1 00:00:03,080 --> 00:00:06,000 Speaker 1: Welcome to stuff to Blow your Mind from how Stuff 2 00:00:06,000 --> 00:00:14,160 Speaker 1: Works dot com. Hey you welcome stuff to bow your mind. 3 00:00:14,160 --> 00:00:16,640 Speaker 1: My name is Robert Lamb and I'm Julie Degrass. Julie 4 00:00:16,640 --> 00:00:19,000 Speaker 1: a smiley person. Would you would you say that you 5 00:00:19,040 --> 00:00:22,680 Speaker 1: are smile prone? M. I don't think of myself that's 6 00:00:22,680 --> 00:00:24,160 Speaker 1: just a smily person. In fact, you and I were 7 00:00:24,200 --> 00:00:27,760 Speaker 1: talking about smiling a little earlier, and I typically have 8 00:00:27,840 --> 00:00:30,160 Speaker 1: sort of a frowny face even though I'm not frowning. 9 00:00:30,160 --> 00:00:34,479 Speaker 1: You just have turned down lips. So I guess others 10 00:00:34,479 --> 00:00:39,280 Speaker 1: think of me as a frowny face. What about you? Um, 11 00:00:39,280 --> 00:00:42,600 Speaker 1: I'm guess I'm not opposed to smiling. I'm not a 12 00:00:43,000 --> 00:00:46,440 Speaker 1: smile I do smile. UM, but I feel like my 13 00:00:46,520 --> 00:00:49,840 Speaker 1: relationship with smiles is kind of weird, Like, on one, 14 00:00:49,960 --> 00:00:52,720 Speaker 1: on one hand, there's there's always this I feel like 15 00:00:53,040 --> 00:00:57,880 Speaker 1: there's this temptation in especially the United States, UH, bombarded 16 00:00:57,960 --> 00:01:02,200 Speaker 1: as we are with perfect smiles in our TV actors 17 00:01:02,240 --> 00:01:04,280 Speaker 1: and especially in our big Hollywood actors and in all 18 00:01:04,280 --> 00:01:07,160 Speaker 1: of our advertisements, that you tend to be a little 19 00:01:07,200 --> 00:01:10,200 Speaker 1: more self conscious about your teeth. Uh if you don't 20 00:01:10,200 --> 00:01:13,000 Speaker 1: have that perfect grin which can can often make you 21 00:01:13,040 --> 00:01:15,040 Speaker 1: a little more tight lipped in your smiling and a 22 00:01:15,080 --> 00:01:18,280 Speaker 1: little more reserved in your flashing of your smile, which 23 00:01:18,360 --> 00:01:20,760 Speaker 1: is something to take take with us. Take that idea 24 00:01:20,840 --> 00:01:23,480 Speaker 1: with us as we we go into this this topic today, 25 00:01:23,480 --> 00:01:27,120 Speaker 1: because I was recently reading in an interview excerpt with 26 00:01:27,959 --> 00:01:30,720 Speaker 1: Ricky Gervei and he was talking, he was getting into 27 00:01:30,720 --> 00:01:32,560 Speaker 1: the whole teeth and of course it's the old trope 28 00:01:32,600 --> 00:01:35,760 Speaker 1: of uh, you know, British teeth versus American teeth, and 29 00:01:35,760 --> 00:01:38,880 Speaker 1: and and what he was finding and what I've found 30 00:01:38,880 --> 00:01:41,679 Speaker 1: before too, is that in the US again, there's that 31 00:01:41,840 --> 00:01:45,360 Speaker 1: huge emphasis on the perfect smile, and in Brittain things 32 00:01:45,360 --> 00:01:47,320 Speaker 1: are a little more relaxed and normal. You can watch 33 00:01:47,319 --> 00:01:50,000 Speaker 1: a TV show there and you'll see people with teeth 34 00:01:50,000 --> 00:01:53,480 Speaker 1: that are refreshingly normal teeth. You'll see like a gap 35 00:01:53,520 --> 00:01:56,280 Speaker 1: in somebody's teeth, and you'll you'll it'll at first it's 36 00:01:56,400 --> 00:01:58,960 Speaker 1: an American view where you're like, oh, well that's interesting. 37 00:01:58,960 --> 00:02:01,400 Speaker 1: Then you feel a little more uh related to the 38 00:02:01,480 --> 00:02:05,160 Speaker 1: character because this person seems a little more real. Um. 39 00:02:05,200 --> 00:02:07,200 Speaker 1: So take all of that with you into into this 40 00:02:07,280 --> 00:02:10,400 Speaker 1: topic as we discuss smiles. The science of smiles, What 41 00:02:10,440 --> 00:02:13,000 Speaker 1: smiles are really doing, because, as is often pointed out, 42 00:02:13,000 --> 00:02:15,359 Speaker 1: a smile is not just this thing floating in the air. 43 00:02:15,440 --> 00:02:18,800 Speaker 1: It's not like the cheshire cat. It's something that's attached 44 00:02:18,840 --> 00:02:20,920 Speaker 1: to our body. It's it's right up here on our face. 45 00:02:20,919 --> 00:02:25,320 Speaker 1: And our faith is the communications array for the organism. Yeah, 46 00:02:25,360 --> 00:02:26,920 Speaker 1: and the smile. There's so much more to the smile 47 00:02:26,960 --> 00:02:29,560 Speaker 1: than you would think. So we're going to dive into that. Uh. 48 00:02:29,600 --> 00:02:32,119 Speaker 1: This is a statistic that is thrown around a lot 49 00:02:32,200 --> 00:02:35,720 Speaker 1: that kids smile four hundred times a day and US 50 00:02:35,760 --> 00:02:40,560 Speaker 1: adults on average smile only twenty times a day. Okay, 51 00:02:40,560 --> 00:02:42,560 Speaker 1: well that makes sense because I feel like with children, 52 00:02:42,600 --> 00:02:45,240 Speaker 1: especially the very young children, it's all just a pendulum 53 00:02:45,240 --> 00:02:49,360 Speaker 1: between you know, absolute care and unhappiness and just just 54 00:02:49,440 --> 00:02:51,760 Speaker 1: and then just unbridled happiness on the other end. So 55 00:02:52,360 --> 00:02:54,120 Speaker 1: you know, they're swinging into the pendle, and they're also 56 00:02:54,120 --> 00:02:55,760 Speaker 1: crying more d in the course of the day. They're 57 00:02:55,760 --> 00:02:58,160 Speaker 1: also feeling heartbroken more during the course of the day. 58 00:02:58,160 --> 00:03:01,400 Speaker 1: And humans have a lot more um humans adults. I 59 00:03:01,520 --> 00:03:06,400 Speaker 1: keep making that mistake in conversations. Uh, Us, adult humans 60 00:03:06,560 --> 00:03:08,600 Speaker 1: have a lot more nuance in the way that we 61 00:03:08,639 --> 00:03:11,280 Speaker 1: react emotionally. To the world. Well, a lot of it 62 00:03:11,320 --> 00:03:15,800 Speaker 1: too is mimicking your environment and learning these social cues. 63 00:03:15,840 --> 00:03:17,880 Speaker 1: And we'll talk more about this in terms of mirror 64 00:03:17,880 --> 00:03:19,840 Speaker 1: neurons in a second, but I did want to point 65 00:03:19,880 --> 00:03:24,640 Speaker 1: out that babies actually smile in the womb, and previous 66 00:03:24,720 --> 00:03:27,720 Speaker 1: to four D scanners, which produced three D images that 67 00:03:27,760 --> 00:03:30,480 Speaker 1: move in real time, it was thought that babies smiled 68 00:03:30,680 --> 00:03:33,880 Speaker 1: only after learning the behavior about six weeks after they 69 00:03:33,880 --> 00:03:36,560 Speaker 1: were born. But it was Dr Stewart Campbell who was 70 00:03:36,600 --> 00:03:39,720 Speaker 1: the first to capture these images of baby smiling in 71 00:03:39,760 --> 00:03:43,200 Speaker 1: the womb, and his idea for this lag of after 72 00:03:43,400 --> 00:03:46,600 Speaker 1: they're born, this six week lag of smiling, is that 73 00:03:47,280 --> 00:03:51,840 Speaker 1: in the womb, it's safe, it's warm, so you're able 74 00:03:51,880 --> 00:03:55,840 Speaker 1: to leisurely float about without a worry and perhaps smile. Yeah, 75 00:03:55,840 --> 00:03:58,000 Speaker 1: of course you'd smile on that right, right, Sure, But 76 00:03:58,000 --> 00:04:00,600 Speaker 1: he's saying that once you're born, you know, all of 77 00:04:00,680 --> 00:04:03,120 Speaker 1: a sudden, you're just bombarded with all the stimuli, and 78 00:04:03,200 --> 00:04:05,760 Speaker 1: so that's a smile and relaxation is sort of the 79 00:04:05,880 --> 00:04:08,880 Speaker 1: furthest things from a child or baby's mind at that point. 