeah, totally. So, yeah, 521 00:29:17,130 --> 00:29:18,830 Speaker 2: I could definitely see that being a factor here. 522 00:29:19,190 --> 00:29:21,360 Speaker 3: And I think there is some research showing that at 523 00:29:21,440 --> 00:29:24,280 Speaker 3: least sometimes we do kind of feel that way, and 524 00:29:24,340 --> 00:29:27,120 Speaker 3: maybe not always, but sometimes that is a reaction that 525 00:29:27,140 --> 00:29:30,980 Speaker 3: can be provoked, that maybe we want people to treat 526 00:29:31,120 --> 00:29:33,770 Speaker 3: us better than they treat other people, not the same, 527 00:29:33,870 --> 00:29:35,730 Speaker 3: not good to everybody equally. 528 00:29:35,750 --> 00:29:37,850 Speaker 2: Yeah. Otherwise, what are we doing here, right? Yeah. 529 00:29:39,050 --> 00:29:42,150 Speaker 3: So, first of all, the researchers found that if you 530 00:29:42,170 --> 00:29:48,420 Speaker 3: don't specify who the behavior is directed toward people generally 531 00:29:48,500 --> 00:29:51,940 Speaker 3: say they want their friends to treat people the same 532 00:29:52,020 --> 00:29:54,560 Speaker 3: way that they want their friends to treat them you 533 00:29:54,580 --> 00:29:56,680 Speaker 3: know so like I want my close friends to be 534 00:29:56,760 --> 00:29:59,840 Speaker 3: kind and trustworthy to me And I also want my 535 00:29:59,940 --> 00:30:04,500 Speaker 3: friends to be kind and trustworthy to unspecified people. But 536 00:30:04,740 --> 00:30:07,620 Speaker 3: they also found people on average want their close friends 537 00:30:07,720 --> 00:30:11,850 Speaker 3: to treat them better than they would treat a hypothetical stranger. 538 00:30:11,950 --> 00:30:14,730 Speaker 3: So now if you give somebody a stranger to imagine, 539 00:30:14,750 --> 00:30:18,410 Speaker 3: maybe don't treat them quite as good as you treat me. 540 00:30:18,650 --> 00:30:22,400 Speaker 3: We want special treatment from our friends. And sometimes, but 541 00:30:22,480 --> 00:30:27,230 Speaker 3: not always, people, quote, prefer friends who are more vicious 542 00:30:27,310 --> 00:30:32,910 Speaker 3: than pro-social, for instance, toward one's enemies. And specifically, the 543 00:30:32,990 --> 00:30:40,920 Speaker 3: preference for viciousness over pro-sociality held in the U.S. samples, 544 00:30:41,380 --> 00:30:44,500 Speaker 3: but it did not reach significance in the India-based sample, 545 00:30:44,560 --> 00:30:46,840 Speaker 3: which is interesting. And the authors note that that could 546 00:30:46,880 --> 00:30:51,450 Speaker 3: be a genuine cultural or ecologically-based difference, or it could 547 00:30:51,530 --> 00:30:54,170 Speaker 3: be a result of low statistical power in the India region. 548 00:30:54,430 --> 00:30:57,580 Speaker 3: in the India based results. So they weren't sure. So 549 00:30:57,680 --> 00:31:00,920 Speaker 3: it feels like a contradiction that people would say, yeah, 550 00:31:01,040 --> 00:31:04,580 Speaker 3: I want friends who treat people with kindness and trustworthiness 551 00:31:04,640 --> 00:31:07,800 Speaker 3: and not viciousness, except maybe actually I do want them 552 00:31:07,840 --> 00:31:12,140 Speaker 3: to be vicious toward my rivals. Um, but it is not, 553 00:31:12,240 --> 00:31:15,540 Speaker 3: this is not the only such contradiction in human relationships. 