1 00:00:03,080 --> 00:00:05,960 Speaker 1: Welcome to Stuff to Blow your Mind from how Stuff 2 00:00:05,960 --> 00:00:13,760 Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:13,760 --> 00:00:16,320 Speaker 1: My name is Robert Lamb and my name is Julie 4 00:00:16,520 --> 00:00:21,200 Speaker 1: Henry Doug Bliss. Really that's really your middle name. But 5 00:00:21,239 --> 00:00:24,599 Speaker 1: if I could choose a guy's name, I think it 6 00:00:24,640 --> 00:00:28,440 Speaker 1: would be Henry. Henry. Good solid name to me, Henry, 7 00:00:28,760 --> 00:00:31,600 Speaker 1: I guess. Yeah, it's kind of ordinary. But that's it's 8 00:00:31,600 --> 00:00:34,239 Speaker 1: the thing about names. So often they're ordinary, and then 9 00:00:34,280 --> 00:00:36,920 Speaker 1: what happens when they're a little different Henry James. And 10 00:00:36,920 --> 00:00:40,840 Speaker 1: it's all about associations, right, That is good? That is good. Yeah, 11 00:00:40,880 --> 00:00:44,519 Speaker 1: there are so many associations with names. There's family history. 12 00:00:45,200 --> 00:00:48,159 Speaker 1: Names are both so simple and too simple and then 13 00:00:48,200 --> 00:00:51,200 Speaker 1: just overly complicated the more you look at it. And 14 00:00:51,560 --> 00:00:55,120 Speaker 1: could they possibly be so freighted with meaning that they 15 00:00:55,200 --> 00:00:58,600 Speaker 1: come to actually form who we are? Yeah, that's the thing. 16 00:00:58,760 --> 00:01:01,360 Speaker 1: The name that you're given is the name the secret 17 00:01:01,480 --> 00:01:05,120 Speaker 1: ruler of your life? Did that determine everything in your 18 00:01:05,200 --> 00:01:08,479 Speaker 1: life from the cradle to the grave, all because your 19 00:01:09,080 --> 00:01:11,319 Speaker 1: your your mother and father decided to name you. Say 20 00:01:11,880 --> 00:01:14,720 Speaker 1: say Sue, I was about to say. Johnt Cash had 21 00:01:14,720 --> 00:01:18,960 Speaker 1: an idea about this long before researchers started to say 22 00:01:18,959 --> 00:01:22,119 Speaker 1: what are the cognitive effects of naming children? Or rather, 23 00:01:22,160 --> 00:01:25,279 Speaker 1: Shell Silverstein did, oh yeah, yeah, he wrote the lyrics 24 00:01:25,319 --> 00:01:27,480 Speaker 1: to that song, or rather that was his poem that 25 00:01:27,600 --> 00:01:30,000 Speaker 1: became the Johnny Cash song. I did not know that. 26 00:01:30,000 --> 00:01:33,280 Speaker 1: That makes it even better, Shall I go for it? Yeah? 27 00:01:33,480 --> 00:01:35,800 Speaker 1: My daughter left home one hours three and he didn't 28 00:01:35,880 --> 00:01:38,479 Speaker 1: leave much to moll and me, just this old guitar 29 00:01:38,600 --> 00:01:41,600 Speaker 1: and empty pol labooze. Now, I don't blame him close 30 00:01:41,720 --> 00:01:44,920 Speaker 1: he running hit. But the meanest thing he ever did 31 00:01:45,120 --> 00:01:48,040 Speaker 1: was before he left, he went and named miss Sue. 32 00:01:48,720 --> 00:01:50,960 Speaker 1: And then, of course the song goes on and on 33 00:01:51,040 --> 00:01:54,520 Speaker 1: to detail his life as a boy named Sue. It's 34 00:01:54,520 --> 00:01:57,640 Speaker 1: a rough life, it's a hard life. But eventually he 35 00:01:57,680 --> 00:02:00,520 Speaker 1: confronts his father. He says, yeah, he's pretty much like 36 00:02:00,520 --> 00:02:02,320 Speaker 1: why did you do that? And his dad's like, well, 37 00:02:02,400 --> 00:02:04,520 Speaker 1: I know it's a rough life, and I thought you 38 00:02:04,560 --> 00:02:06,440 Speaker 1: had to be tough, so of course I named you 39 00:02:06,520 --> 00:02:09,040 Speaker 1: sous that you'd have like a banackbone. And that's how 40 00:02:09,120 --> 00:02:10,960 Speaker 1: much I love you, because I knew I wasn't gonna 41 00:02:11,000 --> 00:02:13,880 Speaker 1: be there. Yeah, he's saying, I essentially put a target 42 00:02:14,000 --> 00:02:17,000 Speaker 1: on your head. Because I knew that either everyone around 43 00:02:17,040 --> 00:02:19,880 Speaker 1: you would destroy you or and what did you know 44 00:02:20,160 --> 00:02:22,960 Speaker 1: his Nieji says, what doesn't destroy me makes me stronger. 45 00:02:23,000 --> 00:02:26,240 Speaker 1: So um, that was the whole, the whole idea here, 46 00:02:26,600 --> 00:02:29,839 Speaker 1: that's what Shell Silverstein was going for a little Niegi. Yeah. Yeah, 47 00:02:29,880 --> 00:02:31,799 Speaker 1: and I can't help. But I mean we've both been 48 00:02:31,800 --> 00:02:34,320 Speaker 1: through the naming process for a child at this point. 49 00:02:34,919 --> 00:02:40,240 Speaker 1: Did you have any names that you ended up rejecting? Um, well, yeah, 50 00:02:40,360 --> 00:02:43,240 Speaker 1: but but obviously I liked them, they were on my list, 51 00:02:43,919 --> 00:02:46,600 Speaker 1: you know. But um, but my grandmother used to to 52 00:02:46,960 --> 00:02:48,760 Speaker 1: ask every day like what are you gonna name or 53 00:02:48,800 --> 00:02:50,040 Speaker 1: what are you gonna name her? And I would just 54 00:02:50,040 --> 00:02:53,639 Speaker 1: come up with ridiculous names to annoy her. Garlic sorbet 55 00:02:55,240 --> 00:03:02,400 Speaker 1: toad stool ivory nice, a period person a person you. 56 00:03:02,720 --> 00:03:05,720 Speaker 1: Oh yeah, I had a short list of Sagan okay, 57 00:03:05,800 --> 00:03:11,440 Speaker 1: that was a strong contender, a tray um Zevon, Shoehorn, Quantis, 58 00:03:12,280 --> 00:03:15,639 Speaker 1: ny are leptap yasav Off. But they got just going 59 00:03:15,680 --> 00:03:20,400 Speaker 1: with Sebastian instead, which is great. I love that name. Um. 60 00:03:20,440 --> 00:03:22,919 Speaker 1: But yeah, this is just becomes a really important thing, 61 00:03:22,960 --> 00:03:25,760 Speaker 1: that's naming of the child, and in fact it's so 62 00:03:25,800 --> 00:03:29,160 Speaker 1: important that you know, people published tons of books about it, 63 00:03:29,240 --> 00:03:32,120 Speaker 1: like name giving Advice, and there was even a two 64 00:03:32,160 --> 00:03:34,800 Speaker 1: thousand and ten British study of three thousand parents that 65 00:03:34,880 --> 00:03:37,760 Speaker 1: revealed that one in five parents regret the name that 66 00:03:37,800 --> 00:03:40,840 Speaker 1: they chose for their child. So it would make sense 67 00:03:40,880 --> 00:03:44,720 Speaker 1: that a parenting website like I don't know baby Center 68 00:03:44,840 --> 00:03:49,000 Speaker 1: would be so um well visited by parents to see 69 00:03:49,040 --> 00:03:52,120 Speaker 1: what are the most popular names for boys and girls. 