80 00:04:09,200 --> 00:04:11,720 Speaker 1: And that made me think about when we've talked about 81 00:04:12,880 --> 00:04:17,200 Speaker 1: children's brains in particular babies being soaked in neurotransmitters which 82 00:04:17,240 --> 00:04:19,560 Speaker 1: are faring around all the data that they're taking in. 83 00:04:19,760 --> 00:04:21,760 Speaker 1: And that makes sense to me, you know, because that 84 00:04:21,880 --> 00:04:24,840 Speaker 1: first six weeks it's just trying to make sense of 85 00:04:24,880 --> 00:04:28,159 Speaker 1: all these different sensations. So smile is going to have 86 00:04:28,200 --> 00:04:31,000 Speaker 1: to wait, you know. On the subject of smiles, also 87 00:04:31,000 --> 00:04:34,200 Speaker 1: found some stats about the world smiles UH, and that 88 00:04:34,800 --> 00:04:38,680 Speaker 1: this particular starters looking at found that countries in East 89 00:04:38,760 --> 00:04:43,440 Speaker 1: Asia Japan and Southeast Asia Thailand, of the Philippines, this 90 00:04:43,480 --> 00:04:45,560 Speaker 1: is where you would find the most smiles per capita 91 00:04:46,240 --> 00:04:48,600 Speaker 1: um and then UH, where as if you looked at 92 00:04:48,640 --> 00:04:52,560 Speaker 1: Northern European countries, Scandinavian countries, in the Eastern Bloc countries, 93 00:04:53,040 --> 00:04:55,880 Speaker 1: you would see considerably a less, not like the least 94 00:04:55,880 --> 00:04:59,080 Speaker 1: smiles per capita in those areas. That's interesting because I 95 00:04:59,160 --> 00:05:00,920 Speaker 1: was recently at a with a party for a kid 96 00:05:00,960 --> 00:05:05,160 Speaker 1: and there was a large contingent of German parents there, 97 00:05:05,720 --> 00:05:08,920 Speaker 1: and I noticed that in the conversations that I had 98 00:05:08,960 --> 00:05:11,479 Speaker 1: with the parents that um, you know, you begin to 99 00:05:11,520 --> 00:05:14,599 Speaker 1: notice your own behavior in this group situation, that I 100 00:05:14,640 --> 00:05:17,800 Speaker 1: was doing the smiling head nodding thing a lot more 101 00:05:17,839 --> 00:05:20,560 Speaker 1: than the German parents were, because I think that for 102 00:05:20,600 --> 00:05:24,760 Speaker 1: me socialized in America, that's a cue for I'm listening 103 00:05:24,800 --> 00:05:28,960 Speaker 1: to you, I'm agreeing, I'm encouraging you. Yes, yeah, that 104 00:05:29,040 --> 00:05:31,640 Speaker 1: little voice that comes on your head, it says all right, 105 00:05:31,680 --> 00:05:34,080 Speaker 1: grinn and not grinn and not. They just convey that 106 00:05:34,120 --> 00:05:36,000 Speaker 1: you you were listening and you were in some on 107 00:05:36,040 --> 00:05:37,880 Speaker 1: some level agreeing with what they're saying, even if you 108 00:05:38,040 --> 00:05:40,680 Speaker 1: are just completely tuning up. Okay, so when I'm grinning 109 00:05:40,680 --> 00:05:43,320 Speaker 1: and nodding, let's take a closer look at what is 110 00:05:43,360 --> 00:05:45,560 Speaker 1: actually going on. Is it sort of like a smile 111 00:05:45,640 --> 00:05:47,880 Speaker 1: one oh one when it comes to our brains and 112 00:05:47,880 --> 00:05:52,160 Speaker 1: our muscles. So if you see something that pleases you, 113 00:05:52,160 --> 00:05:54,560 Speaker 1: you have these neuronal signals that travel from the cortex 114 00:05:54,600 --> 00:05:56,640 Speaker 1: of your brain to the brain stem. Now, the brain 115 00:05:56,680 --> 00:05:58,520 Speaker 1: stom is the most primitive part of our brain. Right 116 00:05:58,960 --> 00:06:02,200 Speaker 1: from there, the cranial muscles carry the signal further towards 117 00:06:02,240 --> 00:06:06,159 Speaker 1: the smiling muscles in your face, in particular something called 118 00:06:06,160 --> 00:06:09,919 Speaker 1: the zygo madocus major muscles, and that draws up the 119 00:06:09,960 --> 00:06:13,599 Speaker 1: corners of your mouth. So once they contract, a positive 120 00:06:13,600 --> 00:06:17,120 Speaker 1: feedback loop goes back to the brain and reinforces this 121 00:06:17,160 --> 00:06:20,360 Speaker 1: feeling of joy or pleasure or whatever it is that 122 00:06:20,440 --> 00:06:24,000 Speaker 1: has made you smile. Now we have a lot more 123 00:06:24,120 --> 00:06:27,839 Speaker 1: insight into a true blue smile. This is the crinkling 124 00:06:27,880 --> 00:06:31,960 Speaker 1: of the eyes kind of smile. Because of someone named 125 00:06:32,520 --> 00:06:36,040 Speaker 1: m A. Bungamin Douchen is called the douch smile. I'm 126 00:06:36,040 --> 00:06:38,280 Speaker 1: glad you tackled Sin's name because I was puzzling over 127 00:06:38,320 --> 00:06:40,800 Speaker 1: that one. I slaughtered his his first name, for sure, 128 00:06:40,839 --> 00:06:43,320 Speaker 1: but Dushan, I think, you know, not too bad. But 129 00:06:43,400 --> 00:06:46,799 Speaker 1: he did experiments where he would actually zap single muscles 130 00:06:46,839 --> 00:06:50,279 Speaker 1: all over the face with electrodes to try to figure 131 00:06:50,320 --> 00:06:54,320 Speaker 1: out all these different expressions and emotions that we show. 132 00:06:54,880 --> 00:06:57,520 Speaker 1: And that's how he came to figure out that there's 133 00:06:57,560 --> 00:07:00,680 Speaker 1: a true blue smile that you see. Yeah, one of 134 00:07:00,720 --> 00:07:04,760 Speaker 1: the sixty different expressions that he u electrocuted into place 135 00:07:04,760 --> 00:07:07,200 Speaker 1: and then photographed. And actually, if you go to stuff 136 00:07:07,200 --> 00:07:09,400 Speaker 1: to Blow your Mind dot com, uh, you will see 137 00:07:09,440 --> 00:07:12,120 Speaker 1: that we have uploaded a gallery if some of these images, 138 00:07:12,120 --> 00:07:13,760 Speaker 1: not all sixty because I think that would just be 139 00:07:13,840 --> 00:07:15,600 Speaker 1: a bit much, but some of these images so you 140 00:07:15,640 --> 00:07:17,680 Speaker 1: can see what we're talking about, because they're brilliant. There's 141 00:07:17,760 --> 00:07:20,560 Speaker 1: this one older gentleman that is the test subject in 142 00:07:20,640 --> 00:07:26,320 Speaker 1: most of these photos, and it's uh at once hilarious 143 00:07:26,400 --> 00:07:31,160 Speaker 1: and horrifying to see his face contorted the electricity into 144 00:07:31,160 --> 00:07:34,440 Speaker 1: these different emotional states because his hair is all kind 145 00:07:34,440 --> 00:07:37,080 Speaker 1: of mussed up anyway, so you know, he's got this 146 00:07:37,400 --> 00:07:40,000 Speaker 1: terrifying smile spreading over his face, and his hair just 147 00:07:40,120 --> 00:07:42,960 Speaker 1: kind of looks like it's a bit on end uh 148 00:07:43,000 --> 00:07:45,960 Speaker 1: and then you you know, you see the electrodes. Uh. So, yes, 