1 00:00:00,280 --> 00:00:02,840 Speaker 1: Brought to you by the reinvented two thousand twelve camera. 2 00:00:03,160 --> 00:00:07,560 Speaker 1: It's ready. Are you welcome to Stuff you Should Know 3 00:00:08,160 --> 00:00:16,479 Speaker 1: from house Stuff Works dot Com. Hey, and welcome to 4 00:00:16,480 --> 00:00:20,200 Speaker 1: the podcast. I'm Josh Clark. There's Charles W. Chuck Bryant 5 00:00:20,680 --> 00:00:24,440 Speaker 1: that makes this stuff you should know? Hey, man, how 6 00:00:24,480 --> 00:00:28,600 Speaker 1: are you doing? You're all smiles, aren't you? I am? 7 00:00:28,840 --> 00:00:31,600 Speaker 1: Is this uh, this article that we're about to talk about? 8 00:00:31,640 --> 00:00:34,760 Speaker 1: Did it make you smile? Reading it? Like the contages? Yawn? Anyway, 9 00:00:35,840 --> 00:00:39,680 Speaker 1: I'm pretty smiling though. You're fairly smiling unless I'm actively 10 00:00:40,800 --> 00:00:44,800 Speaker 1: piste off about something, and then I'll probably be smiling. Okay, 11 00:00:45,240 --> 00:00:47,600 Speaker 1: but you just seen me up sat too. That happens. 12 00:00:48,000 --> 00:00:52,159 Speaker 1: I've never seen you upset. Hey, you just smiled just now? 13 00:00:52,360 --> 00:00:54,600 Speaker 1: Maybe smile? Was that a fake smiler? Was that a 14 00:00:54,920 --> 00:00:58,120 Speaker 1: what's called a duchese smile? That was Duquese baby all 15 00:00:58,120 --> 00:01:00,520 Speaker 1: the way? So we're gonna go with Duke, but it 16 00:01:00,560 --> 00:01:04,560 Speaker 1: could be Duken. Uh, there's two ends, so I think 17 00:01:04,600 --> 00:01:08,440 Speaker 1: it may be Duken zu Ken smile. It's French. It's 18 00:01:08,520 --> 00:01:12,880 Speaker 1: named after a frenchie, Giom Duken. He's a neurologist, one 19 00:01:12,880 --> 00:01:15,080 Speaker 1: of the early ones where it was basically like, oh, 20 00:01:15,120 --> 00:01:17,880 Speaker 1: there's a brain there and it's in control of everything, 21 00:01:17,959 --> 00:01:21,760 Speaker 1: so let's test all sorts of crazy stuff and we'll 22 00:01:21,959 --> 00:01:26,600 Speaker 1: begin the field of neuroscience right in in eighteen sixty two, 23 00:01:27,400 --> 00:01:29,160 Speaker 1: sort of oddly at the time, I think there was 24 00:01:29,200 --> 00:01:32,520 Speaker 1: so much more interesting things going on to study. He 25 00:01:32,800 --> 00:01:36,600 Speaker 1: figured out that the you know, there's a natural smile, 26 00:01:36,760 --> 00:01:39,880 Speaker 1: and there are facial muscles involved in that that are 27 00:01:39,920 --> 00:01:42,160 Speaker 1: involved with the brain, and so he said, I will 28 00:01:42,319 --> 00:01:45,280 Speaker 1: name it after myself. Well, he was kind of an 29 00:01:45,280 --> 00:01:48,160 Speaker 1: interesting guy and that he was, from what I understand, 30 00:01:48,200 --> 00:01:51,560 Speaker 1: somewhat obsessed with the idea that muscles were connected to 31 00:01:51,600 --> 00:01:55,080 Speaker 1: the soul. Okay, which is weird because that kind of 32 00:01:55,080 --> 00:01:59,200 Speaker 1: provides the basis of later research into facial expressions and 33 00:01:59,240 --> 00:02:02,440 Speaker 1: specifically miling. But he was kind of onto something in 34 00:02:02,480 --> 00:02:05,720 Speaker 1: a weird, roundabout way. But the the way that he 35 00:02:06,120 --> 00:02:09,840 Speaker 1: isolated he was famous for isolating the facial expressions involved 36 00:02:09,840 --> 00:02:13,519 Speaker 1: in the smile. But he did it by taking emotion 37 00:02:13,560 --> 00:02:17,320 Speaker 1: out of the equation. I He did that by shocking 38 00:02:17,360 --> 00:02:21,799 Speaker 1: the facial muscles of patients in his hospital. That's how 39 00:02:21,840 --> 00:02:24,320 Speaker 1: he that's how he identified what muscles were involved in 40 00:02:24,320 --> 00:02:28,680 Speaker 1: a smile and a genuine smile yeah um and uh yeah. 41 00:02:28,760 --> 00:02:32,200 Speaker 1: He he was known to um basically shock people's faces. 42 00:02:32,240 --> 00:02:35,560 Speaker 1: There's a picture of him with a patient these two um, 43 00:02:36,000 --> 00:02:38,480 Speaker 1: these two basically rods that you would use to shock 44 00:02:38,560 --> 00:02:42,400 Speaker 1: somebody and the person is going like, uh, I'm not 45 00:02:42,480 --> 00:02:46,639 Speaker 1: doing this on my own. Yeah wow, Well let's do 46 00:02:46,880 --> 00:02:52,280 Speaker 1: can okay, And that was some pretty shocking experiment station. 47 00:02:53,520 --> 00:02:56,880 Speaker 1: So you can right comes up with a smile and 48 00:02:56,919 --> 00:02:59,600 Speaker 1: it's a that's the genuine smile, but there's also a 49 00:02:59,639 --> 00:03:02,560 Speaker 1: fixed mile and the do ken smile. Also, if you're interested, 50 00:03:02,680 --> 00:03:04,640 Speaker 1: Chuck Um, I didn't send it to you, but there's 51 00:03:04,639 --> 00:03:07,520 Speaker 1: this thing called spot the Fake Smile on BBC. It's 52 00:03:07,520 --> 00:03:09,720 Speaker 1: like twenty different pictures and you pick whether it's fake 53 00:03:09,800 --> 00:03:13,080 Speaker 1: or genuine. Apparently people stink at it. I didn't have 54 00:03:13,120 --> 00:03:14,560 Speaker 1: time to really do it, so I don't know what 55 00:03:14,600 --> 00:03:16,480 Speaker 1: my score was. I did like four of them, but 56 00:03:16,520 --> 00:03:19,600 Speaker 1: they were kind of hard. But the key is when 57 00:03:19,600 --> 00:03:22,800 Speaker 1: you're looking for a genuine smile, the eyes are involved. 