70 00:03:52,720 --> 00:03:55,560 Speaker 1: But also they put out information like what are the 71 00:03:55,600 --> 00:03:58,080 Speaker 1: weirdest names? And in two thousand and thirteen they have 72 00:03:58,160 --> 00:04:01,880 Speaker 1: some real hunting urs. Yeah. Um, there were at least 73 00:04:01,960 --> 00:04:06,840 Speaker 1: three baby boys named Cheese yes, which which is nice. Um. 74 00:04:06,920 --> 00:04:09,640 Speaker 1: I believe there was a character on the wire named Cheese. Yeah, 75 00:04:09,680 --> 00:04:11,360 Speaker 1: there was. I have to point out at this point 76 00:04:11,360 --> 00:04:14,000 Speaker 1: there was also a child named Danish, and I was 77 00:04:14,080 --> 00:04:17,599 Speaker 1: really hoping that, like, yeah, that they were twins like 78 00:04:17,680 --> 00:04:19,560 Speaker 1: Cheese in Danish, but I don't think that was the case, 79 00:04:21,160 --> 00:04:26,520 Speaker 1: Little Cheese. Uh. And then some of the other names Panda, yeah, Rocket, 80 00:04:26,960 --> 00:04:29,480 Speaker 1: which is you know, you want an explosive child, it's 81 00:04:29,520 --> 00:04:31,159 Speaker 1: just gonna get out there in the world. I have 82 00:04:31,160 --> 00:04:33,800 Speaker 1: a rocket in my neighborhood. He's great. Yeah, and when 83 00:04:33,839 --> 00:04:36,560 Speaker 1: in doubt, you know, in terms of coming with a 84 00:04:36,640 --> 00:04:39,640 Speaker 1: name for your child, just name them after a primordial 85 00:04:40,200 --> 00:04:45,120 Speaker 1: sea monster that that that rise in the prehistoric darkness 86 00:04:45,320 --> 00:04:49,280 Speaker 1: and h and rivals the might of an ancient Hebrew deity. 87 00:04:49,480 --> 00:04:52,520 Speaker 1: I just name your kid Leviathan, which somebody did. I mean, 88 00:04:52,560 --> 00:04:56,800 Speaker 1: there's there's no weight there, There's there's there's nothing there 89 00:04:56,839 --> 00:04:58,840 Speaker 1: that would make that job feel sort of bogged down 90 00:04:58,880 --> 00:05:02,719 Speaker 1: to the phil his or her destiny. Um, there's also 91 00:05:03,080 --> 00:05:06,440 Speaker 1: Drago and bullet. So all of this kind of whirligig 92 00:05:06,560 --> 00:05:09,679 Speaker 1: naming here made us wonder how does this play out 93 00:05:10,080 --> 00:05:15,240 Speaker 1: in something called nominative determinism. Yeah, this is basically the 94 00:05:15,279 --> 00:05:18,640 Speaker 1: idea that we're talking about here, except with science behind it. 95 00:05:18,839 --> 00:05:21,640 Speaker 1: The idea that any name, yeah name, the name that 96 00:05:21,680 --> 00:05:25,039 Speaker 1: we're given determines who we are, how we behave, and 97 00:05:25,040 --> 00:05:26,880 Speaker 1: how the world's gonna treat us, how the world's gonna 98 00:05:26,920 --> 00:05:30,920 Speaker 1: perceive us. That it really gets down into the complexity 99 00:05:30,920 --> 00:05:35,000 Speaker 1: of language, right. We we end up acquiring language, building language, 100 00:05:35,120 --> 00:05:37,719 Speaker 1: using languages, an operating system for the human brain, and 101 00:05:37,760 --> 00:05:39,680 Speaker 1: the system that we based all of our culture on. 102 00:05:40,160 --> 00:05:44,120 Speaker 1: And what I was really struck with in researching this topic. 103 00:05:44,320 --> 00:05:47,839 Speaker 1: Is that UM is that nominative determinism is kind of 104 00:05:48,520 --> 00:05:50,760 Speaker 1: it's almost like a mistake in the programming or a 105 00:05:50,839 --> 00:05:53,680 Speaker 1: side effect of the programming that the name that you 106 00:05:53,800 --> 00:05:58,240 Speaker 1: give an individual carries a lot of obvious weight. You know, 107 00:05:58,279 --> 00:06:01,680 Speaker 1: if you name your your kid after a mythological hero, 108 00:06:01,839 --> 00:06:04,760 Speaker 1: you're obviously drawing upon that you can call your kid 109 00:06:04,800 --> 00:06:09,080 Speaker 1: thor is a certain thoroughness um that you're you're dragging 110 00:06:09,080 --> 00:06:10,719 Speaker 1: in there. But then there's a lot of stuff that's 111 00:06:10,760 --> 00:06:13,359 Speaker 1: happening at a subconscious level. It's just uh, you know, 112 00:06:13,440 --> 00:06:17,000 Speaker 1: tendrils reaching out through the canvas of language, as do 113 00:06:17,000 --> 00:06:20,800 Speaker 1: you mean, like the symbol wasn't necessarily meant to be internalized, 114 00:06:21,160 --> 00:06:23,359 Speaker 1: but it's so easy for our brains to make that 115 00:06:23,400 --> 00:06:26,480 Speaker 1: little walk over there. And we talked about this kind 116 00:06:26,480 --> 00:06:29,080 Speaker 1: of in the last episode, about how if you have 117 00:06:29,279 --> 00:06:33,760 Speaker 1: a limb that's next to your limb, and you begin 118 00:06:33,839 --> 00:06:36,200 Speaker 1: to see it from your first person perspective, then you 119 00:06:36,240 --> 00:06:37,880 Speaker 1: sort of adopt that limb as your own, and all 120 00:06:37,880 --> 00:06:40,440 Speaker 1: of a sudden you have three limbs. Um And we 121 00:06:40,480 --> 00:06:42,440 Speaker 1: won't go into that, but the point is is that 122 00:06:42,480 --> 00:06:45,360 Speaker 1: it's really easy to sort of take these things on 123 00:06:45,520 --> 00:06:49,919 Speaker 1: as yourself, and that is at the heart of nominative determinism. 124 00:06:49,960 --> 00:06:52,159 Speaker 1: And I wanted to read this little bit from a 125 00:06:52,200 --> 00:06:57,480 Speaker 1: Mental Plus article on the topic. Quote Dr rich Dick 126 00:06:57,640 --> 00:07:01,159 Speaker 1: chop Is in Austin, you're erologist. He was known for 127 00:07:01,200 --> 00:07:05,080 Speaker 1: performing best ectomies. Really other doctors at the same urology 128 00:07:05,160 --> 00:07:10,560 Speaker 1: clinic include Dr Hardeman and Dr Wang. Is this coincidence? 