554 00:31:15,640 --> 00:31:19,640 Speaker 3: The authors highlight other documented examples of double standards in 555 00:31:19,700 --> 00:31:24,300 Speaker 3: our preferences for friends and romantic partners. One example they 556 00:31:24,360 --> 00:31:27,800 Speaker 3: cite that I thought was interesting is that people expect 557 00:31:27,900 --> 00:31:31,960 Speaker 3: their friends to keep their secrets, but to tell them 558 00:31:32,140 --> 00:31:35,360 Speaker 3: other people's secrets. So you want a friend who is 559 00:31:35,440 --> 00:31:39,420 Speaker 3: good at keeping secrets for you, but not from you. 560 00:31:40,240 --> 00:31:44,180 Speaker 3: And people become upset when this double standard is violated. 561 00:31:44,260 --> 00:31:47,280 Speaker 3: Like it's kind of not a fair expectation to have 562 00:31:47,400 --> 00:31:50,940 Speaker 3: because it is self-contradictory, but we still do want it 563 00:31:50,980 --> 00:31:51,400 Speaker 3: that way. 564 00:31:52,120 --> 00:31:55,580 Speaker 2: Yeah. Yeah, absolutely. I mean, you would be understandably upset 565 00:31:55,700 --> 00:31:58,720 Speaker 2: if you found out that, uh, that, uh, that your, 566 00:31:58,860 --> 00:32:01,580 Speaker 2: your friend was, uh, even, even if they were sharing 567 00:32:01,620 --> 00:32:05,700 Speaker 2: someone else's secrets with you, that they were betraying your secrets. Yeah, exactly. Yeah. Um, 568 00:32:06,160 --> 00:32:07,900 Speaker 2: in a similar way, it's like, you want a friend 569 00:32:08,030 --> 00:32:10,640 Speaker 2: you can, you can talk smack with about other people, 570 00:32:11,110 --> 00:32:12,850 Speaker 2: but you don't want your friend talking smack with other 571 00:32:12,890 --> 00:32:13,610 Speaker 2: people about you. 572 00:32:13,970 --> 00:32:14,170 Speaker 3: Right. 573 00:32:14,350 --> 00:32:14,610 Speaker 1: Yeah. 574 00:32:14,850 --> 00:32:17,330 Speaker 2: And, um, and then that, you know, and then that you, you, 575 00:32:17,450 --> 00:32:19,270 Speaker 2: you want a friend who's maybe a little bit, um, 576 00:32:20,030 --> 00:32:21,450 Speaker 2: You know, it gets it gets a little bit mean 577 00:32:21,510 --> 00:32:24,030 Speaker 2: in the things they say about the people that you're 578 00:32:24,050 --> 00:32:24,930 Speaker 2: talking smack about. 579 00:32:25,310 --> 00:32:30,020 Speaker 3: Yeah, totally. The authors also point point to research by 580 00:32:30,200 --> 00:32:34,500 Speaker 3: Shaw and co-authors from 2016, which showed something that I 581 00:32:34,540 --> 00:32:37,620 Speaker 3: think most people know this at some level from experience. 582 00:32:38,640 --> 00:32:41,610 Speaker 3: They found that if a friend is having a dispute 583 00:32:41,790 --> 00:32:46,710 Speaker 3: with other people. and you display neutrality in that dispute, 584 00:32:46,870 --> 00:32:50,130 Speaker 3: it is very possible your friend will take this neutrality 585 00:32:50,270 --> 00:32:54,930 Speaker 3: as active opposition. And this can make a lot of 586 00:32:54,990 --> 00:32:58,650 Speaker 3: situations in friend groups difficult. I think a classic example 587 00:32:58,690 --> 00:33:02,600 Speaker 3: of this is like a romantic breakup within a friend group. 