58 00:03:22,919 --> 00:03:26,639 Speaker 1: You get the crow's feet right, um, you you're you're 59 00:03:26,760 --> 00:03:30,320 Speaker 1: you get kind of squinty. That's a real smile. Fake 60 00:03:30,360 --> 00:03:34,000 Speaker 1: smiles just the mouth. Yeah. I have jokingly doctored up 61 00:03:34,040 --> 00:03:39,040 Speaker 1: photos of Emily and myself, um, like smudging away wrinkles 62 00:03:39,080 --> 00:03:42,000 Speaker 1: and stuff and crow's feet, just kidding around. I wouldn't 63 00:03:43,000 --> 00:03:44,840 Speaker 1: you know me and pictures I don't care, no you, 64 00:03:45,040 --> 00:03:48,400 Speaker 1: that's that's my bag. Um. But it Emily always says, 65 00:03:48,440 --> 00:03:51,080 Speaker 1: it looks like we're like smiling without her eyes. It 66 00:03:51,120 --> 00:03:54,160 Speaker 1: looks like, you know, that fake smile, like you've been botoxed, 67 00:03:54,240 --> 00:03:58,320 Speaker 1: which will come up later exactly in this discussion. So 68 00:03:58,480 --> 00:04:02,440 Speaker 1: um fax smiling, real smiling. Obviously, the one you want 69 00:04:02,440 --> 00:04:04,920 Speaker 1: to go for is the genuine smile because you you 70 00:04:05,000 --> 00:04:06,960 Speaker 1: can feel it. It's like kind of starts in your 71 00:04:06,960 --> 00:04:10,600 Speaker 1: gut and comes out of your heart right. Um, Like 72 00:04:10,640 --> 00:04:12,400 Speaker 1: when you see a guy fall down on the street 73 00:04:12,440 --> 00:04:15,120 Speaker 1: and you just like you feel that sense of happiness, 74 00:04:15,600 --> 00:04:18,359 Speaker 1: you know, Yeah, you just start whistling. Maybe as you 75 00:04:18,400 --> 00:04:21,400 Speaker 1: walk along your way, you're like, sorry, mr, need need 76 00:04:21,440 --> 00:04:25,000 Speaker 1: a hand, Yeah, And then you happen to have your 77 00:04:25,160 --> 00:04:27,240 Speaker 1: your prosthetic hand in there and you let him pull 78 00:04:27,279 --> 00:04:29,680 Speaker 1: it right off, and you're like, WHOA did I ever 79 00:04:29,720 --> 00:04:31,680 Speaker 1: tell you about the guy in college that fell off 80 00:04:31,760 --> 00:04:34,760 Speaker 1: his bike and his books splayed out all over the 81 00:04:34,800 --> 00:04:37,279 Speaker 1: street in front of like hundreds of students on campus 82 00:04:37,839 --> 00:04:40,080 Speaker 1: and he, uh, he just put his arm on his 83 00:04:40,160 --> 00:04:42,839 Speaker 1: chin and started throwing through one of the boats, laying down. 84 00:04:43,240 --> 00:04:45,680 Speaker 1: Its awesome. It was one of the better reactions I've 85 00:04:45,680 --> 00:04:48,479 Speaker 1: ever seen. That is awesome. Wow. I think that would 86 00:04:48,520 --> 00:04:51,360 Speaker 1: have emotionally crippled me. I was so self conscious in college. 87 00:04:51,720 --> 00:04:53,640 Speaker 1: I would not have like that either. I would have 88 00:04:53,680 --> 00:04:56,440 Speaker 1: been like, well, that's it for me in college, transferring 89 00:04:57,120 --> 00:05:01,679 Speaker 1: to attent exactly in my dad's back, y'all. Um, So chuck, 90 00:05:01,839 --> 00:05:04,120 Speaker 1: we've got the fake the difference between the fake smile 91 00:05:04,160 --> 00:05:05,440 Speaker 1: and the real smile. And I don't know if you 92 00:05:05,520 --> 00:05:08,279 Speaker 1: noticed this. You're a little older than me, but in 93 00:05:08,320 --> 00:05:10,280 Speaker 1: the seventies and eighties, were you aware that there was 94 00:05:10,279 --> 00:05:12,680 Speaker 1: a lot of like, this is the heyday of smile research. 95 00:05:13,320 --> 00:05:15,120 Speaker 1: I didn't know that. It sort of makes sense just 96 00:05:15,120 --> 00:05:18,359 Speaker 1: because that's from the whole happy face boom um. You 97 00:05:18,360 --> 00:05:22,680 Speaker 1: know once Forrest Gump invented that with the face T shirt. Yeah, 98 00:05:22,720 --> 00:05:25,000 Speaker 1: that was a big deal. Smiling was a big deal. Okay, 99 00:05:25,040 --> 00:05:28,640 Speaker 1: So well, people don't put funding into figuring out, what, 100 00:05:28,839 --> 00:05:31,039 Speaker 1: you know, just evaluating smiles. And one of the things 101 00:05:31,040 --> 00:05:33,080 Speaker 1: they found that was kind of surprising, is that that 102 00:05:33,160 --> 00:05:35,080 Speaker 1: fake smile we were talking about, the one that just 103 00:05:36,120 --> 00:05:38,760 Speaker 1: has to do with the mouth and it's not necessarily 104 00:05:38,800 --> 00:05:43,680 Speaker 1: connected to any emotion. The fake smile um actually can 105 00:05:43,800 --> 00:05:47,359 Speaker 1: lead to more positive feelings or a better sense of 106 00:05:47,360 --> 00:05:50,080 Speaker 1: well being, at least in these studies that came out 107 00:05:50,120 --> 00:05:52,800 Speaker 1: of the seventies and eighties. Yeah, there's a lot of studies, 108 00:05:52,839 --> 00:05:55,000 Speaker 1: as it turns out. But that's kind of weird because 109 00:05:55,040 --> 00:05:57,479 Speaker 1: you know, the way we've always thought of smiling is 110 00:05:57,520 --> 00:06:01,080 Speaker 1: your smile as the result of positive feelings. You can 111 00:06:01,240 --> 00:06:05,000 Speaker 1: generate positive feelings from smiling. Right, But there there are 112 00:06:05,080 --> 00:06:07,279 Speaker 1: a bunch of studies, as you say that, and they 113 00:06:07,400 --> 00:06:11,839 Speaker 1: found this body of researches is surprisingly consistent, right, Yeah, 114 00:06:11,960 --> 00:06:16,360 Speaker 1: and the in the late eighties, Uh, this psychologist named 115 00:06:16,440 --> 00:06:21,599 Speaker 1: Robert jan I just took it as a johnic. I 116 00:06:21,600 --> 00:06:24,440 Speaker 1: think there's no Balkan I know, but they add like 117 00:06:24,600 --> 00:06:28,320 Speaker 1: um invisible. It's not silent, it's an invisible vowel a Right. 