149 00:07:46,080 --> 00:07:48,440 Speaker 1: it's very interesting stuff. But that's how to Shan figured 150 00:07:48,480 --> 00:07:51,920 Speaker 1: out what this smile, this true blue smile was, because 151 00:07:52,200 --> 00:07:56,440 Speaker 1: again it's the zygomatic major muscle that's turning up the lips. 152 00:07:56,760 --> 00:08:00,520 Speaker 1: But also you have this orbicularious oculi muscle and that 153 00:08:00,640 --> 00:08:04,200 Speaker 1: raises the cheeks informs those cross feet around the eyes. 154 00:08:04,280 --> 00:08:06,200 Speaker 1: I think everybody kind of knows what that looks like, 155 00:08:06,280 --> 00:08:07,760 Speaker 1: right you have an idea in your head right now. 156 00:08:07,760 --> 00:08:10,200 Speaker 1: I always think about my grandmother, you know, and her 157 00:08:10,400 --> 00:08:15,040 Speaker 1: very sweet and joyous smiles and what that looks like. Yeah, 158 00:08:15,080 --> 00:08:18,280 Speaker 1: and then the the eventual smile lines that you hear 159 00:08:18,320 --> 00:08:20,520 Speaker 1: about in people's faces. Yeah, they say, oh, don't don't 160 00:08:20,600 --> 00:08:22,360 Speaker 1: laugh too much, because then you'll have smile lines when 161 00:08:22,360 --> 00:08:24,480 Speaker 1: you get older. So there's this idea that you see 162 00:08:24,520 --> 00:08:27,800 Speaker 1: something it pleases you. But there's also the idea that 163 00:08:28,000 --> 00:08:30,160 Speaker 1: you're talking to someone, they're smiling at you, and what 164 00:08:30,200 --> 00:08:33,680 Speaker 1: do you do? You smile back? Yeah, you know, I 165 00:08:33,679 --> 00:08:35,839 Speaker 1: feel like I encountered that version of smiling more than 166 00:08:35,960 --> 00:08:40,280 Speaker 1: like spontaneous by myself smiling. Because if I'm by myself 167 00:08:40,280 --> 00:08:43,000 Speaker 1: and I'm reading something that I'm enjoying, I mean, occasionally 168 00:08:43,040 --> 00:08:45,640 Speaker 1: i may laugh out loud, but for the most part, 169 00:08:45,760 --> 00:08:49,199 Speaker 1: I'm I'm probably not smiling. I'm thinking maybe I should, 170 00:08:49,280 --> 00:08:51,600 Speaker 1: I should experiment on myself with a camera or something. 171 00:08:51,640 --> 00:08:54,200 Speaker 1: But and smiling really creepily you're right now, just to 172 00:08:54,200 --> 00:08:56,160 Speaker 1: see you feel smile, that's kind of creepy smile. That 173 00:08:56,160 --> 00:08:59,760 Speaker 1: seems like now it's a creepy smile. Well, the thing, 174 00:09:00,080 --> 00:09:02,320 Speaker 1: this is what I think is interesting about when you 175 00:09:02,400 --> 00:09:04,800 Speaker 1: smile at a person who's smiling back at you. It's 176 00:09:04,840 --> 00:09:07,760 Speaker 1: because those neurons that fire both when we observe and 177 00:09:07,800 --> 00:09:11,120 Speaker 1: when we take parton in action, those are called mirror neurons. 178 00:09:11,160 --> 00:09:14,800 Speaker 1: So when we smile, mirror neurons simulate our own smiling. 179 00:09:14,880 --> 00:09:17,839 Speaker 1: So on one level, you can't not smile. Yeah, it's 180 00:09:17,920 --> 00:09:21,959 Speaker 1: it's an innate in state to imitate each other. We 181 00:09:22,120 --> 00:09:23,920 Speaker 1: see that smile, and then the smile forms in our 182 00:09:23,960 --> 00:09:27,120 Speaker 1: own face. Uh. It's uh, you know, ties into a 183 00:09:27,120 --> 00:09:29,839 Speaker 1: synchronicity of our body, our actions, even when we speak 184 00:09:29,880 --> 00:09:32,840 Speaker 1: to each other. Um, you know, like the whole the 185 00:09:32,880 --> 00:09:35,000 Speaker 1: old idea that you know you're you're someone who's grown 186 00:09:35,080 --> 00:09:36,960 Speaker 1: up in the South and you don't really talk with 187 00:09:37,000 --> 00:09:40,160 Speaker 1: the Southern accident until you're pulled over by a Southern cop, 188 00:09:40,559 --> 00:09:42,560 Speaker 1: and then your boice becomes a little Suddenly there are 189 00:09:42,559 --> 00:09:45,560 Speaker 1: all these Southern inflections that you thought you had abandoned 190 00:09:45,640 --> 00:09:49,360 Speaker 1: or outgrown. Um. I find myself doing that a lot. 191 00:09:49,440 --> 00:09:52,200 Speaker 1: Not not being pulled over by Southern cops all the time, 192 00:09:52,200 --> 00:09:54,400 Speaker 1: but I'll be I'll be talking to somebody and I'll 193 00:09:54,400 --> 00:09:57,720 Speaker 1: fall into some of their speech patterns, and and then 194 00:09:57,760 --> 00:09:59,880 Speaker 1: I'll start freaking out, thinking, oh my goodness, they think 195 00:10:00,080 --> 00:10:03,280 Speaker 1: some sort of a complete nut who's only able to 196 00:10:03,320 --> 00:10:07,360 Speaker 1: communicate with people by mimicking the person he's communicating with. Well, 197 00:10:07,400 --> 00:10:09,920 Speaker 1: I think it's just showing that you're getting the person 198 00:10:09,960 --> 00:10:11,720 Speaker 1: you're trying to connect with them. Yeah, I mean, that's 199 00:10:11,760 --> 00:10:14,840 Speaker 1: that's what the research here shows is that I'm not crazy. 200 00:10:15,559 --> 00:10:18,439 Speaker 1: It shows that this is part of our normal interactions 201 00:10:18,480 --> 00:10:21,840 Speaker 1: with people, that when we engage with someone in conversation, 202 00:10:22,360 --> 00:10:23,960 Speaker 1: we make eye contact and we have to go and 203 00:10:24,000 --> 00:10:26,840 Speaker 1: sync with each other. It's kind of a almost kind 204 00:10:26,880 --> 00:10:29,679 Speaker 1: of a Star Trek mind meld that's happening, except in 205 00:10:29,960 --> 00:10:33,360 Speaker 1: a very real sense. That's that's more amazing than any fantasy. Well, 206 00:10:33,360 --> 00:10:35,880 Speaker 1: I think it points back to you, this exquisite external 207 00:10:35,920 --> 00:10:40,319 Speaker 1: stimuli machine that we have within us. And Charles Darwin 208 00:10:40,559 --> 00:10:44,200 Speaker 1: he actually said, you know, I mean, besides you know, 209 00:10:44,360 --> 00:10:47,079 Speaker 1: being known for evolution in biology, he was actually one 210 00:10:47,120 --> 00:10:51,640 Speaker 1: of the early experimental psychologists. And he thought, you know, 211 00:10:51,760 --> 00:10:54,680 Speaker 1: maybe these facial expressions don't come from within. Maybe they 212 00:10:54,720 --> 00:10:57,480 Speaker 1: are external to us. So it's not just us broadcasting 213 00:10:57,480 --> 00:11:01,480 Speaker 1: our mental state of mind. And he thought, maybe these 214 00:11:01,480 --> 00:11:04,720 Speaker 1: expressions can determine your mental state. So this is something 215 00:11:04,760 --> 00:11:09,360 Speaker 1: we now know as facial feedback hypothesis. And he wrote 216 00:11:09,480 --> 00:11:11,800 Speaker 1: the nineteen or excuse me, the eighteen seventy two book 217 00:11:11,840 --> 00:11:15,400 Speaker 1: The Expression of Emotions and Man and Animals, which came 218 00:11:15,440 --> 00:11:19,600 Speaker 1: to that conclusion that the universality of facial expressions owed 219 00:11:19,760 --> 00:11:23,760 Speaker 1: to the evolutionary origin of it. So this all turns 220 00:11:23,800 --> 00:11:26,320 Speaker 1: out to be pretty spot on, and