129 00:07:11,000 --> 00:07:14,560 Speaker 1: Probably um, but there may be something there. That's that's 130 00:07:14,560 --> 00:07:17,200 Speaker 1: why we're discussing it obviously. Well, in my experience, I 131 00:07:17,280 --> 00:07:19,600 Speaker 1: am My father was a dentist, so I've always from 132 00:07:19,600 --> 00:07:22,320 Speaker 1: a very little kid, I would always noticed the signs 133 00:07:22,320 --> 00:07:25,280 Speaker 1: for dentist offices anywhere we went. And even then I 134 00:07:25,320 --> 00:07:28,440 Speaker 1: remember thinking, there are a lot of dentists who have 135 00:07:28,600 --> 00:07:31,480 Speaker 1: the last name Pain P A y. And even why, like, 136 00:07:31,480 --> 00:07:33,200 Speaker 1: wouldn't you want to change that? Do you really want 137 00:07:33,200 --> 00:07:35,080 Speaker 1: to be Dr? Pain when people go to get their 138 00:07:35,080 --> 00:07:37,720 Speaker 1: teeth worked on? And I did a quick Google search 139 00:07:37,880 --> 00:07:40,200 Speaker 1: before we came to the podcast Camber and and just 140 00:07:40,320 --> 00:07:43,960 Speaker 1: page after page of of of dentist named Pain, and 141 00:07:44,000 --> 00:07:46,640 Speaker 1: it it makes you think again, are they are they 142 00:07:46,720 --> 00:07:51,440 Speaker 1: drawn to dentistry somehow subconsciously because of that name or 143 00:07:51,560 --> 00:07:54,640 Speaker 1: and then why maybe not change it if you're going 144 00:07:54,680 --> 00:07:56,720 Speaker 1: to make a go out of business, because you wouldn't 145 00:07:56,920 --> 00:07:59,000 Speaker 1: you wouldn't hesitate to change the name of the business 146 00:07:59,080 --> 00:08:03,520 Speaker 1: off if the business name were somehow a counterpoint to 147 00:08:03,600 --> 00:08:05,720 Speaker 1: what you're trying to the experience that you're trying to 148 00:08:05,760 --> 00:08:08,520 Speaker 1: sell to the customer. So so it seems like you 149 00:08:08,520 --> 00:08:10,200 Speaker 1: would you would want to do that with your your 150 00:08:10,200 --> 00:08:12,680 Speaker 1: professional name as well. I don't know, I'm about to 151 00:08:12,680 --> 00:08:14,480 Speaker 1: tell you something that I think might end up in 152 00:08:14,520 --> 00:08:19,400 Speaker 1: an awkward silence moment. Uh my gas Row anthrologist. His 153 00:08:19,520 --> 00:08:24,520 Speaker 1: name is doctor Sunshine, And I'm not kidding. Yeah, So 154 00:08:24,520 --> 00:08:26,560 Speaker 1: I think on that a moment, And then let's sort 155 00:08:26,560 --> 00:08:28,960 Speaker 1: of switch gears here back to a boy named Sue, 156 00:08:29,080 --> 00:08:34,839 Speaker 1: because apparently if you're a boy named Ashley or Shannon Um, 157 00:08:34,880 --> 00:08:37,040 Speaker 1: there are some things that will be needed out to 158 00:08:37,120 --> 00:08:40,880 Speaker 1: you because of having that name. In fact, research psychologist 159 00:08:40,960 --> 00:08:45,400 Speaker 1: David Figlio of Northwestern University in Illinois looked at millions 160 00:08:45,400 --> 00:08:48,280 Speaker 1: of birth certificates and then he broke them down by 161 00:08:48,400 --> 00:08:51,520 Speaker 1: phonemics and behavior, and he found a bunch of different things, 162 00:08:51,600 --> 00:08:55,680 Speaker 1: not just about Ashley and Shannon Um, but in terms 163 00:08:55,679 --> 00:08:58,160 Speaker 1: of those names. He did to find that the boys 164 00:08:58,400 --> 00:09:01,720 Speaker 1: with names traditionally given to girls are more likely to 165 00:09:02,080 --> 00:09:07,400 Speaker 1: misbehave than their counterparts with masculine names, which is interesting 166 00:09:07,400 --> 00:09:10,120 Speaker 1: because it lines up with the song. Right, boy named 167 00:09:10,120 --> 00:09:12,200 Speaker 1: Sue winds up getting a lot of fights as an 168 00:09:12,240 --> 00:09:15,559 Speaker 1: embattled life that makes him tougher. Uh, they found it 169 00:09:15,640 --> 00:09:17,840 Speaker 1: up into a certain age. I think it was like 170 00:09:17,880 --> 00:09:20,960 Speaker 1: age six. I think sixth grade. Sixth grade rather up. 171 00:09:21,000 --> 00:09:22,880 Speaker 1: Unto a certain point, it didn't really make any difference. 172 00:09:23,160 --> 00:09:27,080 Speaker 1: But then sixth grade hits and and so that's when 173 00:09:27,120 --> 00:09:31,000 Speaker 1: the embattlement begins to really take hold. Suddenly, these these 174 00:09:31,280 --> 00:09:35,680 Speaker 1: male individuals with feminine names are misbehaving and acting out 175 00:09:35,720 --> 00:09:39,080 Speaker 1: all the time. Yeah, gender norms are in full force, right, 176 00:09:39,160 --> 00:09:41,920 Speaker 1: and so you have kids who are are really trying 177 00:09:41,960 --> 00:09:47,320 Speaker 1: to reinforce that idea and to make things worse. And 178 00:09:47,360 --> 00:09:49,720 Speaker 1: I think this will be obvious if there happened to 179 00:09:49,760 --> 00:09:52,360 Speaker 1: be a girl with the name of Shannon or Ashley 180 00:09:52,400 --> 00:09:56,200 Speaker 1: in the same class as that boy, exactly, because there 181 00:09:56,240 --> 00:10:00,520 Speaker 1: you have confirmation that you have a feminine because that 182 00:10:00,600 --> 00:10:03,079 Speaker 1: kid is right there with it. Now. As a side note, 183 00:10:03,080 --> 00:10:08,080 Speaker 1: I wondered to what extent this phenomenon might disappear as 184 00:10:08,880 --> 00:10:13,960 Speaker 1: hopefully culture becomes increasingly sensitive to the the idea of 185 00:10:14,000 --> 00:10:17,000 Speaker 1: gender and that gender is not an issue of one 186 00:10:17,040 --> 00:10:20,000 Speaker 1: fortress and another fortress. Or does that even trickle down 187 00:10:20,040 --> 00:10:22,440 Speaker 1: to kids or kids always going to be boys versus girls. 