118 00:06:28,400 --> 00:06:33,200 Speaker 1: This doctor from the Falklands where Balkans Balkans from the Falklands, 119 00:06:33,279 --> 00:06:37,080 Speaker 1: from the Falkland Islands published a study This smile stuff 120 00:06:37,120 --> 00:06:41,080 Speaker 1: is making us so silly. Uh. He had subjects repeat 121 00:06:41,120 --> 00:06:44,320 Speaker 1: vowel sounds, obviously, which would mimic either a smile or 122 00:06:44,320 --> 00:06:45,919 Speaker 1: a frown. So if you're going to mimic a smile, 123 00:06:45,960 --> 00:06:50,599 Speaker 1: you would do like an E R and uh frown, 124 00:06:50,760 --> 00:06:53,720 Speaker 1: you would do a long you you and even your 125 00:06:54,200 --> 00:06:57,400 Speaker 1: brow furrows, even though I think you're exaggerating, but that's 126 00:06:57,440 --> 00:07:01,839 Speaker 1: sort of what happens naturally to your face, right. But 127 00:07:01,839 --> 00:07:04,400 Speaker 1: what he was making them use these vowel sounds because 128 00:07:04,960 --> 00:07:07,680 Speaker 1: to find out whether it has an effect positive or 129 00:07:07,760 --> 00:07:10,800 Speaker 1: negative or none, you have to take emotions out. You 130 00:07:10,800 --> 00:07:13,760 Speaker 1: want them to be emotionally neutral to begin with, which 131 00:07:13,760 --> 00:07:15,320 Speaker 1: is kind of hard because I would be sitting there 132 00:07:15,360 --> 00:07:17,640 Speaker 1: kind of giggling anyway at the stillness of the whole thing. 133 00:07:17,840 --> 00:07:21,480 Speaker 1: But it's similar to like Duke Ken using the shocks. 134 00:07:21,560 --> 00:07:24,120 Speaker 1: You're trying to keep emotion out of it to generate 135 00:07:24,200 --> 00:07:27,040 Speaker 1: I don't think it's something happy, just go right. Uh. 136 00:07:27,040 --> 00:07:30,080 Speaker 1: And they in fact reported the subjects reported feeling better 137 00:07:30,320 --> 00:07:33,480 Speaker 1: with the long sound the sound, and feeling bad with 138 00:07:33,560 --> 00:07:40,000 Speaker 1: the you. So there you have it in case closed, right. Uh. Yeah, 139 00:07:40,680 --> 00:07:43,320 Speaker 1: I guess I do kind of You know, I have 140 00:07:43,400 --> 00:07:47,520 Speaker 1: problems with studies like that anytime it's a they base 141 00:07:47,600 --> 00:07:52,040 Speaker 1: everything on a measure of reported well being subjective well being. Sure, like, 142 00:07:52,080 --> 00:07:55,360 Speaker 1: we've talked a lot about happiness, right, We've got an 143 00:07:55,360 --> 00:07:58,800 Speaker 1: audiobook just sitting there that we've never released on happiness 144 00:07:58,840 --> 00:08:02,080 Speaker 1: just gathering dust. Um, so we know a lot about this, 145 00:08:02,120 --> 00:08:04,120 Speaker 1: and we know that there are a lot of studies 146 00:08:04,160 --> 00:08:07,120 Speaker 1: out there that are just kind of like, you know, yes, 147 00:08:07,960 --> 00:08:11,320 Speaker 1: and if it were just this one, I would I 148 00:08:11,360 --> 00:08:13,200 Speaker 1: would be poop pooing it. But there's a bunch of 149 00:08:13,200 --> 00:08:15,760 Speaker 1: other ones that have kind of followed similar methodology have 150 00:08:15,840 --> 00:08:20,400 Speaker 1: come up with similar results. Well, rather than making vowel sounds, 151 00:08:20,440 --> 00:08:23,280 Speaker 1: there was another study that had people hold a pencil 152 00:08:23,800 --> 00:08:29,240 Speaker 1: and they're in their mouths to make it makes the 153 00:08:29,280 --> 00:08:33,120 Speaker 1: smile or sticking out, which makes a pout out makes 154 00:08:33,120 --> 00:08:37,319 Speaker 1: a pout always remember that there's your mnemonic device. Uh, 155 00:08:37,320 --> 00:08:39,600 Speaker 1: And they found the same thing that people who were 156 00:08:39,840 --> 00:08:42,720 Speaker 1: who had the pens sticking out of their mouths were 157 00:08:42,920 --> 00:08:46,760 Speaker 1: unhappier afterward, and people who are holding the pencil or 158 00:08:46,800 --> 00:08:51,319 Speaker 1: pen lengthwise, we're happier afterwards. That's right, again self reported, 159 00:08:51,360 --> 00:08:53,520 Speaker 1: But this is kind of strange that people are still 160 00:08:53,559 --> 00:08:56,520 Speaker 1: coming in the same conclusion yes, and yet another. Josh 161 00:08:56,679 --> 00:09:00,520 Speaker 1: had um three groups of people. One was shown pictures 162 00:09:01,240 --> 00:09:05,760 Speaker 1: of facial expressions, another group made those facial expressions, and 163 00:09:05,840 --> 00:09:09,400 Speaker 1: yet another made those expressions while looking at themselves in 164 00:09:09,400 --> 00:09:13,920 Speaker 1: a mirror. And then they were asked questions at pinpointed 165 00:09:13,960 --> 00:09:18,440 Speaker 1: their emotional state before and after, and overwhelmingly they scored 166 00:09:18,480 --> 00:09:22,400 Speaker 1: happier after smiling, and the mirror subjects saw an even 167 00:09:22,440 --> 00:09:25,720 Speaker 1: more pronounced change in mood than those who didn't see 168 00:09:25,720 --> 00:09:27,840 Speaker 1: the mirror. So it went. The people who just looked 169 00:09:27,840 --> 00:09:30,680 Speaker 1: at pictures of people smiling didn't have much of a change. 170 00:09:31,200 --> 00:09:33,079 Speaker 1: He didn't have any at all. Mild, they didn't have 171 00:09:33,080 --> 00:09:35,560 Speaker 1: any at all. What it says people who smiled but 172 00:09:35,640 --> 00:09:37,880 Speaker 1: didn't look at pictures and didn't look into a mirror 173 00:09:38,120 --> 00:09:40,760 Speaker 1: had some change. But the people who smiled but they 174 00:09:40,760 --> 00:09:43,000 Speaker 1: looked into a mirror head like through the roof change. 175 00:09:43,160 --> 00:09:45,160 Speaker 1: That's the jackpot. That's when you're looking, You're like, hey, 176 00:09:45,320 --> 00:09:47,360 Speaker 1: look at you got like that guy he's smiling. I'm 177 00:09:47,400 --> 00:09:50,280 Speaker 1: smiling right back, and it's just the love fest. That's 178 00:09:50,280 --> 00:09:52,680 Speaker 1: the finny. I'm always disappointed when I look in the mirror, 179 00:09:52,720 --> 00:09:56,640 Speaker 1: even when I'm smiling. Yeah, yeah, but I shouldn't even 180 00:09:56,640 --> 00:09:59,040 Speaker 1: look in mirrors that much anymore. I think we've talked 181 00:09:59,080 --> 00:10:01,559 Speaker 1: about that. Yeah, we and probably in the How Mirrors 182 00:10:01,559 --> 00:10:07,120 Speaker 1: Work episode. I'm gonna suspect that one. Although that little 183 00:10:07,120 --> 00:10:10,160 Speaker 1: trick mirror. We were on that photo film shoot not 184 00:10:10,240 --> 00:10:11,640 Speaker 1: too long ago and they had one of those mirrors. 