there are a 221 00:11:26,320 --> 00:11:30,160 Speaker 1: lot of studies that support that. And one of probably 222 00:11:30,200 --> 00:11:33,640 Speaker 1: the most well known studies, there's several variations on this, 223 00:11:34,440 --> 00:11:39,040 Speaker 1: is a study of pencils stuck in the mouth, in 224 00:11:39,080 --> 00:11:43,200 Speaker 1: which the person has to then evaluate fake smiles versus 225 00:11:43,480 --> 00:11:47,559 Speaker 1: real smiles. Yes, and I challenge anyone who's listening and 226 00:11:47,600 --> 00:11:51,040 Speaker 1: not driving a car or doing anything remotely dangerous, uh, 227 00:11:51,280 --> 00:11:54,960 Speaker 1: that has a pencil around a clean pencil. Uh. You know, 228 00:11:55,160 --> 00:11:57,040 Speaker 1: if that pencil has germs on it, that's your your 229 00:11:57,080 --> 00:11:59,280 Speaker 1: own business. But if you put that pencil and hold 230 00:11:59,320 --> 00:12:02,280 Speaker 1: it between your teeth, try to smile, and you will 231 00:12:02,280 --> 00:12:06,920 Speaker 1: find that you're smiling abilities are somewhat hindered actually too. 232 00:12:06,960 --> 00:12:10,520 Speaker 1: And if you take that that pencil and you put 233 00:12:10,600 --> 00:12:14,760 Speaker 1: it uh in a vertical position so that it's just 234 00:12:14,920 --> 00:12:19,040 Speaker 1: under your lip, that will actually form a frown, which 235 00:12:19,440 --> 00:12:23,199 Speaker 1: you know, again that's a different pencil studying. Many variations 236 00:12:23,240 --> 00:12:26,280 Speaker 1: on this, but the one I'm thinking about was conducted 237 00:12:26,360 --> 00:12:30,800 Speaker 1: by social psychologist Pold Nightenthal and it was a mimicking study. Again, 238 00:12:30,840 --> 00:12:32,839 Speaker 1: it was this idea that Darwin was saying, Hey, it's 239 00:12:32,880 --> 00:12:36,360 Speaker 1: not necessarily internal. It can come externally. And so she 240 00:12:36,600 --> 00:12:38,719 Speaker 1: had one group of participants asked to look at these 241 00:12:38,720 --> 00:12:41,600 Speaker 1: photos of people smiling and determine whether or not it 242 00:12:41,679 --> 00:12:44,000 Speaker 1: was real or fake and hold that pencil in their mouth, 243 00:12:44,080 --> 00:12:47,240 Speaker 1: and then the other group was asked to identify real 244 00:12:47,280 --> 00:12:48,880 Speaker 1: and fake smiles, but they didn't have the pencil in 245 00:12:48,880 --> 00:12:50,599 Speaker 1: their mouth. Well, okay, of course, it turned out that 246 00:12:50,600 --> 00:12:53,199 Speaker 1: the people who had the pencil in their mouth had 247 00:12:53,240 --> 00:12:57,760 Speaker 1: a harder time identifying the true blue smiles because that 248 00:12:57,800 --> 00:13:00,760 Speaker 1: whole mechanism of their rare neurons and their ability to 249 00:13:01,679 --> 00:13:05,839 Speaker 1: mimic that smile was interrupted. So the ability to mimic 250 00:13:05,880 --> 00:13:09,240 Speaker 1: the smile influences our power to understand them and our 251 00:13:09,280 --> 00:13:12,320 Speaker 1: power to feel that emotion. So they didn't get the 252 00:13:12,360 --> 00:13:16,199 Speaker 1: emotional lift that their counterparts, who were not hindered and 253 00:13:16,400 --> 00:13:19,000 Speaker 1: could identify a real smile got when they looked at 254 00:13:19,000 --> 00:13:22,760 Speaker 1: that true blue smile. It's another uh, all this information 255 00:13:22,880 --> 00:13:26,040 Speaker 1: is just another great argument for that mind body connection 256 00:13:26,280 --> 00:13:28,040 Speaker 1: that we've talked about again again. They had the idea 257 00:13:28,120 --> 00:13:30,959 Speaker 1: that we're not this brain that's sealed up in this 258 00:13:31,040 --> 00:13:33,679 Speaker 1: body suit. We are and we're not this rider on 259 00:13:33,760 --> 00:13:36,160 Speaker 1: this horse where a centaur where this uh, this can 260 00:13:36,240 --> 00:13:39,440 Speaker 1: joint being of brain and body and uh and to 261 00:13:39,520 --> 00:13:41,480 Speaker 1: the you know the quote that I mentioned earlier, which 262 00:13:41,480 --> 00:13:44,440 Speaker 1: actually came from Paula Needenthal, were not these uh these 263 00:13:44,480 --> 00:13:47,200 Speaker 1: magic chess our cat grins who are just floating in 264 00:13:47,200 --> 00:13:50,080 Speaker 1: the middle of space. That that grin is attached to 265 00:13:50,120 --> 00:13:51,920 Speaker 1: our body. That's a part of our body, and it's 266 00:13:51,960 --> 00:13:54,720 Speaker 1: it's part of this facial communication system that we have. Yeah, 267 00:13:54,720 --> 00:13:57,000 Speaker 1: it's telling your brain something about the world and how 268 00:13:57,040 --> 00:13:59,319 Speaker 1: you should feel. All right, let's take a quick break 269 00:13:59,360 --> 00:14:02,840 Speaker 1: and when we get back, when you're talking about smiles, happiness, 270 00:14:02,880 --> 00:14:15,120 Speaker 1: life expectancy, and chopsticks. All right, we are back. Does 271 00:14:15,360 --> 00:14:18,880 Speaker 1: flashing a grin make you happier? It's the question, and 272 00:14:19,680 --> 00:14:22,400 Speaker 1: could you live longer? Yes, because that's the big question 273 00:14:22,480 --> 00:14:25,320 Speaker 1: that sort of arises out of what we've discussed so far. Um, 274 00:14:25,320 --> 00:14:28,200 Speaker 1: we've talked about the way that it is the smiles 275 00:14:28,240 --> 00:14:30,320 Speaker 1: are as part of our communications array. It's a part 276 00:14:30,320 --> 00:14:34,240 Speaker 1: of our means of communing with other individuals who were 277 00:14:34,240 --> 00:14:38,120 Speaker 1: talking to about sharing things that are smile worthy. So 278 00:14:38,120 --> 00:14:40,800 Speaker 1: to what extent does it have a positive impact on 279 00:14:41,040 --> 00:14:44,960 Speaker 1: longevity and just sort of mental health? In general, especially 280 00:14:45,000 --> 00:14:47,920 Speaker 1: when you consider that smiling um in studies has shown 281 00:14:47,920 --> 00:14:51,320 Speaker 1: to reduce courses all levels of stress hormone levels and 282 00:14:51,560 --> 00:14:56,560 Speaker 1: increase endorphins that feel good hormone HW. Can you study 283 00:14:56,600 --> 00:14:59,000 Speaker 1: this right? Well? One way, of course is to look 284 00:14:59,040 --> 00:15:02,960 Speaker 1: at older pick ars of somebody, particularly pictures in say 285 00:15:03,000 --> 00:15:06,520 Speaker 1: a yearbook or baseball card photos. Both of these factor 286 00:15:06,560 --> 00:15:09,000 Speaker 1: into a couple of different studies that we're about to discuss. 