188 00:10:22,840 --> 00:10:25,560 Speaker 1: I think it takes a while, because I try with 189 00:10:25,880 --> 00:10:28,560 Speaker 1: my own daughter to try to live in a not 190 00:10:28,679 --> 00:10:31,000 Speaker 1: a gender free world, but to not make that as 191 00:10:31,280 --> 00:10:35,400 Speaker 1: as the starting point for for conversations or decisions. But 192 00:10:35,440 --> 00:10:39,840 Speaker 1: I do see her teachers maybe unconsciously putting that dynamic 193 00:10:40,080 --> 00:10:43,240 Speaker 1: in play and really talking a lot about boys and 194 00:10:43,320 --> 00:10:47,679 Speaker 1: girls and the girls are lovely, and the boys are handsome, 195 00:10:47,960 --> 00:10:50,240 Speaker 1: and the girls are well behaved, and that so on 196 00:10:50,320 --> 00:10:53,400 Speaker 1: and so forth, and spice and everything nice exactly. Yeah, 197 00:10:53,640 --> 00:10:56,480 Speaker 1: And and to that point, Um, I didn't want to 198 00:10:56,480 --> 00:11:01,160 Speaker 1: point out that David Biglio found that girls with names 199 00:11:01,200 --> 00:11:04,479 Speaker 1: that are relatively feminine in high school choose advanced coursework 200 00:11:04,520 --> 00:11:08,880 Speaker 1: and humanities and less feminine names, Um they are given 201 00:11:08,920 --> 00:11:11,560 Speaker 1: to girls, those girls are more likely to choose math 202 00:11:11,600 --> 00:11:15,839 Speaker 1: and science courses. Interesting. So here's an idea, and one 203 00:11:15,920 --> 00:11:19,960 Speaker 1: that I am really having trouble by, the idea that 204 00:11:20,080 --> 00:11:24,360 Speaker 1: a name could not only determine how the society will 205 00:11:24,440 --> 00:11:26,640 Speaker 1: view you and how your view your own place in society. 206 00:11:26,640 --> 00:11:30,280 Speaker 1: But could a name actually make you more prone to 207 00:11:30,360 --> 00:11:33,960 Speaker 1: disease or make you more unhealthy? Mm? I know you're 208 00:11:34,000 --> 00:11:36,760 Speaker 1: talking about You're talking about the Brady Bunch study that 209 00:11:36,840 --> 00:11:38,199 Speaker 1: they called the Brake I don't think they call it 210 00:11:38,240 --> 00:11:40,200 Speaker 1: a pretty much study. But it was a study about 211 00:11:40,240 --> 00:11:43,840 Speaker 1: people with a surname of Brady. This is in Doublin 212 00:11:43,960 --> 00:11:47,480 Speaker 1: right researchers in Dublin. They wanted to discover whether or 213 00:11:47,520 --> 00:11:50,640 Speaker 1: not a person's name might influence their health, and so 214 00:11:50,720 --> 00:11:53,080 Speaker 1: they looked at whether people with his surname Brady had 215 00:11:53,080 --> 00:11:56,280 Speaker 1: a higher incidence of Brady cardia that is a slow 216 00:11:56,520 --> 00:11:59,000 Speaker 1: heart rate. How did they get funding for this? This 217 00:11:59,320 --> 00:12:02,079 Speaker 1: just sounds in aimed to me, where someone and as 218 00:12:02,080 --> 00:12:04,720 Speaker 1: we'll see, the research is really fat. I mean they 219 00:12:04,880 --> 00:12:07,480 Speaker 1: find it's really fascinating. But who said I wonder if 220 00:12:07,480 --> 00:12:09,920 Speaker 1: people with the name Brady are more likely to suffer 221 00:12:09,920 --> 00:12:14,720 Speaker 1: from Brady Brady cardia. Like it's almost to propose that question, 222 00:12:14,760 --> 00:12:18,000 Speaker 1: you have to feel like the answer might be yes. Yeah. 223 00:12:18,080 --> 00:12:20,880 Speaker 1: I also kind of wondered to what degree were people 224 00:12:20,920 --> 00:12:25,000 Speaker 1: familiar with the term Brady cardia and knew about it 225 00:12:25,000 --> 00:12:27,199 Speaker 1: and maybe internalized it because that's the idea, right. Yeah, 226 00:12:27,240 --> 00:12:29,000 Speaker 1: I was not familiar with the term, so it didn't 227 00:12:29,040 --> 00:12:33,119 Speaker 1: play into my view of the Brady punch. YEA. Researchers 228 00:12:33,200 --> 00:12:35,520 Speaker 1: used data from a hospital database and the percentage of 229 00:12:35,559 --> 00:12:39,679 Speaker 1: the population of surname Brady, of course, and they determined 230 00:12:39,720 --> 00:12:43,480 Speaker 1: through use of online telephone listenings in Dublin between two 231 00:12:43,520 --> 00:12:46,199 Speaker 1: thousand and seven and two thousand and thirteen that they 232 00:12:46,240 --> 00:12:49,360 Speaker 1: were something like five dred seventy nine Bradies listed in 233 00:12:49,440 --> 00:12:54,040 Speaker 1: total and one thousand and twelve pacemakers fitted during this time, 234 00:12:55,400 --> 00:12:59,640 Speaker 1: and the median age of the patients seventy seven years old, 235 00:13:00,440 --> 00:13:05,040 Speaker 1: and the proportion of pacemaker recipients among Brady's one point 236 00:13:05,240 --> 00:13:13,400 Speaker 1: three was significantly higher than among non Brady's point six one. Okay, 237 00:13:13,440 --> 00:13:15,520 Speaker 1: so there's something there. It's not huge. I mean, we're 238 00:13:15,559 --> 00:13:18,400 Speaker 1: not saying, well, what a huge this. This completely says 239 00:13:18,440 --> 00:13:21,199 Speaker 1: that this is going on, right. It's like a number 240 00:13:21,200 --> 00:13:22,920 Speaker 1: of the things that we're talking about here, a number 241 00:13:22,920 --> 00:13:26,600 Speaker 1: of the examples rather on an individual basis, you're just 242 00:13:26,720 --> 00:13:29,000 Speaker 1: looking around at the people, you know it, there's a 243 00:13:29,000 --> 00:13:31,120 Speaker 1: good chance it's not going to line up. But when 244 00:13:31,120 --> 00:13:35,160 Speaker 1: you look at larger population groups and larger sample groups, 245 00:13:35,240 --> 00:13:38,320 Speaker 1: that's where you begin to see these interesting statistics to uh, 246 00:13:38,520 --> 00:13:41,480 Speaker 1: you know emerging. Yeah, and they did say in the study, hey, 247 00:13:41,520 --> 00:13:44,280 Speaker 1: there are limitations to this. We don't know that the 248 00:13:44,720 --> 00:13:47,600 Speaker 1: patient's background. We don't know if they were related and 249 00:13:47,640 --> 00:13:50,960 Speaker 1: they had genetic predispositions, and this could have skewed results. 