185 00:10:11,679 --> 00:10:14,120 Speaker 1: It makes you all squatty. Fun house mirror. I think 186 00:10:14,160 --> 00:10:16,200 Speaker 1: you and I, like five year old stood in front 187 00:10:16,200 --> 00:10:19,000 Speaker 1: of that thing for thirty minutes laughing. Yeah. The funniest 188 00:10:19,000 --> 00:10:20,760 Speaker 1: part with you and I are like going up and down, 189 00:10:20,800 --> 00:10:22,600 Speaker 1: you know, like we're playing in the mirror. But then 190 00:10:22,640 --> 00:10:26,239 Speaker 1: the crew was just walking by, and they looked really deliberate, 191 00:10:26,280 --> 00:10:30,240 Speaker 1: you know, but they like little little person there carrying 192 00:10:30,240 --> 00:10:32,839 Speaker 1: that light it was but with big feet. That was 193 00:10:32,880 --> 00:10:37,520 Speaker 1: pretty cool. Fun house mirrors the best. Um. But this 194 00:10:37,600 --> 00:10:39,640 Speaker 1: is this kind of raises a big question like why 195 00:10:39,679 --> 00:10:43,439 Speaker 1: would looking in the mirror um increase your happiness more 196 00:10:43,440 --> 00:10:47,920 Speaker 1: than just smiling? Right? Um, unless you love yourself? I 197 00:10:47,960 --> 00:10:53,240 Speaker 1: I think you know, I mean that's an explanation. Sure, um, 198 00:10:53,320 --> 00:10:55,280 Speaker 1: but you're probably gonna lose your funding if that's what 199 00:10:55,360 --> 00:10:58,319 Speaker 1: you come you come up with instead, these researchers who 200 00:10:58,360 --> 00:11:03,080 Speaker 1: conducted this particular it um suggested that there's a self 201 00:11:03,120 --> 00:11:09,079 Speaker 1: conscious aspect to um smiling right where if you so 202 00:11:09,200 --> 00:11:12,040 Speaker 1: in the group that just smiled there, if there are 203 00:11:12,040 --> 00:11:15,559 Speaker 1: people who were introspective, who thought about their feelings, who 204 00:11:15,559 --> 00:11:18,720 Speaker 1: were aware of their changes and emotion, those people would 205 00:11:18,720 --> 00:11:23,040 Speaker 1: have had the most UM boost in happiness from just smiling. 206 00:11:23,720 --> 00:11:26,319 Speaker 1: But looking in the mirror. You take all those people 207 00:11:26,400 --> 00:11:30,280 Speaker 1: who aren't necessarily introspective and force them to confront their 208 00:11:30,400 --> 00:11:34,880 Speaker 1: change and emotion by by making them watch themselves smile, 209 00:11:35,600 --> 00:11:38,120 Speaker 1: and so that that it's that almost UM is a 210 00:11:38,160 --> 00:11:41,280 Speaker 1: supplement to self consciousness. If you're not self conscious. This 211 00:11:42,200 --> 00:11:47,600 Speaker 1: simulates that that phenomenon. You see what I'm saying, Like you, 212 00:11:47,600 --> 00:11:49,040 Speaker 1: you don't have to just sit there and think, oh, 213 00:11:49,040 --> 00:11:51,160 Speaker 1: I'm smiling right now, you can see it. You're taking 214 00:11:51,200 --> 00:11:54,480 Speaker 1: it in. So they think that there's a there's a 215 00:11:54,679 --> 00:12:00,160 Speaker 1: psychological aspect to it. But this guy, Roberts Johnic, that's 216 00:12:00,200 --> 00:12:03,160 Speaker 1: what we concluded his name is. He suggests that there's 217 00:12:03,200 --> 00:12:07,800 Speaker 1: a physiological basis for it, right, So there's maybe both. 218 00:12:08,120 --> 00:12:12,160 Speaker 1: So the only thing we're missing now is what Duken thought, 219 00:12:12,400 --> 00:12:15,400 Speaker 1: which is that they're all facial muscles are connected to 220 00:12:15,440 --> 00:12:17,680 Speaker 1: the soul. That's right, and then everybody will just be 221 00:12:17,760 --> 00:12:21,280 Speaker 1: happy and covered. That's right. And interestingly, Josh, this goes 222 00:12:21,320 --> 00:12:25,200 Speaker 1: back to one Chucky Darwin. Yeah, he actually thought of 223 00:12:25,200 --> 00:12:29,199 Speaker 1: the stuff back in the nineteenth century that facial expressions 224 00:12:29,320 --> 00:12:33,839 Speaker 1: don't only reflect emotions, but could be the cause of them. 225 00:12:33,960 --> 00:12:36,320 Speaker 1: And then he got busy with you, now, the whole 226 00:12:36,600 --> 00:12:38,920 Speaker 1: other stuff that he did. That's that little matter if 227 00:12:39,280 --> 00:12:42,120 Speaker 1: the galappa goes and uh, it kind of sat on 228 00:12:42,160 --> 00:12:45,360 Speaker 1: the backburner until the eighties when these new dudes started 229 00:12:45,400 --> 00:12:49,760 Speaker 1: studying it, and uh, doctors aghn I looked at the 230 00:12:49,800 --> 00:12:52,840 Speaker 1: research a little further and basically says, you know what, 231 00:12:53,760 --> 00:12:56,880 Speaker 1: I've got a physiological reason. I've got a hypothesis here 232 00:12:56,920 --> 00:13:00,560 Speaker 1: why a smile might trigger happiness. And it has to 233 00:13:00,600 --> 00:13:05,559 Speaker 1: do with the temperature of your body parts change when 234 00:13:05,559 --> 00:13:09,000 Speaker 1: there's activity there in the muscles, and there's chemical activities 235 00:13:09,040 --> 00:13:11,000 Speaker 1: that happen in that area as well because of that 236 00:13:11,040 --> 00:13:15,400 Speaker 1: temperature change, just like in smiling. Right. Well, he was saying, 237 00:13:15,440 --> 00:13:17,600 Speaker 1: there was other research, I don't think anything to do 238 00:13:17,600 --> 00:13:21,480 Speaker 1: with smiling that that found that changes in temperature in 239 00:13:21,520 --> 00:13:25,560 Speaker 1: the brain led to biochemical changes, right, So like maybe 240 00:13:25,679 --> 00:13:29,880 Speaker 1: more of an endorphin was released when it's cooler. Or basically, 241 00:13:29,920 --> 00:13:34,359 Speaker 1: what they found was when you can connect emotions to temperature, 242 00:13:34,640 --> 00:13:38,080 Speaker 1: A warmer brain is an anxious brain. Yes, maybe it 243 00:13:38,120 --> 00:13:41,160 Speaker 1: has to do with fight or flight. Sure, Um, a 244 00:13:41,360 --> 00:13:47,559 Speaker 1: cooler brain comparatively is a happier brain. And Zgohnic said, Okay, well, 245 00:13:47,600 --> 00:13:50,600 Speaker 1: how does this relate to smiling and what did he find? 246 00:13:50,760 --> 00:13:54,080 Speaker 1: The answer is in the carotid artery, that's right, not 247 00:13:54,200 --> 00:13:58,520 Speaker 1: the cartoid artery is some people mistaken, they say, uh, 248 00:13:58,520 --> 00:14:00,680 Speaker 1: and that is the pipe that livers. Most of the 249 00:14:00,679 --> 00:14:03,160 Speaker 1: blood of the brain flows through an opening called the 250 00:14:03,200 --> 00:14:06,640 Speaker 1: cavernous sinus, and that's got a lot of facial veins there. 