588 00:33:03,400 --> 00:33:06,820 Speaker 3: That can be really difficult if people are friends with 589 00:33:06,960 --> 00:33:11,360 Speaker 3: both people in the relationship. And maybe neither of them, like, 590 00:33:11,400 --> 00:33:14,959 Speaker 3: did anything actively awful that would end the friendship with 591 00:33:15,000 --> 00:33:18,360 Speaker 3: the others. But the breakup is not exactly on good terms. 592 00:33:18,820 --> 00:33:22,469 Speaker 3: So people find themselves forced to pick sides if they 593 00:33:22,510 --> 00:33:26,110 Speaker 3: want to remain friends with at least one person. Because 594 00:33:26,190 --> 00:33:29,090 Speaker 3: just saying, like, I am neutral on this will often 595 00:33:29,170 --> 00:33:32,310 Speaker 3: be seen as a betrayal by both parties. Like, if 596 00:33:32,350 --> 00:33:34,950 Speaker 3: you're not willing to badmouth my ex with me, you're 597 00:33:34,990 --> 00:33:35,510 Speaker 3: against me. 598 00:33:35,530 --> 00:33:36,450 Speaker 2: Yeah, yeah. 599 00:33:37,190 --> 00:33:39,410 Speaker 3: So I think this is an interesting finding, though I 600 00:33:39,470 --> 00:33:44,030 Speaker 3: do want to emphasize that none of these experiments involved 601 00:33:44,290 --> 00:33:48,290 Speaker 3: observations of like behavior on a task or practices in 602 00:33:48,330 --> 00:33:52,710 Speaker 3: the real world. This research was based entirely on self-reported 603 00:33:52,790 --> 00:33:57,550 Speaker 3: preferences and answers about like hypothetical situations on a survey. 604 00:33:58,150 --> 00:34:02,100 Speaker 3: So what we have here is what people would consciously 605 00:34:02,230 --> 00:34:05,730 Speaker 3: admit about what they're looking for in a friend. I 606 00:34:05,770 --> 00:34:09,759 Speaker 3: have to wonder if people would demonstrate even larger revealed 607 00:34:09,860 --> 00:34:14,359 Speaker 3: preferences for vicious allies in like experimental conditions where they 608 00:34:14,400 --> 00:34:16,990 Speaker 3: don't have to explicitly say it, where it's some kind of, 609 00:34:17,040 --> 00:34:21,040 Speaker 3: you know, revealed preference through activities and in a test. 610 00:34:21,780 --> 00:34:23,480 Speaker 3: Of course, we don't know that's the case, but I 611 00:34:23,760 --> 00:34:25,900 Speaker 3: would be curious and I would kind of suspect that. 612 00:34:26,780 --> 00:34:30,260 Speaker 2: Yeah, yeah. I wonder, too, if part of it is like, 613 00:34:30,280 --> 00:34:31,910 Speaker 2: you know, the idea that like, oh, this friend's really 614 00:34:31,950 --> 00:34:35,649 Speaker 2: vicious regarding my enemies. But they're really, but they're nice 615 00:34:35,690 --> 00:34:37,770 Speaker 2: to me. And therefore, like, I know that that niceness 616 00:34:37,850 --> 00:34:41,399 Speaker 2: is genuine or, and, you know, I guess with all 617 00:34:41,420 --> 00:34:44,839 Speaker 2: of this, we can imagine how easily these things can 618 00:34:44,860 --> 00:34:50,640 Speaker 2: also bleed over into maybe slightly toxic areas as well. Oh, totally. 619 00:34:50,660 --> 00:34:54,069 Speaker 3: Yeah. I think, I mean, there's a lot of toxicity 620 00:34:54,110 --> 00:34:57,049 Speaker 3: wrapped up in all this. Like, it's a thing I 621 00:34:57,090 --> 00:34:59,810 Speaker 3: think a lot of people would probably realize, like you, 622 00:35:00,489 --> 00:35:02,430 Speaker 3: that's why I was saying, you know, it's interesting that 623 00:35:02,910 --> 00:35:06,219 Speaker 3: this result is just what people would admit on a survey. 