250 00:13:51,320 --> 00:13:53,720 Speaker 1: We also don't know whether or not because this is 251 00:13:53,760 --> 00:13:57,920 Speaker 1: a city center for um, this procedure that drew more 252 00:13:58,640 --> 00:14:03,960 Speaker 1: bradyes and so that kind skew the results as well. So, um, 253 00:14:04,160 --> 00:14:05,760 Speaker 1: you know, it's just kind of an interesting thing that's 254 00:14:05,760 --> 00:14:09,120 Speaker 1: put out there. You know, you begin to wonder, should 255 00:14:09,120 --> 00:14:10,839 Speaker 1: I name Mike, you know, just be on the safe side, 256 00:14:10,880 --> 00:14:13,760 Speaker 1: I'll just go ahead and name my kid Methuselah or 257 00:14:14,720 --> 00:14:16,600 Speaker 1: you know, just to ensure that they have a long life. 258 00:14:16,600 --> 00:14:18,480 Speaker 1: But then, in my tempting fate, what happens when a 259 00:14:18,559 --> 00:14:21,520 Speaker 1: kid named Methusela dies at age fifty? Then you're gonna 260 00:14:21,560 --> 00:14:24,680 Speaker 1: feel really like I did that by giving him this 261 00:14:24,800 --> 00:14:27,720 Speaker 1: name and trying to force the universe to make them 262 00:14:27,760 --> 00:14:29,800 Speaker 1: live a really long time. I think it's okay. I 263 00:14:29,800 --> 00:14:32,880 Speaker 1: think that sometimes kids will buck against their names. And um, 264 00:14:33,000 --> 00:14:36,560 Speaker 1: this was actually in one of the articles that we read. Um, 265 00:14:36,600 --> 00:14:38,040 Speaker 1: I'll have to look at it in a moment and 266 00:14:38,040 --> 00:14:41,200 Speaker 1: bring up the title. But the article was saying that 267 00:14:41,240 --> 00:14:44,800 Speaker 1: there was a father who named his kid loser lane 268 00:14:45,840 --> 00:14:47,800 Speaker 1: and then purpose or was this one of those incidents 269 00:14:47,800 --> 00:14:50,840 Speaker 1: where they thought it would be pronounced differently? Well you 270 00:14:50,920 --> 00:14:55,200 Speaker 1: decided after tell you the next kid's name, Winner Lane. Okay, 271 00:14:55,720 --> 00:14:58,640 Speaker 1: Loser ends up to be like an upstanding citizen. I 272 00:14:58,640 --> 00:15:00,640 Speaker 1: don't think he's a cop or something, but I mean 273 00:15:00,680 --> 00:15:04,160 Speaker 1: he's done well for himself. Winner turns out to be 274 00:15:04,400 --> 00:15:08,360 Speaker 1: like in the Pokey all the time. His crime written 275 00:15:08,840 --> 00:15:11,200 Speaker 1: What kind of father was this is? I'm just imagining 276 00:15:11,280 --> 00:15:13,520 Speaker 1: it means it was like a B. F. Skinner type 277 00:15:13,560 --> 00:15:16,040 Speaker 1: of ploy here. Well, did you hear about the sociologist 278 00:15:16,080 --> 00:15:20,080 Speaker 1: who wrote Parentology. He named his children their first names, 279 00:15:20,760 --> 00:15:24,320 Speaker 1: his daughter's e and then his other son or his 280 00:15:24,440 --> 00:15:28,560 Speaker 1: son is yo, and then beyond like the first names, 281 00:15:28,560 --> 00:15:31,720 Speaker 1: they have a million other names tacked onto it. And 282 00:15:31,760 --> 00:15:35,600 Speaker 1: then they are not of Asian descent, But he decided 283 00:15:35,680 --> 00:15:39,440 Speaker 1: to throw in some Asian names in there, just to 284 00:15:39,560 --> 00:15:43,920 Speaker 1: kind of throw off the paradigm. He says of immigrants 285 00:15:44,040 --> 00:15:50,880 Speaker 1: taking on um that country's name messed with the paradigm 286 00:15:50,960 --> 00:15:54,400 Speaker 1: there um. Anyway, there was an interview with his kids, 287 00:15:54,400 --> 00:15:55,960 Speaker 1: and his kids are like, yeah, we're fine with it, 288 00:15:56,160 --> 00:16:02,080 Speaker 1: but yes, sometimes they're sociologists who unleash some experiments at home. Yeah, now, 289 00:16:02,080 --> 00:16:04,240 Speaker 1: of course there's well this is we'll discuss this some 290 00:16:04,280 --> 00:16:06,000 Speaker 1: more as well. But of course any name you give 291 00:16:06,080 --> 00:16:08,360 Speaker 1: somebody who does not exist in a vacuum, there are 292 00:16:08,480 --> 00:16:11,880 Speaker 1: plenty of other factors at play. We're gonna take a break, 293 00:16:11,880 --> 00:16:20,520 Speaker 1: and when we come back, this will come directly into play. 294 00:16:22,080 --> 00:16:24,000 Speaker 1: All Right, we're back. We're going to talk a little 295 00:16:24,000 --> 00:16:26,240 Speaker 1: bit about fre Economics, because this is a book if 296 00:16:26,280 --> 00:16:28,440 Speaker 1: you're not familiar with it, that sort of takes this 297 00:16:28,640 --> 00:16:32,520 Speaker 1: um socio economic view of things that we don't normally 298 00:16:32,560 --> 00:16:35,640 Speaker 1: apply that sort of lens to and tries to figure 299 00:16:35,680 --> 00:16:39,240 Speaker 1: out if there's some sort of algorithm that is driving 300 00:16:39,240 --> 00:16:41,360 Speaker 1: our behavior and the things that we do. And of 301 00:16:41,400 --> 00:16:45,200 Speaker 1: course naming came up in Fre Economics, um Steve Levitt, 302 00:16:45,360 --> 00:16:48,800 Speaker 1: the author of Economics and Harvard Economics Roland G. Friar. 303 00:16:48,920 --> 00:16:51,320 Speaker 1: They wanted to see if the trend of black parents 304 00:16:51,400 --> 00:16:55,280 Speaker 1: naming their children distinctly non white names. They wanted to 305 00:16:55,280 --> 00:16:58,040 Speaker 1: see if this had an impact on those kids later 306 00:16:58,120 --> 00:17:02,280 Speaker 1: on socially and comically. Yeah. So what Friar did is 307 00:17:02,280 --> 00:17:05,040 Speaker 1: he looked at birth certificate information for every child born 308 00:17:05,080 --> 00:17:08,679 Speaker 1: in California since nineteen sixty one and uh and what 309 00:17:08,800 --> 00:17:11,960 Speaker 1: he found uh initially matches up pretty well with with 310 00:17:12,160 --> 00:17:16,400 Speaker 1: I think everyone's experience of names. Up until the early seventies, 311 00:17:16,440 --> 00:17:19,440 Speaker 1: there was a more overlap in white black names. But 312 00:17:19,520 --> 00:17:22,880 Speaker 1: then by nineteen eighty you see an explosion of distinctly 313 00:17:23,040 --> 00:17:25,880 Speaker 1: black names. Uh. And some of the fuel for this, 314 00:17:26,200 --> 00:17:28,760 Speaker 1: uh you can find in the Black power movement and 315 00:17:29,200 --> 00:17:34,040 Speaker 1: the push to accentuate African culture and African roots and uh. 316 00:17:34,080 --> 00:17:37,280 Speaker 1: And so you see this this divide. So suddenly you 317 00:17:37,359 --> 00:17:41,080 Speaker 1: see more distinctly black names, increasing number of distinctly black 318 00:17:41,160 --> 00:17:43,720 Speaker 1: names in the black community. So Friar found that the 319 00:17:44,119 --> 00:17:47,359 Speaker 1: data showed that on average, person with a distinctly black 320 00:17:47,440 --> 00:17:50,520 Speaker 1: name had a worse life outcome than an individual with 321 00:17:50,600 --> 00:17:53,720 Speaker 1: a more common name. Now, it's important to note, and 322 00:17:54,000 --> 00:17:56,560 Speaker 1: the authors of economic note that it's not the fault 323 00:17:56,600 --> 00:18:00,159 Speaker 1: of their names. Okay, it has to do with the 324 00:18:00,240 --> 00:18:03,280 Speaker 1: parents who select a particular sort of name. So again, 325 00:18:03,320 --> 00:18:05,880 Speaker 1: like I said earlier, names don't exist in a vacuum. 