251 00:14:06,679 --> 00:14:10,680 Speaker 1: So when you smile, Uh, those muscles tighten, those veins 252 00:14:10,679 --> 00:14:13,360 Speaker 1: are constricted. It's gonna cut down the blood flow going 253 00:14:13,600 --> 00:14:18,280 Speaker 1: through the car Toyd carotid artery, and uh, you're gonna 254 00:14:18,280 --> 00:14:21,080 Speaker 1: get a cooler brain. So it's gonna gonna make you happier. 255 00:14:21,160 --> 00:14:25,080 Speaker 1: But he said, also conversely, when you frown, it actually 256 00:14:25,080 --> 00:14:29,080 Speaker 1: relieves even more pressure on that corodid artery, so more 257 00:14:29,120 --> 00:14:33,240 Speaker 1: blood flows. More blood flow equals more higher temperature in 258 00:14:33,280 --> 00:14:36,000 Speaker 1: the brain and I mean, we're talking about such a 259 00:14:36,040 --> 00:14:40,440 Speaker 1: minute change. But it certainly makes sense that if if 260 00:14:40,440 --> 00:14:44,040 Speaker 1: our brains are sensitive, if the chemical processes in our 261 00:14:44,080 --> 00:14:47,320 Speaker 1: brains are sensitive to very minute changes, which I imagine 262 00:14:47,360 --> 00:14:52,640 Speaker 1: they would be, then this explanation is perfectly rational reasonable. Uh, 263 00:14:52,720 --> 00:14:56,040 Speaker 1: it's not supported in any way. There's like, none of 264 00:14:56,080 --> 00:15:02,080 Speaker 1: these studies show definitively that yes, um, smiling makes you happier, 265 00:15:02,280 --> 00:15:05,880 Speaker 1: but they suggest that the results suggest that there's a 266 00:15:05,880 --> 00:15:11,160 Speaker 1: pretty good chance that people become happier just from smiling, 267 00:15:11,200 --> 00:15:14,280 Speaker 1: even even faking it. Yes, but you found a study 268 00:15:14,320 --> 00:15:18,440 Speaker 1: that refuted that. Josh, Well, let's talk about the botox first. Yes, 269 00:15:18,480 --> 00:15:21,560 Speaker 1: two more studies with both very interesting. So the botox one, 270 00:15:21,640 --> 00:15:23,480 Speaker 1: remember when it supports this, we were saying, like with 271 00:15:23,560 --> 00:15:27,800 Speaker 1: the uh, with the shocks, do Ken's shocks are using 272 00:15:27,840 --> 00:15:30,800 Speaker 1: the pen all right, You're you're trying to take emotion 273 00:15:31,000 --> 00:15:33,720 Speaker 1: out of the equation to see if facial expressions can 274 00:15:33,760 --> 00:15:37,360 Speaker 1: create emotions. With botox is doing the opposite. You're taking 275 00:15:37,400 --> 00:15:41,280 Speaker 1: the facial expressions out to see how that affects emotions. 276 00:15:41,840 --> 00:15:44,360 Speaker 1: And what they found. There's a study from two thousand 277 00:15:44,440 --> 00:15:48,320 Speaker 1: ten from Barnard College in New York UM that found 278 00:15:48,360 --> 00:15:52,840 Speaker 1: that people who have botox botalks we should unsure most 279 00:15:52,880 --> 00:15:57,160 Speaker 1: people know. But it's a it's a toxic proteins, yeah, 280 00:15:57,200 --> 00:16:01,720 Speaker 1: that they inject into your uh skin and too basically 281 00:16:01,760 --> 00:16:05,160 Speaker 1: paralyze it so like you don't have that troublesome space 282 00:16:05,240 --> 00:16:08,280 Speaker 1: between your eyes when you frown, or your your forehead 283 00:16:08,320 --> 00:16:11,160 Speaker 1: doesn't crinkle up, or your crow's feet don't don't crinkle 284 00:16:11,240 --> 00:16:14,120 Speaker 1: up when you smile, and paralyzes the nerves. Yes, and 285 00:16:14,160 --> 00:16:18,240 Speaker 1: it's sort of creepy looking sometimes especially it's not too 286 00:16:18,400 --> 00:16:21,480 Speaker 1: too bad, right, but it's it's super popular these days. 287 00:16:21,480 --> 00:16:26,640 Speaker 1: It is. To have injected into your face is very popular. 288 00:16:26,960 --> 00:16:30,320 Speaker 1: It is pretty we have finally arrived at the dystopian 289 00:16:30,400 --> 00:16:34,160 Speaker 1: future that's been predicted forever. UM. But what they found 290 00:16:34,280 --> 00:16:40,080 Speaker 1: was that people UM who had botox injected reported UM, 291 00:16:40,160 --> 00:16:43,400 Speaker 1: they showed him basically like tear jerk or clips from 292 00:16:43,440 --> 00:16:45,680 Speaker 1: movies or or something like that, like a net Banning 293 00:16:45,720 --> 00:16:48,400 Speaker 1: is on a couch and she's like crippled or something 294 00:16:48,480 --> 00:16:51,560 Speaker 1: like that. Yeah, like Sweet Home, Alabama or something. Yeah, 295 00:16:51,600 --> 00:16:54,080 Speaker 1: exactly like at the end when things turn out right 296 00:16:54,080 --> 00:16:59,200 Speaker 1: for everybody, it's UM. And the people who had received 297 00:16:59,240 --> 00:17:03,080 Speaker 1: botox and actions reported less of an emotional response than 298 00:17:03,120 --> 00:17:06,159 Speaker 1: people who've been given restling, which is another injection, but 299 00:17:06,200 --> 00:17:09,360 Speaker 1: it's a filler, it doesn't paralyze anything. So basically the 300 00:17:09,400 --> 00:17:13,760 Speaker 1: idea it matched their face and the results were that 301 00:17:14,400 --> 00:17:20,280 Speaker 1: they if you can't produce a facial expression, then your 302 00:17:20,560 --> 00:17:25,800 Speaker 1: emotional experience is slightly lessened. Yeah, it's muted. So this 303 00:17:25,920 --> 00:17:30,120 Speaker 1: shows both ways facial expressions are somehow connected to emotion, 304 00:17:31,440 --> 00:17:35,040 Speaker 1: to producing emotion. The other study, which I like, talks 305 00:17:35,040 --> 00:17:39,640 Speaker 1: about fake smiling, like, uh, you know, turn that frown 306 00:17:39,680 --> 00:17:42,439 Speaker 1: upside down and you won't be so gloomy. Not true. 307 00:17:42,600 --> 00:17:47,400 Speaker 1: Fake smiling can actually make things worse. So Walmart greeters, 308 00:17:47,880 --> 00:17:51,159 Speaker 1: when you're being told the smile on your job, that 309 00:17:51,440 --> 00:17:54,679 Speaker 1: can actually bum you out more. And that's that's the reason. 