624 00:35:06,320 --> 00:35:08,920 Speaker 3: I mean, a lot of people might really deep down 625 00:35:09,020 --> 00:35:11,580 Speaker 3: kind of like to have a friend who would be 626 00:35:11,680 --> 00:35:14,740 Speaker 3: mean to their enemies, but they wouldn't say that out loud. 627 00:35:14,760 --> 00:35:17,460 Speaker 3: They'd be like, well, I shouldn't say that, but that 628 00:35:17,520 --> 00:35:18,560 Speaker 3: is kind of what I want. 629 00:35:18,980 --> 00:35:22,080 Speaker 2: Yeah, you might want it while also realizing that this 630 00:35:22,120 --> 00:35:25,360 Speaker 2: could cause a lot of problems. Again, especially if it 631 00:35:25,410 --> 00:35:28,090 Speaker 2: went beyond that person just is going to talk smack 632 00:35:28,110 --> 00:35:31,210 Speaker 2: with you about this enemy. But if they're going to 633 00:35:31,250 --> 00:35:36,460 Speaker 2: actively like, provokes that enemy, then maybe that's the whole 634 00:35:36,500 --> 00:35:41,200 Speaker 2: situation you really don't actually want in your life, but 635 00:35:41,260 --> 00:35:42,510 Speaker 2: on some level you want it. 636 00:35:43,860 --> 00:35:47,050 Speaker 3: Another variation that is not directly tested in the paper, 637 00:35:47,170 --> 00:35:51,950 Speaker 3: but which interests me, is about how this would affect 638 00:35:52,050 --> 00:35:56,810 Speaker 3: the way we view actions themselves. Like, Again, the paper 639 00:35:56,870 --> 00:36:02,700 Speaker 3: explores hypothetical behavior that is explicitly labeled as vicious or cruel. 640 00:36:03,200 --> 00:36:05,920 Speaker 3: But what I'm wondering is how would it affect our 641 00:36:06,020 --> 00:36:11,859 Speaker 3: judgments about whether actions are vicious or cruel? In other words, 642 00:36:11,940 --> 00:36:15,020 Speaker 3: I think if we witness somebody acting a certain way 643 00:36:15,100 --> 00:36:18,920 Speaker 3: toward a friend or a neutral stranger, you might look 644 00:36:18,960 --> 00:36:21,100 Speaker 3: at the behavior and say that is vicious. 645 00:36:21,200 --> 00:36:21,980 Speaker 2: But if you. 646 00:36:21,920 --> 00:36:26,090 Speaker 3: Saw the same person behaving the same way towards someone 647 00:36:26,150 --> 00:36:29,550 Speaker 3: you perceive as an enemy, you might not even perceive 648 00:36:29,610 --> 00:36:31,980 Speaker 3: the behavior as vicious to begin with. So you wouldn't 649 00:36:32,000 --> 00:36:33,680 Speaker 3: even get to the point of saying, like, I will 650 00:36:33,719 --> 00:36:36,920 Speaker 3: tolerate viciousness against my enemies. You might just say, like, 651 00:36:36,960 --> 00:36:40,460 Speaker 3: that's not vicious. You know, instead of looking like cruelty, 652 00:36:40,880 --> 00:36:43,060 Speaker 3: it would look like your enemy getting what they have 653 00:36:43,120 --> 00:36:43,839 Speaker 3: coming to them. 654 00:36:44,520 --> 00:36:46,600 Speaker 2: I have to admit, in all of this, I keep 655 00:36:47,760 --> 00:36:51,719 Speaker 2: picturing the vicious behavior as being like an offhand sick burn. 656 00:36:52,370 --> 00:36:56,330 Speaker 2: as opposed to like actively clawing somebody's face. So I 657 00:36:56,350 --> 00:36:58,239 Speaker 2: guess a lot of weight goes into how we're going 658 00:36:58,260 --> 00:36:59,780 Speaker 2: to think about vicious behavior. 