287 00:15:09,240 --> 00:15:11,360 Speaker 1: As far as the yearbook goes, researchers at De Paul 288 00:15:11,480 --> 00:15:15,040 Speaker 1: University in Greencastle, Indiana analyzed the college yearbook photos of 289 00:15:15,080 --> 00:15:17,840 Speaker 1: six hundred and fifty five alumni and ranked the smiles 290 00:15:17,840 --> 00:15:19,800 Speaker 1: and those photographs in the scale of two which is 291 00:15:19,840 --> 00:15:23,360 Speaker 1: your complete gloomy, gus angsty teenager smile to a full tin, 292 00:15:23,600 --> 00:15:26,920 Speaker 1: which is your complete electrodes attached to the face, grim 293 00:15:27,040 --> 00:15:30,000 Speaker 1: beaming from ear to ear smile. And the participants in 294 00:15:30,000 --> 00:15:31,880 Speaker 1: these studies were also asked a series of questions about 295 00:15:31,880 --> 00:15:35,280 Speaker 1: their relationships, that status, their divorce history, and UH, and 296 00:15:35,360 --> 00:15:39,120 Speaker 1: the non smilers were actually more likely, it turned out 297 00:15:39,120 --> 00:15:40,920 Speaker 1: to be divorced, and the people who smiled at the most. 298 00:15:40,960 --> 00:15:43,000 Speaker 1: Now then they also did some follow up on this 299 00:15:43,160 --> 00:15:45,800 Speaker 1: right UH, they performed a second round of smile rankings, 300 00:15:45,800 --> 00:15:48,720 Speaker 1: this time recruiting sixty one adults fifty five years older 301 00:15:48,720 --> 00:15:51,360 Speaker 1: who are willing to hand over a handful of photographs 302 00:15:51,360 --> 00:15:53,480 Speaker 1: from when they were ages five to twenty two, and 303 00:15:53,520 --> 00:15:55,680 Speaker 1: once again, the people who smiled the most in their 304 00:15:55,680 --> 00:15:59,400 Speaker 1: photographs were least likely to be divorced. Okay and the 305 00:15:59,520 --> 00:16:03,840 Speaker 1: University of California, Berkeley, they also studied as a thirty 306 00:16:03,920 --> 00:16:08,000 Speaker 1: year longitudinal study of yearbook photos of women who had 307 00:16:08,080 --> 00:16:12,640 Speaker 1: the best, you know, truest smiles, and they found the 308 00:16:12,680 --> 00:16:15,120 Speaker 1: same sort of thing that after a thirty year study 309 00:16:15,160 --> 00:16:17,120 Speaker 1: of those people who had those true blue smiles, that 310 00:16:17,200 --> 00:16:20,840 Speaker 1: women who smiled the most and those photos had the 311 00:16:20,840 --> 00:16:25,000 Speaker 1: happier lives, happier marriages, and fewer setbacks, which leads me 312 00:16:25,080 --> 00:16:28,720 Speaker 1: to the baseball cards study, which is very similar. This 313 00:16:28,800 --> 00:16:33,040 Speaker 1: is a Wayne State University research project examining the baseball 314 00:16:33,080 --> 00:16:36,520 Speaker 1: card photos of major league players in nineteen fifty two, 315 00:16:37,000 --> 00:16:39,480 Speaker 1: and players who didn't smile in their pictures lived an 316 00:16:39,480 --> 00:16:42,960 Speaker 1: average of only seventy two point nine years, while players 317 00:16:43,000 --> 00:16:46,240 Speaker 1: with beaming smiles they lived in average of seventy nine 318 00:16:46,240 --> 00:16:48,560 Speaker 1: point nine years. So with this data suggests is that 319 00:16:48,640 --> 00:16:51,920 Speaker 1: smiling increased life expectancy. Now, some people will look at 320 00:16:51,920 --> 00:16:54,960 Speaker 1: these studies and say, okay, yeah, but in terms of 321 00:16:55,400 --> 00:17:00,400 Speaker 1: cultural responses to smiling, men are sometimes not encouraged smile. 322 00:17:00,800 --> 00:17:03,680 Speaker 1: So perhaps that person was happy, but they just didn't smile. 323 00:17:04,280 --> 00:17:08,600 Speaker 1: Or perhaps the person smiling was thinking about something that 324 00:17:08,720 --> 00:17:11,840 Speaker 1: really sort of made them feel warm and fuzzing on 325 00:17:11,880 --> 00:17:14,480 Speaker 1: the inside. Maybe they were thinking about their children, and 326 00:17:14,560 --> 00:17:16,280 Speaker 1: so at that very moment they got a picture of 327 00:17:16,280 --> 00:17:18,680 Speaker 1: what that person's frame of mind was, but that wasn't 328 00:17:18,680 --> 00:17:21,560 Speaker 1: necessarily true for how they conducted the rest of their lives. Yeah, 329 00:17:21,600 --> 00:17:24,600 Speaker 1: I mean, there's plenty of room to pick this apart, 330 00:17:24,840 --> 00:17:27,040 Speaker 1: you know, Stanley, there because there are a lot of 331 00:17:27,080 --> 00:17:30,119 Speaker 1: people who were significantly happier after they got out of 332 00:17:30,160 --> 00:17:31,880 Speaker 1: high school. For instance, there are a lot of people 333 00:17:31,920 --> 00:17:34,960 Speaker 1: who for whom everything after high school was just a 334 00:17:34,960 --> 00:17:38,359 Speaker 1: backward gaze to the brilliance that was their senior year. 335 00:17:38,400 --> 00:17:40,040 Speaker 1: I mean, and then when you start to your point, 336 00:17:40,040 --> 00:17:44,600 Speaker 1: when you start looking about the differences internationally and culturally, um, 337 00:17:44,640 --> 00:17:46,199 Speaker 1: you know, how would the study have looked if it 338 00:17:46,240 --> 00:17:48,560 Speaker 1: had it been conducted in Thailand? How would it look 339 00:17:48,640 --> 00:17:53,280 Speaker 1: had it been conducted in Scandinavian country. So one say 340 00:17:53,400 --> 00:17:57,119 Speaker 1: that that's far harder to pick apart. Has to do 341 00:17:57,200 --> 00:18:02,960 Speaker 1: with stress and chopsticks. Yes, Now, unlike the pencil scenario 342 00:18:03,000 --> 00:18:04,760 Speaker 1: where you stick a pencil in your mouth and suddenly 343 00:18:04,840 --> 00:18:08,760 Speaker 1: you're you're inhibited from smiling, you can, of course take 344 00:18:08,800 --> 00:18:12,880 Speaker 1: two chopsticks and you can force a smile. Um, I've 345 00:18:12,920 --> 00:18:14,919 Speaker 1: never done that. Was this a thing? Is this like 346 00:18:14,960 --> 00:18:18,000 Speaker 1: a horsing around with chopsticks kind of gag? Or is 347 00:18:18,040 --> 00:18:20,080 Speaker 1: this just something that thought up of the experiment. I 348 00:18:20,119 --> 00:18:22,880 Speaker 1: think it was just for the experiment because what they 349 00:18:22,880 --> 00:18:27,240 Speaker 1: could do with these chopsticks is they could manipulate more muscles. 350 00:18:27,560 --> 00:18:31,800 Speaker 1: We were talking about hundred sixty nine participants who muscles 351 00:18:31,800 --> 00:18:35,680 Speaker 1: were manipulated with chopsticks into a neutral expression, a standard 352 00:18:35,720 --> 00:18:38,719 Speaker 1: smile or a doc in smile. Because that way they 353 00:18:38,720 --> 00:18:43,879 Speaker 1: could test all these different stress reactions against those mimicking 354 00:18:44,200 --> 00:18:48,680 Speaker 1: neuronal signals that were going up to the brain. Right, So, 355 00:18:48,760 --> 00:18:52,920 Speaker 1: in addition to the chopstick placement, some were explicitly instructed 356 00:18:52,960 --> 00:18:55,520 Speaker 1: to smile. Then, of course this is where the stress 357 00:18:55,560 --> 00:18:57,960 Speaker 1: comes in. They were subjected to a series of stress 358 00:18:58,000 --> 00:19:02,480 Speaker 1: inducing multitasking activities which they struggle to perform, of course, 359 00:19:02,520 --> 00:19:06,040 Speaker 1: because they have chopsticks in their face while continuing to 360 00:19:06,080 --> 00:19:08,960 Speaker 1: hold the chopsticks um, and the subjects heart rates and 361 00:19:09,040 --> 00:19:13,480 Speaker 1: self reported stress levels were monitored throughout, So those who 362 00:19:13,600 --> 00:19:16,760 Speaker 1: were instructed to smile recovered from these stressful activities with 363 00:19:16,840 --> 00:19:20,959 Speaker 1: lower heart rates than those who held neutral expressions, and 364 00:19:21,040 --> 00:19:24,720 Speaker 1: those with duchene smiles were the most relaxed of all, 365 00:19:25,000 --> 00:19:27,600 Speaker 1: with the most positive effects. And those with four smiles 366 00:19:27,640 --> 00:19:31,080 Speaker 1: held only by the chopsticks also reported more positive feelings 367 00:19:31,080 --> 00:19:32,840 Speaker 1: than those who didn't smile at all. So, I mean, 368 00:19:32,880 --> 00:19:37,560 Speaker 1: the big story here is that um neutral expressions, they 369 00:19:37,600 --> 00:19:40,640 Speaker 1: have more stress or that they seem to uh not 370 00:19:40,680 --> 00:19:45,280 Speaker 1: be able to weather this multitasking with the lower heart rates, right, 371 00:19:46,240 --> 00:19:49,040 Speaker 1: But those with that true blue smile, that duchene smile, 372 00:19:49,560 --> 00:19:53,440 Speaker 1: they have sailed away on this and even the fake 373 00:19:53,480 --> 00:19:57,959 Speaker 1: smiles actually had a positive influence. And that's really telling 374 00:19:57,960 --> 00:20:00,119 Speaker 1: as well and interesting because you tend to think of 375 00:20:00,520 --> 00:20:02,960 Speaker 1: the fake smile like when you encounter like that genuine 376 00:20:02,960 --> 00:20:08,040 Speaker 1: fake smile on somebody's face, uh, you you often think you're, like, 377 00:20:08,119 --> 00:20:09,840 Speaker 1: what kind of monster is on the other side of it? 378 00:20:09,920 --> 00:20:12,439 Speaker 1: What kind of just complete emotional blank slate, am I 379 00:20:12,520 --> 00:20:16,040 Speaker 1: actually having a conversation with And in reality, here's this 380 00:20:16,080 --> 00:20:18,959 Speaker 1: person who's I mean, they're wearing the mask, but the 381 00:20:19,000 --> 00:20:21,520 Speaker 1: mask is wearing them, you know, I know. It's just 382 00:20:21,560 --> 00:20:24,440 Speaker 1: thinking about two examples of that. One is the beauty 383 00:20:24,520 --> 00:20:28,399 Speaker 1: queen smile, which can be a terrifying smile also because 384 00:20:28,520 --> 00:20:31,199 Speaker 1: you know, there's a large amount of drag, makeup and 385 00:20:31,280 --> 00:20:33,879 Speaker 1: gender performance going on. And the second thing is the 386 00:20:33,880 --> 00:20:37,200 Speaker 1: mayor from the Nightmare before Christmas? Do you remember this? 387 00:20:37,600 --> 00:20:40,520 Speaker 1: He had a frown and he had a smile, and 388 00:20:40,600 --> 00:20:42,960 Speaker 1: so it would revolve around depending on you know, who 389 00:20:43,000 --> 00:20:46,520 Speaker 1: he was constituent he was talking to. Um. But yeah, 390 00:20:46,600 --> 00:20:49,080 Speaker 1: I mean this is this is the interesting thing about 391 00:20:49,160 --> 00:20:51,919 Speaker 1: even that terrifying fake smile is going to give you 392 00:20:51,960 --> 00:20:54,880 Speaker 1: a little bit of a lift. And here is yet 393 00:20:54,960 --> 00:20:57,600 Speaker 1: another study about smiling, and this one has to do 394 00:20:57,760 --> 00:21:01,000 Speaker 1: with pain. Um. It turns out at people who frowned 395 00:21:01,080 --> 00:21:04,840 Speaker 1: during an unpleasant procedure, they report feeling more pain than 396 00:21:04,880 --> 00:21:07,399 Speaker 1: those who do not. This is a study that was 397 00:21:07,480 --> 00:21:10,280 Speaker 1: published in the Journal of Pain. And what happened is 398 00:21:10,320 --> 00:21:13,679 Speaker 1: that the researchers applied heat to the forums of twenty 399 00:21:13,720 --> 00:21:16,840 Speaker 1: nine participants who were asked to either make unhappy, neutral, 400 00:21:16,920 --> 00:21:19,359 Speaker 1: or relax faces during the procedure, and lo and behold. 401 00:21:19,520 --> 00:21:23,639 Speaker 1: Those who exhibited negative expressions reported being in more pain 402 00:21:23,680 --> 00:21:26,680 Speaker 1: than the others. That reminds me of one of the 403 00:21:26,760 --> 00:21:28,879 Speaker 1: yoga classes I used to go to, back when I 404 00:21:28,880 --> 00:21:31,720 Speaker 1: got to go to yoga. Would always wait until we 405 00:21:31,720 --> 00:21:35,600 Speaker 1: were in some sort of complicated balancing scenario and uh, 406 00:21:35,640 --> 00:21:37,679 Speaker 1: and we're all standing out there, no doubt what kind 407 00:21:37,680 --> 00:21:41,000 Speaker 1: of strange faces going on, and she would encourage everyone 408 00:21:41,040 --> 00:21:42,639 Speaker 1: to smile, Like if you just said, if you're if 409 00:21:42,680 --> 00:21:45,159 Speaker 1: you can't smile, you're you're working too hard at it. 410 00:21:45,520 --> 00:21:49,040 Speaker 1: And so you you'd force a smile while you know, 411 00:21:49,080 --> 00:21:52,080 Speaker 1: wrapped in eagle pose or something, and and it would 412 00:21:52,080 --> 00:21:53,920 Speaker 1: have this I feel like it would have the strengthening 413 00:21:53,920 --> 00:21:56,280 Speaker 1: effect at least on me, Like I'm suddenly I'm smiling, 414 00:21:56,320 --> 00:21:57,760 Speaker 1: and I can actually make it through the pose a 415 00:21:57,800 --> 00:22:00,800 Speaker 1: little longer than I'm just setting there kind of uh, 416 00:22:00,880 --> 00:22:04,560 Speaker 1: you know, grimly trying to to force myself into this position. Right, 417 00:22:04,600 --> 00:22:06,760 Speaker 1: It had a calming effect. And so that's what we 418 00:22:06,840 --> 00:22:09,800 Speaker 1: see over and over again in these studies. Grant Embarrett 419 00:22:09,960 --> 00:22:13,000 Speaker 1: grant Embarrett Nights, which incidentally, was the title of that 420 00:22:13,040 --> 00:22:16,119 Speaker 1: study we're just talking about with the chopsticks, Grin and Barrett, 421 00:22:16,160 --> 00:22:19,760 Speaker 1: the influence of manipulated positive facial expression on the stress response. 422 00:22:20,680 --> 00:22:23,720 Speaker 1: So we talked about the divide between adults and children 423 00:22:23,920 --> 00:22:26,040 Speaker 1: as far as smiles goes. But but how about the 424 00:22:26,240 --> 00:22:30,000 Speaker 1: gender divide. Well, if there are any women out there 425 00:22:30,080 --> 00:22:33,639 Speaker 1: listening to this, and you've ever had someone tell you 426 00:22:33,720 --> 00:22:36,440 Speaker 1: to smile, probably an older gentleman than you. Know what 427 00:22:36,520 --> 00:22:39,720 Speaker 1: I'm talking about here in terms of what is sometimes 428 00:22:39,760 --> 00:22:41,879 Speaker 1: expected of women, that they're going to be friendly, that 429 00:22:41,920 --> 00:22:45,000 Speaker 1: they're going to smile, And so you tend to think 430 00:22:45,000 --> 00:22:47,800 Speaker 1: of women smiling more, and you often see studies that 431 00:22:47,920 --> 00:22:51,000 Speaker 1: say that women do. But then you have someone named 432 00:22:51,000 --> 00:22:55,159 Speaker 1: Marianne la France. She is a professor of psychology at Yale, 433 00:22:55,800 --> 00:22:59,560 Speaker 1: and she says that wide cultural, ethnic, and other differences 434 00:22:59,560 --> 00:23:03,000 Speaker 1: suggest that the sex difference is not something that is hardwired, 435 00:23:03,840 --> 00:23:06,679 