326 00:18:06,320 --> 00:18:09,800 Speaker 1: Names are coming from parents. And so you see trends 327 00:18:09,800 --> 00:18:13,879 Speaker 1: where certain names are more likely to be bestowed by 328 00:18:14,000 --> 00:18:19,320 Speaker 1: members of various levels of the socio economic scale. And 329 00:18:19,320 --> 00:18:22,120 Speaker 1: and and this this is in the data that they discussing. 330 00:18:22,119 --> 00:18:25,520 Speaker 1: Fre economics concerns more than just the white black divide, 331 00:18:25,520 --> 00:18:28,960 Speaker 1: but also uh, the economic divide. What names are more 332 00:18:29,040 --> 00:18:33,880 Speaker 1: common among lower income households versus higher income households. So 333 00:18:33,920 --> 00:18:37,919 Speaker 1: we already know that there are unconscious associations. There's just 334 00:18:37,960 --> 00:18:40,560 Speaker 1: all sorts of biases here. Yeah, not not to mean 335 00:18:40,640 --> 00:18:44,119 Speaker 1: not to count out just overt bias and racism exactly. Yeah, 336 00:18:44,440 --> 00:18:48,280 Speaker 1: so this is really interesting. Um Latonia Russell, Harvard Professor 337 00:18:48,320 --> 00:18:52,879 Speaker 1: of Government Technology. She published a study about search results 338 00:18:52,880 --> 00:18:58,280 Speaker 1: in Google related to name searches and racial profiling in 339 00:18:58,280 --> 00:19:01,440 Speaker 1: in the ad works for Good Well. And she did 340 00:19:01,480 --> 00:19:04,440 Speaker 1: this after a search for her name served up an 341 00:19:04,440 --> 00:19:07,080 Speaker 1: AD next to her name with find an arrest record 342 00:19:07,520 --> 00:19:11,840 Speaker 1: and it was actually a colleague of hers um who 343 00:19:12,200 --> 00:19:15,240 Speaker 1: was not black, who they were searching something about some 344 00:19:15,320 --> 00:19:17,840 Speaker 1: of the work that they were doing and student in 345 00:19:17,840 --> 00:19:19,760 Speaker 1: the search they were of course looking for their names 346 00:19:19,760 --> 00:19:21,560 Speaker 1: to see how that would come up, and he was 347 00:19:21,600 --> 00:19:24,640 Speaker 1: the first person to tag like, oh, that's weird. Mine 348 00:19:24,680 --> 00:19:27,760 Speaker 1: doesn't come up with this arrest record ad over here, 349 00:19:27,760 --> 00:19:30,320 Speaker 1: but yours does. And so he started to do a 350 00:19:30,320 --> 00:19:32,520 Speaker 1: couple of different searches and came up with the idea 351 00:19:32,560 --> 00:19:35,399 Speaker 1: of I think it's kind of tied to black sounding names, 352 00:19:35,840 --> 00:19:37,600 Speaker 1: and she was appalled. She said, no, no no, no, no, 353 00:19:38,480 --> 00:19:40,879 Speaker 1: I'm a scientist here. I'm going to conduct a formal 354 00:19:41,520 --> 00:19:44,399 Speaker 1: um study of this, and I'm going to prove you wrong, 355 00:19:44,520 --> 00:19:46,520 Speaker 1: because she didn't want to believe that that was actually 356 00:19:46,560 --> 00:19:49,560 Speaker 1: like regional profiling was happening in the ad words. And 357 00:19:49,720 --> 00:19:54,720 Speaker 1: she found that a black identified name was twenty more 358 00:19:54,800 --> 00:19:56,960 Speaker 1: likely than a white identified name to get an add 359 00:19:57,359 --> 00:20:02,080 Speaker 1: suggestive of an arrest record, huh, which is troublesome because 360 00:20:02,200 --> 00:20:04,280 Speaker 1: you see that and it does have this sort of 361 00:20:04,320 --> 00:20:07,080 Speaker 1: association of like, well, perhaps this person does have an 362 00:20:07,160 --> 00:20:10,440 Speaker 1: arrest record, right, and then that's just more fire to 363 00:20:10,560 --> 00:20:12,840 Speaker 1: just sort of the subliminal messaging that's coming at you 364 00:20:13,240 --> 00:20:16,120 Speaker 1: through your your search engine, through one of the ways 365 00:20:16,119 --> 00:20:18,920 Speaker 1: that you're interacting with the world, and so at least 366 00:20:19,119 --> 00:20:22,520 Speaker 1: subliminally your search engine is saying, hey, you're the type 367 00:20:22,520 --> 00:20:24,760 Speaker 1: of person who might be arrested, and then you're going 368 00:20:24,800 --> 00:20:27,720 Speaker 1: to absorb that information and have to deal with And 369 00:20:27,760 --> 00:20:30,960 Speaker 1: as David Eagleman might say, the problem with us is 370 00:20:30,960 --> 00:20:35,120 Speaker 1: that all of this is happening under the cover of unconscious. 371 00:20:35,280 --> 00:20:38,600 Speaker 1: Right You're unconscious is meeting all of this out and 372 00:20:38,680 --> 00:20:43,359 Speaker 1: serving it up to your conscious as this idea, and 373 00:20:43,400 --> 00:20:45,439 Speaker 1: you don't even know what's going on. And he calls 374 00:20:45,480 --> 00:20:50,720 Speaker 1: this implicit bias. This implicit bias is within us. We're 375 00:20:50,760 --> 00:20:54,000 Speaker 1: not aware of it. It's it's acting um sort of 376 00:20:54,040 --> 00:20:57,840 Speaker 1: independently to our consciousness. And he said that this is 377 00:20:57,880 --> 00:21:02,800 Speaker 1: borne out in reaction time and hesitations during computer models 378 00:21:02,800 --> 00:21:06,960 Speaker 1: that allow us to like or dislike images or words 379 00:21:07,000 --> 00:21:09,679 Speaker 1: to show how we're driven by our unconscious and he 380 00:21:09,720 --> 00:21:12,119 Speaker 1: gives a couple of examples of this, but the one 381 00:21:12,160 --> 00:21:14,639 Speaker 1: that I like best is um this one that begins 382 00:21:14,640 --> 00:21:18,359 Speaker 1: with a screen that has like and dislike at the 383 00:21:18,400 --> 00:21:21,600 Speaker 1: top of the screen, and then in the middle there 384 00:21:21,800 --> 00:21:24,840 Speaker 1: is a name that appears. So he says, like you 385 00:21:24,840 --> 00:21:27,240 Speaker 1: could have the name of a religion appearing in the middle, 386 00:21:27,760 --> 