659 00:37:00,239 --> 00:37:04,759 Speaker 3: Yeah, yeah, that's true. Obviously, if you got into the 660 00:37:04,800 --> 00:37:08,219 Speaker 3: details of specifying like acts of violence or stuff, I 661 00:37:08,239 --> 00:37:12,549 Speaker 3: think that would probably provoke different responses than what I 662 00:37:12,630 --> 00:37:15,370 Speaker 3: imagine most people are thinking about in the study, which 663 00:37:15,430 --> 00:37:19,819 Speaker 3: is probably, yeah, like, saying mean things about somebody or 664 00:37:19,860 --> 00:37:21,980 Speaker 3: maybe like little bits of social sabotage. 665 00:37:22,100 --> 00:37:25,299 Speaker 2: Yeah, it's got to be to some level socially acceptable. 666 00:37:26,160 --> 00:37:29,510 Speaker 2: If it's not socially acceptable, I feel like it's surely 667 00:37:29,950 --> 00:37:31,049 Speaker 2: crossing some line here. 668 00:37:31,510 --> 00:37:31,710 Speaker 1: Yeah. 669 00:37:32,530 --> 00:37:36,650 Speaker 3: So anyway, everybody listening right now, think about which of 670 00:37:36,690 --> 00:37:39,110 Speaker 3: your friends are the most vicious and do you value 671 00:37:39,150 --> 00:37:39,690 Speaker 3: this in them? 672 00:37:41,010 --> 00:37:44,580 Speaker 2: Yeah, or yeah, there's probably a lot to unpack there 673 00:37:44,640 --> 00:37:48,130 Speaker 2: because too, I often think about Friendships is being like orbits, 674 00:37:48,230 --> 00:37:50,150 Speaker 2: you know, and you have you have closer orbits and 675 00:37:50,190 --> 00:37:52,750 Speaker 2: you have you have orbits that are a bit farther 676 00:37:52,870 --> 00:37:55,570 Speaker 2: out and you need things to be in their right orbit. 677 00:37:56,210 --> 00:37:59,270 Speaker 2: It can be disastrous if the wrong cosmic body is 678 00:37:59,330 --> 00:38:02,739 Speaker 2: in the wrong orbit. And therefore, perhaps like a vicious 679 00:38:02,820 --> 00:38:05,259 Speaker 2: friend is somebody you want them. You want them, you know, 680 00:38:05,320 --> 00:38:09,680 Speaker 2: several astronomical units out. You want them to protect protect 681 00:38:09,719 --> 00:38:13,210 Speaker 2: you from incoming bits of shrapnel, you know. But you 682 00:38:13,230 --> 00:38:15,770 Speaker 2: don't want them like super close, right? And maybe if 683 00:38:15,810 --> 00:38:18,529 Speaker 2: you were in close proximity to them too much, then 684 00:38:18,590 --> 00:38:20,410 Speaker 2: it could maybe be a bit toxic. I don't know. 685 00:38:21,190 --> 00:38:24,469 Speaker 2: There's so many dynamics to potentially consider here. I would love, 686 00:38:24,510 --> 00:38:26,649 Speaker 2: I guess, some good field reports on this, provided there's 687 00:38:26,670 --> 00:38:29,029 Speaker 2: a kind of field reports we can actually share on 688 00:38:29,070 --> 00:38:29,390 Speaker 2: the show. 689 00:38:30,100 --> 00:38:33,600 Speaker 3: The vicious friend planetary body can, I would say, emit 690 00:38:33,660 --> 00:38:34,940 Speaker 3: a lot of radiation. 691 00:38:35,080 --> 00:38:35,319 Speaker 2: Yes. 692 00:38:35,560 --> 00:38:38,319 Speaker 3: So like being in their direct vicinity can have just 693 00:38:38,400 --> 00:38:39,460 Speaker 3: secondary effects. 