Speaker 1: so it's not a function of being male or female, 436 00:23:06,760 --> 00:23:10,399 Speaker 1: but that there's a cultural overlay that sort of tells 437 00:23:10,440 --> 00:23:13,520 Speaker 1: he tells us about these rules about smiling, and she did. 438 00:23:13,880 --> 00:23:17,119 Speaker 1: She and co authors Elizabeth Pallack of Fale and Marvin 439 00:23:17,160 --> 00:23:20,760 Speaker 1: Heck examined hundred and eighty six research reports about smiling 440 00:23:20,760 --> 00:23:25,679 Speaker 1: and gender and came up with some very interesting information. First, 441 00:23:25,720 --> 00:23:28,359 Speaker 1: they found that women do smile more than them but 442 00:23:28,440 --> 00:23:31,520 Speaker 1: the difference is really modest. Yes. And she also found 443 00:23:31,520 --> 00:23:34,560 Speaker 1: that when when occupying similar work and social status, the 444 00:23:34,600 --> 00:23:37,840 Speaker 1: gender differences in the rate of smiling tends to disappear. So, yeah, 445 00:23:37,840 --> 00:23:40,920 Speaker 1: everyone's working in the same pit or the same office, 446 00:23:41,640 --> 00:23:43,920 Speaker 1: then you're gonna see you're not gonna see as much 447 00:23:43,920 --> 00:23:46,760 Speaker 1: of this social contract and play that not in the 448 00:23:46,760 --> 00:23:49,320 Speaker 1: same way that it would be outside of the workplace. Well, 449 00:23:49,320 --> 00:23:52,399 Speaker 1: and in those instances of the playing field is leveled 450 00:23:52,400 --> 00:23:55,080 Speaker 1: because they occupy the same position of power, So it's 451 00:23:55,119 --> 00:23:58,960 Speaker 1: not necessary for women to put on that thick smile, yeah, 452 00:23:59,160 --> 00:24:03,359 Speaker 1: to try to amelior every situation. Um. Another finding was 453 00:24:03,400 --> 00:24:05,280 Speaker 1: that the rate at which men and women differ and 454 00:24:05,280 --> 00:24:07,320 Speaker 1: how much they smile is greater in the United States 455 00:24:07,320 --> 00:24:09,320 Speaker 1: and Canada than other parts of the world like England 456 00:24:09,359 --> 00:24:12,680 Speaker 1: and Australia and the US. There's a greater sex difference 457 00:24:12,720 --> 00:24:17,200 Speaker 1: among Caucasians in smiling, but this difference virtually disappears among 458 00:24:17,320 --> 00:24:22,000 Speaker 1: African Americans, and in terms of age differences, teens show 459 00:24:22,080 --> 00:24:25,600 Speaker 1: the largest sex difference in smiling. After that, the sexes 460 00:24:25,640 --> 00:24:28,520 Speaker 1: converge on their smile. Right, So that's this idea that 461 00:24:28,600 --> 00:24:33,280 Speaker 1: teens are really very preoccupied with gender roles at that 462 00:24:33,400 --> 00:24:36,600 Speaker 1: point and performing those gender roles. So perhaps that's why 463 00:24:36,920 --> 00:24:39,280 Speaker 1: that is the biggest difference that's seen. So the guys 464 00:24:39,280 --> 00:24:41,000 Speaker 1: are given in more to this idea though you need 465 00:24:41,040 --> 00:24:43,160 Speaker 1: to be a little more macho and not smile. Yeah, 466 00:24:43,200 --> 00:24:47,399 Speaker 1: I'm tough, I'm angsty, I'm very deep man, whereas the 467 00:24:47,880 --> 00:24:51,320 Speaker 1: females are more feel more pressure to be that smiley, 468 00:24:51,320 --> 00:24:55,720 Speaker 1: happy creature. Yeah. And another finding this was pretty fascinating, 469 00:24:55,760 --> 00:24:58,080 Speaker 1: the largest sex differences in smiling a card when men 470 00:24:58,160 --> 00:25:02,600 Speaker 1: and women thought they were being observed. So again that's 471 00:25:02,600 --> 00:25:05,600 Speaker 1: this idea that, um, you know, if you're being observed, 472 00:25:05,600 --> 00:25:07,840 Speaker 1: then you're going to fulfill whatever social role you think 473 00:25:07,840 --> 00:25:11,000 Speaker 1: you're supposed to be playing. And you know, perhaps then 474 00:25:11,040 --> 00:25:14,040 Speaker 1: that's when you see women smiling more, because that's what 475 00:25:14,080 --> 00:25:17,159 Speaker 1: women do in in in the bigger social contract that 476 00:25:17,240 --> 00:25:19,800 Speaker 1: we all are sort of signing on too. And as 477 00:25:19,840 --> 00:25:22,480 Speaker 1: we talked about the teenager brain before and our we 478 00:25:22,480 --> 00:25:24,199 Speaker 1: did a whole episode on that. Check that out in 479 00:25:24,240 --> 00:25:27,760 Speaker 1: our archives we talked about just how far more important 480 00:25:27,840 --> 00:25:30,560 Speaker 1: the social world is to the teenager because you have 481 00:25:30,720 --> 00:25:33,240 Speaker 1: an organism that is has evolved to the point where 482 00:25:33,240 --> 00:25:35,200 Speaker 1: it's supposed to be branching off and finding a new 483 00:25:35,240 --> 00:25:37,399 Speaker 1: tribe to live in and fit in with, and therefore 484 00:25:37,440 --> 00:25:41,159 Speaker 1: it's it's to the to the species side of us, 485 00:25:41,520 --> 00:25:44,359 Speaker 1: it is it is literally life and death, even though 486 00:25:44,880 --> 00:25:47,320 Speaker 1: social agent in high school it's not life and death. 487 00:25:47,600 --> 00:25:50,639 Speaker 1: So um, so you can imagine how this, uh, the 488 00:25:50,680 --> 00:25:53,080 Speaker 1: pressure to smile or not to smile would be even 489 00:25:53,160 --> 00:25:56,679 Speaker 1: greater in in say high school lunch ron. Well, yes, 490 00:25:56,760 --> 00:25:59,600 Speaker 1: especially if you thought that your smile might be rejected, 491 00:26:00,000 --> 00:26:03,160 Speaker 1: because we talked about how that the pain was actually 492 00:26:03,240 --> 00:26:06,120 Speaker 1: felt more in the teenage brain, and we've talked about 493 00:26:06,119 --> 00:26:09,400 Speaker 1: how pain in terms of emotion and physical pain are 494 00:26:09,440 --> 00:26:13,480 Speaker 1: both processed by the magdala. So um, yeah, I can 495 00:26:13,520 --> 00:26:15,439 Speaker 1: see that. So I think what the spells out to 496 00:26:15,440 --> 00:26:18,800 Speaker 1: everybody is you gotta smile. You don't have a choice. Yeah, 497 00:26:18,840 --> 00:26:21,600 Speaker 1: you will smile, don't fight it. In fact, you really 498 00:26:21,600 --> 00:26:24,439 Speaker 1: should probably be going in the opposite direction, trying to 499 00:26:24,480 --> 00:26:27,240 Speaker 1: smile more faking it until you make it, but also 500 00:26:27,320 --> 00:26:30,960 Speaker 1: just faking it in general. Um now on the on 501 00:26:31,000 --> 00:26:33,680 Speaker 1: the subject of fake smiles, Mary le France we mentioned 502 00:26:33,680 --> 00:26:36,679 Speaker 1: earlier um I was reading a Wired dot com interview 503 00:26:36,680 --> 00:26:39,280 Speaker 1: with her, and she pointed out that the problem is 504 00:26:39,320 --> 00:26:42,240 Speaker 1: that in some situations were just too preoccupied with other 505 00:26:42,280 --> 00:26:44,960 Speaker 1: details that we're just not going to notice. You know, 506 00:26:44,960 --> 00:26:47,520 Speaker 1: it's like, all right, somebody smiling, they're talking at me, Fine, 507 00:26:48,240 --> 00:26:50,360 Speaker 1: you just let it pass. But if you're actually able 508 