00:21:30,200 Speaker 1: And he said, what's interesting about this is not just 387 00:21:30,280 --> 00:21:34,919 Speaker 1: the speed of the participants selecting like or dislike, but 388 00:21:35,160 --> 00:21:39,520 Speaker 1: that this program actually tracks the trajectory of the mouse 389 00:21:39,680 --> 00:21:43,679 Speaker 1: movements and it can show the drift. So it shows like, 390 00:21:43,720 --> 00:21:47,640 Speaker 1: maybe you're going toward no, and then you correct yourself 391 00:21:47,680 --> 00:21:51,320 Speaker 1: and go to um or not no, maybe you're going 392 00:21:51,400 --> 00:21:53,679 Speaker 1: towards dislike, and then you correct yourself and go toward 393 00:21:54,200 --> 00:21:57,520 Speaker 1: like UM. And he's saying that that is showing that 394 00:21:57,640 --> 00:22:03,439 Speaker 1: you're you're doing the more social appropriate response. Your conscious 395 00:22:03,600 --> 00:22:07,639 Speaker 1: is catching up to your unconscious and correcting it. So 396 00:22:07,720 --> 00:22:10,760 Speaker 1: he's saying that even people with certainty about their attitudes 397 00:22:10,800 --> 00:22:14,680 Speaker 1: and beliefs um, they can find themselves surprised and sometimes 398 00:22:14,760 --> 00:22:18,080 Speaker 1: appalled by what's lurking within their brains that they're not 399 00:22:18,119 --> 00:22:21,000 Speaker 1: even aware of. So it's it's like the gut reaction 400 00:22:21,160 --> 00:22:25,320 Speaker 1: versus the actual conscious thought reaction. Sort of if someone 401 00:22:25,320 --> 00:22:28,399 Speaker 1: were to say, offer someone a beer for lunch at work, 402 00:22:28,840 --> 00:22:31,080 Speaker 1: their gut instinct might be might be to say yes, 403 00:22:31,080 --> 00:22:33,240 Speaker 1: I would like a beer, and then they're they're conscious 404 00:22:33,240 --> 00:22:35,840 Speaker 1: reaction might be no, I don't drink beer at work, 405 00:22:35,960 --> 00:22:38,200 Speaker 1: or no, I don't drink beer at all. Why would 406 00:22:38,240 --> 00:22:40,760 Speaker 1: I even entertain the idea? But for that split second 407 00:22:40,760 --> 00:22:43,000 Speaker 1: you do yeah, your hand might start to reach out 408 00:22:43,119 --> 00:22:45,880 Speaker 1: and you're like, oh no, no no, no thanks yeah. Um. 409 00:22:46,000 --> 00:22:49,320 Speaker 1: So that gets us into this idea of implicit association, 410 00:22:49,560 --> 00:22:54,240 Speaker 1: because that's where we get into this idea of unconscious commonality. So, 411 00:22:55,400 --> 00:22:57,000 Speaker 1: you know, here's a good example that I think we've 412 00:22:57,000 --> 00:22:59,879 Speaker 1: talked about before. If your name is Dennis or Dinny, 413 00:23:00,480 --> 00:23:02,800 Speaker 1: there's some data out there, and Eagleman talks about this 414 00:23:02,840 --> 00:23:06,400 Speaker 1: in his book that you perhaps could become a dentist. 415 00:23:07,200 --> 00:23:11,239 Speaker 1: You're internalizing this association between the way that your your 416 00:23:11,320 --> 00:23:14,520 Speaker 1: name sounds in this profession. Yeah, people Denise or Dennis 417 00:23:14,560 --> 00:23:18,320 Speaker 1: more are disproportionately more likely to become dentist, Laura Lawrence 418 00:23:18,440 --> 00:23:22,760 Speaker 1: more likely to become a lawyer, George or Georgiana more 419 00:23:22,840 --> 00:23:25,959 Speaker 1: likely to become a geologist. Uh. And it's it's interesting. 420 00:23:26,119 --> 00:23:29,280 Speaker 1: My my birth name is of course Padrick, so that 421 00:23:29,400 --> 00:23:31,560 Speaker 1: and that is why I became a podcaster. I guess, 422 00:23:31,960 --> 00:23:36,080 Speaker 1: ha ha ha, very nice, Um, Padrick. You know what 423 00:23:36,240 --> 00:23:38,560 Speaker 1: that Nay show up in is like one of the 424 00:23:38,560 --> 00:23:41,080 Speaker 1: most popular baby names really just because of the Game 425 00:23:41,119 --> 00:23:45,120 Speaker 1: of Thrones. Now we're just thinking because of the Profession podcast, 426 00:23:45,359 --> 00:23:47,480 Speaker 1: because everybody will be everybody wants their kid to be 427 00:23:47,520 --> 00:23:51,880 Speaker 1: a podcaster because that's where the money is, alright. So 428 00:23:51,960 --> 00:23:56,000 Speaker 1: another layer of this is something called implicit ego. And 429 00:23:56,080 --> 00:23:58,719 Speaker 1: so that's that not just that unconscious connection that you 430 00:23:58,720 --> 00:24:01,240 Speaker 1: have like oh someone is like me or that's like me, 431 00:24:01,440 --> 00:24:05,159 Speaker 1: but actually feeling like, you know, like your ego is 432 00:24:05,240 --> 00:24:08,879 Speaker 1: bound up in this idea of that thing or that person. 433 00:24:09,160 --> 00:24:10,760 Speaker 1: And we do a lot of this. We've talked about 434 00:24:10,760 --> 00:24:12,840 Speaker 1: this before, when we attach our ego to something. It 435 00:24:12,920 --> 00:24:16,000 Speaker 1: might be a sports team, yea, or or it might 436 00:24:16,040 --> 00:24:18,480 Speaker 1: just be uh, it might be an individual, it might 437 00:24:18,520 --> 00:24:20,480 Speaker 1: be a cup of tea. All right. So here's a 438 00:24:20,560 --> 00:24:23,960 Speaker 1: nice example. Eagleman says that when students read an essay 439 00:24:24,280 --> 00:24:27,879 Speaker 1: by Resputant in this example, uh, they also read a 440 00:24:27,920 --> 00:24:33,000 Speaker 1: bit of biographical detail about Resputing, including his birthday, which 441 00:24:33,160 --> 00:24:35,320 Speaker 1: by the way, was manipulated in the text to be 442 00:24:35,359 --> 00:24:38,840 Speaker 1: the same as the readers. So when they read that 443 00:24:39,000 --> 00:24:43,720 Speaker 1: and that little the little data bit, that student gave 444 00:24:44,280 --> 00:24:48,439 Speaker 1: Resputing a more generous rating. Yeah, that's really interesting. It's 445 00:24:48,480 --> 00:24:51,720 Speaker 1: just just the mere insertion of that date given it 446 00:24:51,760 --> 00:24:54,280 Speaker 1: gives you the subconscious link with this individual, and so 447 00:24:54,359 --> 00:24:57,760 Speaker 1: you feel like a little more than usual, like Gregory 448 00:24:57,800 --> 00:25:00,520 Speaker 1: Resputant is, uh, he's like you, He's is one of me. 449 00:25:00,640 --> 00:25:04,359 Speaker 