310 00:17:54,840 --> 00:17:58,080 Speaker 1: Can't you just one intuitively, didn't you intuitively know this 311 00:17:58,160 --> 00:18:01,199 Speaker 1: already that that Porsche mom whose job it is a 312 00:18:01,280 --> 00:18:03,960 Speaker 1: smile at everybody is probably the one who like wants 313 00:18:04,000 --> 00:18:06,320 Speaker 1: to punch in the stomach most by the end of 314 00:18:06,320 --> 00:18:09,320 Speaker 1: the day. Sure, yeah, but it's just interesting because all 315 00:18:09,320 --> 00:18:11,639 Speaker 1: these other things say like a smile can actually increase 316 00:18:11,640 --> 00:18:14,359 Speaker 1: your emotion, but it's got to be a real smile. 317 00:18:15,080 --> 00:18:19,119 Speaker 1: A fake smile has the reverse effect. And they actually 318 00:18:19,160 --> 00:18:22,000 Speaker 1: did some research on this, Yeah, Michigan State two thousand 319 00:18:22,040 --> 00:18:25,879 Speaker 1: eleven study Spartans. It was in the Academy of Management Journal, 320 00:18:26,040 --> 00:18:29,760 Speaker 1: And basically this professor Um, he's a professor management. He 321 00:18:29,840 --> 00:18:33,000 Speaker 1: studied a group of bus drivers over two weeks and 322 00:18:33,080 --> 00:18:36,320 Speaker 1: found that the ones who fake smile the most had 323 00:18:36,400 --> 00:18:41,280 Speaker 1: more withdrawal and emotional exhaustion and had less hemorrhoids probably 324 00:18:41,840 --> 00:18:46,120 Speaker 1: um and but so basically that's surface acting fake smiling. 325 00:18:46,720 --> 00:18:49,639 Speaker 1: But he did find also that deep acting, which is 326 00:18:49,680 --> 00:18:54,400 Speaker 1: where you're like trying to cultivate a more positive outlook 327 00:18:54,440 --> 00:18:57,000 Speaker 1: inside yourself, like thinking of a really pleasant memory that 328 00:18:57,200 --> 00:19:00,320 Speaker 1: genuinely makes you happy, right you, you're doing that can 329 00:19:00,440 --> 00:19:04,400 Speaker 1: lead to actual more positive feelings, better performance at work. 330 00:19:04,400 --> 00:19:06,479 Speaker 1: Because again it's a management study, so that's what they 331 00:19:06,520 --> 00:19:11,000 Speaker 1: care about. But do you you actually do um experience 332 00:19:11,520 --> 00:19:14,760 Speaker 1: more better feelings. There's a positive effect rather than an 333 00:19:14,840 --> 00:19:19,600 Speaker 1: emotional withdrawal or waste that comes from fake smiling, Which 334 00:19:19,640 --> 00:19:21,600 Speaker 1: makes sense to me because I mean think about it, 335 00:19:21,640 --> 00:19:27,520 Speaker 1: like facial expressions are we've always assumed designed for another person. 336 00:19:27,640 --> 00:19:30,720 Speaker 1: This is how I'm feeling right now, respond accordingly, If 337 00:19:30,800 --> 00:19:34,560 Speaker 1: you are misleading everybody, you're you're going to at the 338 00:19:34,680 --> 00:19:37,720 Speaker 1: very least feel like you're not connected anyone because there's 339 00:19:37,720 --> 00:19:40,800 Speaker 1: no one who's understanding you. Yeah, they said it causes 340 00:19:40,800 --> 00:19:44,520 Speaker 1: feelings of in in authenticity, which makes sense. And they 341 00:19:44,520 --> 00:19:48,480 Speaker 1: also found that women, who are typically viewed as more 342 00:19:48,520 --> 00:19:51,760 Speaker 1: emotional than men, got in worse moods with the fake 343 00:19:51,800 --> 00:19:56,360 Speaker 1: smiling and reacted even more positively when they were deep 344 00:19:56,400 --> 00:19:58,960 Speaker 1: acting and really able to able to conjure up those 345 00:19:59,320 --> 00:20:04,600 Speaker 1: pleasant feelings puppies. Yeah, so men are just apes. Well. 346 00:20:04,880 --> 00:20:10,159 Speaker 1: Another study two thousand five minut University study found that 347 00:20:10,320 --> 00:20:14,280 Speaker 1: UM women are likelier to smile, what whether they feel 348 00:20:14,280 --> 00:20:17,639 Speaker 1: like smiling or not, in almost all social situations, compared 349 00:20:17,680 --> 00:20:22,280 Speaker 1: to man. So there that explains why women are often 350 00:20:22,280 --> 00:20:26,040 Speaker 1: emotionally exhausted. Yeah, my mom was much more inclined to 351 00:20:26,040 --> 00:20:28,199 Speaker 1: put on a happy face around other people than my 352 00:20:28,280 --> 00:20:31,720 Speaker 1: dad was. My dad would literally just like go off 353 00:20:31,720 --> 00:20:34,239 Speaker 1: by himself and sulk in front of everybody and just 354 00:20:34,280 --> 00:20:38,040 Speaker 1: be like here's me. But still in two thousand and eleven, 355 00:20:38,040 --> 00:20:40,879 Speaker 1: the point that we're at is um putting pens in 356 00:20:40,920 --> 00:20:44,399 Speaker 1: people's mouths and telling him to make e sounds in 357 00:20:44,440 --> 00:20:46,880 Speaker 1: our smile research. This is where we are. But at 358 00:20:46,880 --> 00:20:51,800 Speaker 1: the very least the findings are they're interesting and man, 359 00:20:52,119 --> 00:20:56,359 Speaker 1: it has been forever since we've done like a study fest. Yeah, 360 00:20:56,680 --> 00:21:00,400 Speaker 1: this feels like two thousand and eight, two thousand nine, crazy. Yeah, 361 00:21:00,480 --> 00:21:01,879 Speaker 1: you know we've been doing this for more than three 362 00:21:01,960 --> 00:21:07,160 Speaker 1: years now. Really that means uh Sarah our fan that 363 00:21:07,520 --> 00:21:11,040 Speaker 1: is she's like ninety, she wrote recently. I think she's fourteen? Now? 364 00:21:14,760 --> 00:21:17,159 Speaker 1: Is she fourteen? Now? Yes, she's she's on the Facebook 365 00:21:17,200 --> 00:21:21,080 Speaker 1: page now. No, I haven't keeps the darn button. Well 366 00:21:21,080 --> 00:21:23,800 Speaker 1: that's great. Well that's it for smiling. I'm done smiling 367 00:21:23,960 --> 00:21:26,560 Speaker 1: for the day. Yeah, I'm not. I don't feel like 368 00:21:26,600 --> 00:21:30,480 Speaker 1: being emotionally withdrawn and exhausted. Although our next podcast that 369 00:21:30,520 --> 00:21:34,200 Speaker 1: we're recording is pretty fun, it is, but that'll be 370 00:21:34,240 --> 00:21:37,080 Speaker 1: a genuine smile. Yes, okay, So Chuck, you got anything? 