00:26:50,400 --> 00:26:52,720 Speaker 1: to focus in on that grin and it actually becomes 509 00:26:52,720 --> 00:26:55,880 Speaker 1: the thing that you're you're thinking about and contemplating, then 510 00:26:55,920 --> 00:26:59,080 Speaker 1: you can more often than not see through the fakeness. Well, 511 00:26:59,119 --> 00:27:02,080 Speaker 1: and we've talked about micro expressions before, the split second 512 00:27:02,400 --> 00:27:06,399 Speaker 1: expressions across the face, and so we we pick up 513 00:27:06,400 --> 00:27:08,160 Speaker 1: on those, like you say, if you're really paying attention, 514 00:27:08,200 --> 00:27:10,240 Speaker 1: if you're not distracted, so you could have a smile, 515 00:27:10,280 --> 00:27:12,600 Speaker 1: but you could also have a WinCE in there. So 516 00:27:12,640 --> 00:27:14,359 Speaker 1: it was really important for us to be able to 517 00:27:14,400 --> 00:27:17,920 Speaker 1: pick up on those really subtle hints about what someone's feeling, 518 00:27:18,200 --> 00:27:20,720 Speaker 1: because a lot of the way that we communicate is 519 00:27:21,040 --> 00:27:26,520 Speaker 1: non verbal. So here's a question, should we all have 520 00:27:26,800 --> 00:27:31,600 Speaker 1: permanent smiles inscribed on our faces? Because this has apparently 521 00:27:31,640 --> 00:27:35,119 Speaker 1: been a trend to some degree in South Korea, with 522 00:27:35,240 --> 00:27:38,720 Speaker 1: the individuals getting this, uh, this perma smile etched into 523 00:27:38,720 --> 00:27:41,160 Speaker 1: their face kind of kind of a mild like little 524 00:27:41,240 --> 00:27:42,560 Speaker 1: just in a little up turn out like a full 525 00:27:42,600 --> 00:27:46,040 Speaker 1: on joker face. But that the idea of then you'll 526 00:27:46,040 --> 00:27:48,280 Speaker 1: look happier all the time. And really, when you look 527 00:27:48,280 --> 00:27:50,680 Speaker 1: at the science, it begins to make a certain sort 528 00:27:50,720 --> 00:27:53,760 Speaker 1: of sense. Like if you'd ask me beforehand, hey, would 529 00:27:53,800 --> 00:27:55,400 Speaker 1: you want to have a smile inscribed in your face? 530 00:27:55,400 --> 00:27:57,320 Speaker 1: I would say no. And I would still say no, 531 00:27:57,480 --> 00:28:00,280 Speaker 1: but I would at least now be able to say all. 532 00:28:00,920 --> 00:28:02,600 Speaker 1: I wouldn't do it personally, but I can see what 533 00:28:02,640 --> 00:28:04,960 Speaker 1: the benefits would be. I don't know. I think that 534 00:28:05,000 --> 00:28:09,640 Speaker 1: it would be really confusing in seriously sad situations if 535 00:28:09,640 --> 00:28:12,880 Speaker 1: someone was staring back at me with a little smile. Well, yeah, 536 00:28:12,920 --> 00:28:15,119 Speaker 1: because to your point, the social contract, and sometimes the 537 00:28:15,200 --> 00:28:18,800 Speaker 1: social contract is saying do not smile, do not at 538 00:28:18,800 --> 00:28:21,600 Speaker 1: this very moment. Do the opposite of that, please, Yeah, 539 00:28:21,600 --> 00:28:22,840 Speaker 1: So if you look at it that way, it would 540 00:28:23,080 --> 00:28:24,800 Speaker 1: be a definite problem. You'd really have to be in 541 00:28:24,800 --> 00:28:29,679 Speaker 1: the right occupation, like maybe newscaster, like not not like 542 00:28:29,720 --> 00:28:33,600 Speaker 1: a full like twenty four our newscaster, but more like 543 00:28:33,680 --> 00:28:37,959 Speaker 1: a local newscaster. I think like the good morning you know, 544 00:28:38,000 --> 00:28:41,280 Speaker 1: like happy news person. Yeah where even even countering before, 545 00:28:41,280 --> 00:28:43,800 Speaker 1: like they're even delivering kind of down news, but they 546 00:28:43,800 --> 00:28:45,600 Speaker 1: still keep that smile on their face. They think it's 547 00:28:45,640 --> 00:28:47,480 Speaker 1: a little it can be a little creepy because then 548 00:28:47,520 --> 00:28:49,160 Speaker 1: we're back in the area. If you're using a smile 549 00:28:49,320 --> 00:28:52,400 Speaker 1: when you really shouldn't be, and and it's really skewing 550 00:28:52,400 --> 00:28:54,360 Speaker 1: the message you're trying to relate, we'll see that's the 551 00:28:54,360 --> 00:28:59,400 Speaker 1: botox problem. Like there are some applications of botox that 552 00:28:59,480 --> 00:29:02,960 Speaker 1: actually will inhibit the person to use the muscles to frown. 553 00:29:03,600 --> 00:29:06,920 Speaker 1: And you know, by the way those people report being 554 00:29:06,920 --> 00:29:10,960 Speaker 1: happier perhaps because they can't frown, but again, you can't 555 00:29:10,960 --> 00:29:12,920 Speaker 1: take the social cue off of their face and really 556 00:29:12,960 --> 00:29:15,440 Speaker 1: know what they're thinking or responding to. Right, And then 557 00:29:15,480 --> 00:29:17,000 Speaker 1: it comes back to what we were talking about earlier. 558 00:29:17,040 --> 00:29:19,680 Speaker 1: If if you were to whatever degree you were inhibited 559 00:29:19,880 --> 00:29:23,400 Speaker 1: from smiling, you are that inhibit your ability to sync 560 00:29:23,440 --> 00:29:27,160 Speaker 1: with someone else's smile to understand the emotions behind behind 561 00:29:27,240 --> 00:29:30,080 Speaker 1: their facial situation. All right, So think about that the 562 00:29:30,200 --> 00:29:33,000 Speaker 1: next time you engage in a smiling session. With your 563 00:29:33,040 --> 00:29:35,920 Speaker 1: fellow human. Do you see the crinkler eyes or is 564 00:29:35,960 --> 00:29:40,520 Speaker 1: it just the zygomatic major muscle plan let us know. Yeah, 565 00:29:40,520 --> 00:29:41,560 Speaker 1: if you want to get in touch with us, you 566 00:29:41,560 --> 00:29:43,640 Speaker 1: can find us in all the normal places. You want 567 00:29:43,640 --> 00:29:45,760 Speaker 1: to see that smile gallery we're talking about. Head to 568 00:29:45,880 --> 00:29:48,000 Speaker 1: Stuff to Bow your Mind dot com. That's the mothership. 569 00:29:48,040 --> 00:29:50,800 Speaker 1: That's where we put all the podcast episodes, and I 570 00:29:50,880 --> 00:29:52,280 Speaker 1: mean all of them, not just the ones that are 571 00:29:52,320 --> 00:29:54,760 Speaker 1: available on iTunes and wherever you go to get it. 572 00:29:54,920 --> 00:29:56,200 Speaker 1: We have all of them on the site. You can 573 00:29:56,200 --> 00:29:58,640 Speaker 1: also find our blog posts, you can find our videos, 574 00:29:59,160 --> 00:30:01,320 Speaker 1: you can find links all of our social accounts, and 575 00:30:01,400 --> 00:30:03,000 Speaker 1: you can just go to those social accounts out right. 576 00:30:03,280 --> 00:30:06,840 Speaker 1: We are generally going at it on Facebook, Twitter, Tumbler, 577 00:30:07,280 --> 00:30:09,560 Speaker 1: We're on Google Plus and hey, we also have that 578 00:30:09,600 --> 00:30:13,200 Speaker 1: YouTube channel, Mind Stuff Show, And you can always craft 579 00:30:13,240 --> 00:30:15,560 Speaker 1: an email and send it to Blow the Mind at 580 00:30:15,560 --> 00:30:21,680 Speaker 1: Discovery dot com. For more on this and thousands of 581 00:30:21,680 --> 00:30:30,840 Speaker 1: other topics, visit how Stuff Works dot com