694 00:38:39,760 --> 00:38:41,980 Speaker 2: Yeah, you don't want that in your Goldilocks zone for sure. 695 00:38:42,000 --> 00:38:42,460 Speaker 3: Yeah. 696 00:38:43,450 --> 00:38:45,830 Speaker 2: But then you wonder, too, does the vicious friend have 697 00:38:45,870 --> 00:38:48,630 Speaker 2: vicious friends? Does this just keep going? There's got to 698 00:38:48,650 --> 00:38:49,850 Speaker 2: be a limit, right? Yeah. 699 00:39:00,440 --> 00:39:02,259 Speaker 3: I guess that's it for all of the ones we're 700 00:39:02,280 --> 00:39:03,940 Speaker 3: going to do a deep dive on today. But I 701 00:39:04,239 --> 00:39:07,239 Speaker 3: briefly did want to flag also the physics prize this 702 00:39:07,300 --> 00:39:10,960 Speaker 3: year was the one about the splash-free urinal. So that 703 00:39:11,040 --> 00:39:19,200 Speaker 3: one went to Randy Hurd. And it was, quote, for 704 00:39:19,280 --> 00:39:23,219 Speaker 3: theoretical and experimental attempts to design a splash-free urinal. This 705 00:39:23,260 --> 00:39:27,170 Speaker 3: was research that was published in 2025. And I was 706 00:39:27,210 --> 00:39:31,460 Speaker 3: just shocked that, like, there's like, still research going on 707 00:39:31,500 --> 00:39:34,759 Speaker 3: about splash-free urinals. That's, like, not a solved problem. 708 00:39:34,780 --> 00:39:38,719 Speaker 2: Yeah, I guess so. I mean, you're still going to 709 00:39:38,739 --> 00:39:41,509 Speaker 2: get some urine on you sometimes. Well, that may be... 710 00:39:41,469 --> 00:39:44,129 Speaker 2: You just haven't worked that out as a civilization yet. 711 00:39:44,610 --> 00:39:48,700 Speaker 3: I'm just... shocked that that wouldn't be something that, you know, 712 00:39:48,739 --> 00:39:52,109 Speaker 3: where the optimal design was discovered like a hundred years ago, 713 00:39:52,120 --> 00:39:52,549 Speaker 3: you know? 714 00:39:52,570 --> 00:39:55,330 Speaker 2: Hmm. I guess they're just a number. I'm just guessing 715 00:39:55,390 --> 00:39:57,029 Speaker 2: here that they're just a number of factors in the 716 00:39:57,070 --> 00:40:01,950 Speaker 2: fluid dynamics of, of peeing onto a surface like this, uh, 717 00:40:02,010 --> 00:40:05,390 Speaker 2: with or without flowing water. And yeah, it's like, how 718 00:40:05,410 --> 00:40:06,549 Speaker 2: do you account for all of that? 719 00:40:07,130 --> 00:40:07,350 Speaker 1: Yeah. 720 00:40:08,270 --> 00:40:10,080 Speaker 3: Well, uh, hats off to him. 721 00:40:10,530 --> 00:40:10,750 Speaker 2: Yeah. 722 00:40:10,790 --> 00:40:10,930 Speaker 1: Yeah. 723 00:40:11,050 --> 00:40:12,930 Speaker 2: Yeah. Somebody, somebody has got to work on the hard stuff. 724 00:40:14,969 --> 00:40:17,430 Speaker 3: Okay, well, that's all I've got for this year. And 725 00:40:17,650 --> 00:40:19,129 Speaker 3: if you want to look up the other prize winners, 726 00:40:19,170 --> 00:40:23,130 Speaker 3: we didn't cover everything. You can, again, go to improbable.com, 727 00:40:23,190 --> 00:40:25,189 Speaker 3: and they list all of the winners. You can click 728 00:40:25,210 --> 00:40:28,130 Speaker 3: through to them, read the papers, read the coverage, and 729 00:40:28,170 --> 00:40:28,650 Speaker 3: check it out. 730 00:40:29,030 --> 00:40:32,049 Speaker 2: Yeah, as is always the case, some are funnier on 731 00:40:32,570 --> 00:40:35,969 Speaker 2: the surface level. And a lot of times that is 732 00:40:37,030 --> 00:40:39,779 Speaker 2: what it's about. There's just some sort of an instinct 733 00:40:39,820 --> 00:40:43,819 Speaker 2: to laugh based on what is being studied or how 734 00:40:43,860 --> 00:40:46,270 Speaker 2: it is being studied. But then, you know, I think 735 00:40:46,430 --> 00:40:48,170 Speaker 2: generally in the ones that we tend to dive into, 736 00:40:48,510 --> 00:40:52,390 Speaker 2: there's something deeper that's either, like, there's deeper comedy there, 737 00:40:52,770 --> 00:40:54,989 Speaker 2: or there's something, you know, there's some serious science going 738 00:40:55,050 --> 00:40:57,270 Speaker 2: on there that is, you know, deeply contemplated. 