371 00:21:38,359 --> 00:21:42,040 Speaker 1: Uh no, Just to plug the fact that we're on 372 00:21:42,080 --> 00:21:44,520 Speaker 1: the radio now, you can listen to us on Friday 373 00:21:44,600 --> 00:21:46,240 Speaker 1: nights from seven eight if you're in the New York 374 00:21:46,280 --> 00:21:49,880 Speaker 1: area New Jersey area on WFMU ninety one point one. 375 00:21:49,960 --> 00:21:52,000 Speaker 1: As a matter of fact, we cover the whole Hudson 376 00:21:52,080 --> 00:21:55,760 Speaker 1: Valley like a wet blanket that's been left out in 377 00:21:55,800 --> 00:21:59,159 Speaker 1: the street for a couple of days. Hudson Valley. You 378 00:21:59,200 --> 00:22:01,600 Speaker 1: can find us it in dy point one Friday's from 379 00:22:01,600 --> 00:22:06,000 Speaker 1: seven eight and big thanks to Ken Friedman. Yeah, huge thanks. 380 00:22:06,080 --> 00:22:08,480 Speaker 1: Ken Friedman is like he should wear a cape. Yeah 381 00:22:08,720 --> 00:22:11,399 Speaker 1: he might, he probably does. But I Ken is a 382 00:22:11,600 --> 00:22:14,560 Speaker 1: w FM you and he's like everyone we've talked to 383 00:22:14,720 --> 00:22:17,640 Speaker 1: in public radio, because we've talked to other folks, has said, boy, 384 00:22:17,720 --> 00:22:21,240 Speaker 1: Ken is like one of these stand up guys. So 385 00:22:21,240 --> 00:22:24,360 Speaker 1: so thanks Ken, And if you're listening to this right 386 00:22:24,400 --> 00:22:29,280 Speaker 1: now on WFMU, we'll bet you appreciate Ken yourself. Yeah 387 00:22:29,320 --> 00:22:33,399 Speaker 1: they um, okay, So what do you want to do? Listener? 388 00:22:33,400 --> 00:22:36,000 Speaker 1: Mail now? Oh, if you want to know more about 389 00:22:36,040 --> 00:22:39,240 Speaker 1: smiling and happiness, type happy in to the search bar 390 00:22:39,640 --> 00:22:43,399 Speaker 1: at our beloved venerable website How Stuff Works dot com, 391 00:22:43,440 --> 00:22:46,000 Speaker 1: and it's gonna bring up a ton of stuff. There 392 00:22:46,040 --> 00:22:48,880 Speaker 1: was so much happiness stuff that we wrote like last year, 393 00:22:49,000 --> 00:22:53,280 Speaker 1: what people love studying emotion? Yeah, yes they do. That's 394 00:22:53,320 --> 00:22:56,919 Speaker 1: psychologists that that's just that's their thing. It certainly is 395 00:22:57,040 --> 00:22:59,159 Speaker 1: let's make people cry and then ask him about it. 396 00:23:00,560 --> 00:23:02,680 Speaker 1: Let's make people to shock people in the face. We 397 00:23:02,800 --> 00:23:06,760 Speaker 1: got to get that happiness audiobook released. Is it still relevant? 398 00:23:07,359 --> 00:23:10,920 Speaker 1: Sure it is, okay, it was ever greenest timeless classic. Anyway, 399 00:23:10,920 --> 00:23:13,439 Speaker 1: I said how stuff works in handy search bar. So 400 00:23:13,880 --> 00:23:19,919 Speaker 1: listener mail, should we go with the underground railroad or 401 00:23:20,240 --> 00:23:27,440 Speaker 1: um fear orgasms? I think fear orgaism. I got permission 402 00:23:27,480 --> 00:23:29,000 Speaker 1: to read this, by the way, as I do all 403 00:23:29,040 --> 00:23:31,600 Speaker 1: of them. Hi, guys, love the podcast. Thanks for making 404 00:23:31,640 --> 00:23:34,880 Speaker 1: me learn and laugh. I swear the following story is true, 405 00:23:34,880 --> 00:23:37,560 Speaker 1: bizarre but true. So I'm listening to the Fear podcast 406 00:23:37,600 --> 00:23:40,399 Speaker 1: at the gym today, and you gave an example of 407 00:23:40,440 --> 00:23:43,520 Speaker 1: men asking women out after experiencing fear because they feel 408 00:23:43,560 --> 00:23:46,720 Speaker 1: invisible or sexual. And Josh said something like, if you've 409 00:23:46,720 --> 00:23:48,520 Speaker 1: ever had a strange reaction to fear, let us know 410 00:23:48,760 --> 00:23:54,840 Speaker 1: invincible invisible. I think she made invincible maybe. So last 411 00:23:54,880 --> 00:23:57,280 Speaker 1: month I had a truly bizarre experience related to fear. 412 00:23:57,359 --> 00:23:59,159 Speaker 1: My boss was out of town. You put me in 413 00:23:59,200 --> 00:24:01,439 Speaker 1: charge of a webinar he had planned to do, and 414 00:24:01,480 --> 00:24:04,000 Speaker 1: I've moderated them before, but this was the first time 415 00:24:04,000 --> 00:24:06,280 Speaker 1: I had to make sure all the mechanics worked. Correctly. 416 00:24:07,320 --> 00:24:10,040 Speaker 1: About fifty people were expected to join. I'd practiced thoroughly, 417 00:24:10,520 --> 00:24:12,040 Speaker 1: going through it a few times to make sure I 418 00:24:12,040 --> 00:24:14,760 Speaker 1: had it down. When the day came to do the webinar, 419 00:24:14,840 --> 00:24:17,920 Speaker 1: I loaded it up two hours beforehand to make sure 420 00:24:17,920 --> 00:24:20,960 Speaker 1: it was already and it did not work correctly. I 421 00:24:21,040 --> 00:24:23,159 Speaker 1: read through my notes and tried again. I could not 422 00:24:23,280 --> 00:24:26,320 Speaker 1: get the slides up and started to panic. I can't 423 00:24:26,359 --> 00:24:28,120 Speaker 1: get the phone lines to work. All of a sudden, 424 00:24:28,320 --> 00:24:30,920 Speaker 1: I try again and again, and I am panicking. Now 425 00:24:31,280 --> 00:24:33,480 Speaker 1: I call the client to let them know my difficulties. 426 00:24:33,920 --> 00:24:37,400 Speaker 1: At this point, I am really panicked. It's been two hours. 427 00:24:37,560 --> 00:24:40,920 Speaker 1: Folks sending me text while they can't connect sending emails. 428 00:24:41,040 --> 00:24:44,240 Speaker 1: I like the build up here. It's just like especially coming. 429 00:24:46,359 --> 00:24:48,159 Speaker 1: Two phone lines went down, no way to reach the 430 00:24:48,200 --> 00:24:50,280 Speaker 1: software support line, and fifty people waiting for me to 431 00:24:50,280 --> 00:24:52,680 Speaker 1: connect them to the webinar that is supposed to start 432 00:24:52,760 --> 00:24:55,960 Speaker 1: right now. I'm shaking with anxiety. And guess what my 433 00:24:56,040 --> 00:25:03,360 Speaker 1: body does. I have an intense orgasm, and then another one. 434 00:25:03,520 --> 00:25:08,320 Speaker 1: She doubled down. Well, I'm thinking my body was trying 435 00:25:08,320 --> 00:25:10,240 Speaker 1: to get rid of extra energy so I could focus, 436 00:25:10,640 --> 00:25:13,280 Speaker 1: which kind of makes sense. Maybe or it's just like 437 00:25:13,480 --> 00:25:18,840 Speaker 1: enough of this, right, let's party. Who knows? It was 438 00:25:18,880 --> 00:25:22,359 Speaker 1: so unexpected that I almost started laughing. And no, I 439 00:25:22,400 --> 00:25:27,280 Speaker 1: have not told many people about this. I'm not sure 440 00:25:24,760 --> 00:25:29,840 Speaker 1: how you can share it if you find it of interest, 441 00:25:30,640 --> 00:25:34,520 Speaker 1: but please only use my first name. And Julie I 442 00:25:34,800 --> 00:25:37,639 Speaker 1: wrote her back and said, yeah, I really would like 443 00:25:37,680 --> 00:25:40,040 Speaker 1: to read this, and by the way, good for you, 444 00:25:40,880 --> 00:25:46,359 Speaker 1: and she said, yeah, right now, she like goes into 445 00:25:46,400 --> 00:25:51,360 Speaker 1: a bear dens and she hang glides and does all 446 00:25:51,400 --> 00:25:55,720 Speaker 1: sorts of crazy stuff. All that exactly crazy, Julie beckon 447 00:25:55,800 --> 00:25:57,840 Speaker 1: with by the way, I just made up that last name. 448 00:25:57,920 --> 00:26:01,480 Speaker 1: And literally she didn't send her last name. Man, So 449 00:26:01,600 --> 00:26:05,440 Speaker 1: for all those years that you know, I was stumbling 450 00:26:05,480 --> 00:26:07,840 Speaker 1: around in the dark not knowing what the heck was 451 00:26:07,880 --> 00:26:13,880 Speaker 1: going on, I should have just like none at a webinar. Okay, 452 00:26:16,280 --> 00:26:21,240 Speaker 1: so I don't even know what to call for now. Um, 453 00:26:21,359 --> 00:26:24,320 Speaker 1: let's see if you have ever encountered a bear, let 454 00:26:24,359 --> 00:26:27,600 Speaker 1: us know. Sorry, yeah, we don't get too many outdoors 455 00:26:27,640 --> 00:26:30,520 Speaker 1: and emails these days. How about that you've ever encountered 456 00:26:30,520 --> 00:26:33,879 Speaker 1: a bear? Tell us about it? And uh, you can 457 00:26:34,520 --> 00:26:38,080 Speaker 1: tweet to us right s y s K podcast, which 458 00:26:38,119 --> 00:26:39,760 Speaker 1: by the way, I should tell you we have a 459 00:26:39,760 --> 00:26:43,760 Speaker 1: little campaign going that started last night a guy named 460 00:26:43,840 --> 00:26:47,920 Speaker 1: OMG Chris. That's his Twitter handle OMG C h R 461 00:26:48,040 --> 00:26:52,320 Speaker 1: I S S S. Right, Okay, he had he asked 462 00:26:52,359 --> 00:26:54,680 Speaker 1: us to take a vacation because he wanted to catch up, 463 00:26:54,720 --> 00:26:57,200 Speaker 1: and I tweeted that, like many other people have caught 464 00:26:57,320 --> 00:27:00,880 Speaker 1: up and succeeded, you know you need to so um 465 00:27:00,920 --> 00:27:03,600 Speaker 1: I asked all of our fans and followers on Twitter 466 00:27:04,040 --> 00:27:06,199 Speaker 1: to let Chris know that he can do it. And 467 00:27:06,240 --> 00:27:09,240 Speaker 1: there's a hashtag now, it's pound Chris can do it, 468 00:27:10,000 --> 00:27:12,680 Speaker 1: And all these people send him these words of encouragement 469 00:27:12,760 --> 00:27:15,040 Speaker 1: and tips and on how to catch up. Some people 470 00:27:15,040 --> 00:27:17,080 Speaker 1: listen to us at one point five or two times 471 00:27:17,640 --> 00:27:20,320 Speaker 1: and they say, your your laugh is very funny. Twice 472 00:27:20,320 --> 00:27:21,879 Speaker 1: the speed. Yeah, We've gotten a lot of people that 473 00:27:21,920 --> 00:27:24,919 Speaker 1: said they do that. So if you want to encourage Chris, 474 00:27:24,960 --> 00:27:27,639 Speaker 1: I've been retweeting a lot of words of encouragement. But 475 00:27:27,800 --> 00:27:31,520 Speaker 1: you can send him a tweet and c c us 476 00:27:31,600 --> 00:27:33,800 Speaker 1: on it, and then make sure you use the hashtag 477 00:27:34,400 --> 00:27:38,680 Speaker 1: pound Chris can do it? All right, R S S S. 478 00:27:38,840 --> 00:27:40,960 Speaker 1: You know it's just h C H R I S 479 00:27:41,040 --> 00:27:44,360 Speaker 1: can do it. Good, good thinking. Awesome um. And then 480 00:27:44,400 --> 00:27:47,560 Speaker 1: also we were on Facebook, Facebook dot com slash stuff 481 00:27:47,560 --> 00:27:50,280 Speaker 1: You should know and you can send us your bare 482 00:27:50,400 --> 00:28:00,960 Speaker 1: stories at Stuff Podcast at how stuff works dot com. 483 00:28:01,000 --> 00:28:03,560 Speaker 1: Be sure to check out our new video podcast, Stuff 484 00:28:03,600 --> 00:28:06,639 Speaker 1: from the Future. Join how staffork staff as we explore 485 00:28:06,680 --> 00:28:12,840 Speaker 1: the most promising and perplexing possibilities of tomorrow, brought to 486 00:28:12,880 --> 00:28:16,000 Speaker 1: you by the reinvented two thousand twelve camera. It's ready, 487 00:28:16,160 --> 00:28:16,560 Speaker 1: are you