739 00:40:57,830 --> 00:41:00,910 Speaker 3: Yeah, it's not always, you know, the ones that are 740 00:41:00,930 --> 00:41:02,850 Speaker 3: the funniest are not always the ones that are the 741 00:41:02,890 --> 00:41:04,750 Speaker 3: most interesting to go deep on. 742 00:41:04,830 --> 00:41:05,270 Speaker 2: Yeah. 743 00:41:06,030 --> 00:41:08,770 Speaker 3: Maybe I'd give my personal prize this year for the 744 00:41:08,890 --> 00:41:12,710 Speaker 3: one that's, like, the greatest peak of both actually very 745 00:41:12,810 --> 00:41:16,230 Speaker 3: funny and Interesting to get into the details of. I 746 00:41:16,270 --> 00:41:18,750 Speaker 3: thought that peak may have been the necroprinting one. Big 747 00:41:18,810 --> 00:41:19,430 Speaker 3: thumbs up here. 748 00:41:19,469 --> 00:41:22,720 Speaker 2: Yeah, that one was good. I really like the underpants 749 00:41:22,780 --> 00:41:25,360 Speaker 2: as well, though. And yeah, vicious friends blowing your nose. 750 00:41:26,260 --> 00:41:28,839 Speaker 2: It's a good crop. Good crop this year. All right, 751 00:41:28,860 --> 00:41:29,980 Speaker 2: we're going to go ahead and close it out. But 752 00:41:30,000 --> 00:41:32,080 Speaker 2: we'll just remind everyone that Stuff to Blow Your Mind 753 00:41:32,140 --> 00:41:34,859 Speaker 2: is primarily a science and culture podcast with core episodes 754 00:41:35,010 --> 00:41:38,629 Speaker 2: on Tuesdays and Thursdays and Weird House Cinema on Fridays. 755 00:41:39,670 --> 00:41:43,820 Speaker 2: let's see, wherever you're listening to this podcast, rate, review, subscribe. 756 00:41:43,860 --> 00:41:46,300 Speaker 2: That really helps us out. If you're watching as well 757 00:41:46,440 --> 00:41:48,700 Speaker 2: on Netflix, that's where you get to watch the show 758 00:41:48,719 --> 00:41:51,220 Speaker 2: in addition to listen to it, just make sure that 759 00:41:51,239 --> 00:41:53,430 Speaker 2: you're giving us a couple of thumbs up and asking 760 00:41:53,469 --> 00:41:55,110 Speaker 2: to be reminded about new episodes. 761 00:41:55,870 --> 00:41:58,850 Speaker 3: Huge thanks, as always, to our excellent audio producer, J.J. 762 00:41:58,890 --> 00:41:59,310 Speaker 2: Posway. 763 00:41:59,770 --> 00:42:01,190 Speaker 3: If you would like to get in touch with us 764 00:42:01,230 --> 00:42:03,550 Speaker 3: with feedback on this episode or any other, to suggest 765 00:42:03,610 --> 00:42:05,549 Speaker 3: a topic for the future, or just to say hello, 766 00:42:05,610 --> 00:42:09,259 Speaker 3: you can email us at contact at stufftoblowyourmind.com. 767 00:42:17,540 --> 00:42:20,000 Speaker 1: Stuff to Blow Your Mind is a production of iHeartRadio. 768 00:42:20,340 --> 00:42:23,669 Speaker 1: For more podcasts from iHeartRadio, visit the iHeartRadio app. Apple 769 00:42:23,710 --> 00:42:26,050 Speaker 1: Podcasts are wherever you listen to your favorite shows. 770 00:42:40,469 --> 00:42:40,840 Speaker 2: Thank you.