1: I I I agree with everything he did to some extent. Yeah, 450 00:25:04,359 --> 00:25:07,359 Speaker 1: and then on another level, it's like, yeah, go January seven, 451 00:25:08,040 --> 00:25:09,960 Speaker 1: the team January seven, all of us who were born 452 00:25:09,960 --> 00:25:13,080 Speaker 1: into there, your your winner. Oh man. I actually experienced 453 00:25:13,080 --> 00:25:15,600 Speaker 1: this quiet a lot when I'm taking the train to work, 454 00:25:15,640 --> 00:25:17,600 Speaker 1: because I take the westbound train and then I take 455 00:25:17,600 --> 00:25:19,280 Speaker 1: the North Brown train. When I'm waiting on the North 456 00:25:19,280 --> 00:25:22,639 Speaker 1: Brown trained air to northbound trains, one is the Doorville train, 457 00:25:23,119 --> 00:25:26,320 Speaker 1: one is the North Springs Only the North Springs train 458 00:25:26,440 --> 00:25:28,479 Speaker 1: actually will get me all the way to work. And 459 00:25:28,520 --> 00:25:32,399 Speaker 1: so I'll find myself, uh, standing there the Doorville train arrives, 460 00:25:32,440 --> 00:25:34,879 Speaker 1: the wrong train arrives, and people are getting on board, 461 00:25:34,920 --> 00:25:38,520 Speaker 1: and I'll actually think to myself, all those Doorville train people, 462 00:25:38,520 --> 00:25:42,239 Speaker 1: they're the worst, just judging on the hardcore, even though 463 00:25:42,280 --> 00:25:44,320 Speaker 1: there's there's like one. And then I asked me, why 464 00:25:44,320 --> 00:25:46,480 Speaker 1: am I doing that? Why am I attaching my ego 465 00:25:46,560 --> 00:25:49,760 Speaker 1: to the to the North Springs train and judging everyone 466 00:25:49,800 --> 00:25:54,000 Speaker 1: who rides the Doorville train. Star Billy Sneeches my friend exactly. 467 00:25:54,119 --> 00:25:57,720 Speaker 1: Dr SEUs shows up again in the podcast, so you know, 468 00:25:58,200 --> 00:26:01,639 Speaker 1: you also have priming going on too. Some of it's unconscious, 469 00:26:01,680 --> 00:26:03,880 Speaker 1: some of it's not so unconscious. I was thinking about 470 00:26:03,920 --> 00:26:07,240 Speaker 1: Alison louder Milk because she shared with me that she 471 00:26:07,480 --> 00:26:10,520 Speaker 1: this is actually implicit ego and priming. She shared with 472 00:26:10,560 --> 00:26:15,640 Speaker 1: me that she buys Almond milk because she really enjoys 473 00:26:16,080 --> 00:26:18,720 Speaker 1: the layout, the graphic layout of Almond milk, and it 474 00:26:18,840 --> 00:26:23,080 Speaker 1: also kind of reminds her of her name, Alison louder 475 00:26:23,119 --> 00:26:26,480 Speaker 1: Milk Almond Milk. Interesting. That was because this is another 476 00:26:26,760 --> 00:26:29,520 Speaker 1: study that David Equlman brings up where they they had 477 00:26:30,400 --> 00:26:34,800 Speaker 1: consumers test subjects um consider different brands of fictional teas, 478 00:26:35,280 --> 00:26:37,960 Speaker 1: and they were more likely to go with the fictional 479 00:26:38,000 --> 00:26:41,320 Speaker 1: tea that contained the first three letters of their first name. So, 480 00:26:41,440 --> 00:26:43,920 Speaker 1: I mean, this is why, of course I like Robina 481 00:26:43,960 --> 00:26:47,720 Speaker 1: tea and you like Juilliard Tea. Yes, I love Juilliard Tea. 482 00:26:47,840 --> 00:26:51,200 Speaker 1: Yeah no, I don't think they're all their real tees. 483 00:26:51,440 --> 00:26:53,399 Speaker 1: But but but the idea is that we would be 484 00:26:53,480 --> 00:26:56,800 Speaker 1: drawn to those brands in theory because they contain bits 485 00:26:56,800 --> 00:26:58,800 Speaker 1: of our name and in a sense are a bit 486 00:26:58,840 --> 00:27:01,760 Speaker 1: of us. Gosh, don't you just feel like such a 487 00:27:01,800 --> 00:27:05,320 Speaker 1: simple ton. Sometimes that's the kind of stuff that gives 488 00:27:05,320 --> 00:27:09,359 Speaker 1: you like sometimes like a glorious being in the universe 489 00:27:09,640 --> 00:27:12,520 Speaker 1: taking in all the wonderments of life. And then sometimes 490 00:27:12,520 --> 00:27:15,520 Speaker 1: you're like cash, we're just such simpletons, just you know, 491 00:27:16,160 --> 00:27:19,560 Speaker 1: being manipulated left and right. Were not even knowing it. Well, 492 00:27:19,600 --> 00:27:21,840 Speaker 1: because so much of our experience of the world, understanding 493 00:27:21,840 --> 00:27:23,919 Speaker 1: of in our culture is based in language, and again 494 00:27:24,000 --> 00:27:27,120 Speaker 1: this kind of these kind of free associations, it's it's 495 00:27:27,200 --> 00:27:29,359 Speaker 1: kind of a flaw in the system. You're just kind 496 00:27:29,400 --> 00:27:34,120 Speaker 1: of a side effect of this system being in place. Well, 497 00:27:34,119 --> 00:27:36,400 Speaker 1: I will tell you, um, having done the research on this, 498 00:27:36,720 --> 00:27:39,680 Speaker 1: I have decided that if I do have another child, 499 00:27:39,960 --> 00:27:44,000 Speaker 1: I know the exact perfect name to give that child. 500 00:27:44,119 --> 00:27:50,280 Speaker 1: Oh let's hear it. Okay, nominative determinism okay, or in 501 00:27:50,440 --> 00:27:55,440 Speaker 1: D yeah yeah, or your namdi yeah, nam D. That's 502 00:27:55,440 --> 00:27:58,600 Speaker 1: a pretty good one. Pretty good. Yeah. I mean, don't 503 00:27:58,600 --> 00:28:00,840 Speaker 1: you think like that they'd have to explain that name 504 00:28:00,880 --> 00:28:03,919 Speaker 1: over and over again, and they'd be super aware of 505 00:28:04,080 --> 00:28:07,720 Speaker 1: everything they did, everything that they perceived, and they would 506 00:28:07,720 --> 00:28:11,080 Speaker 1: just be really over analytical and perhaps even in a 507 00:28:11,160 --> 00:28:13,840 Speaker 1: fetal position as a result, And that idea to change 508 00:28:13,840 --> 00:28:17,920 Speaker 1: it eventially too, because didn't Moon the unit Zappa. Did 509 00:28:17,960 --> 00:28:21,000 Speaker 1: she change it? Seems like I thought she might have changed. 510 00:28:21,119 --> 00:28:23,560 Speaker 1: Maybe she just goes by Moon. Maybe I don't know. 511 00:28:23,600 --> 00:28:25,080 Speaker 1: I feel like, if you're a Zappa kid, you just 512 00:28:25,200 --> 00:28:27,440 Speaker 1: roll with it. Probably, But I have her tales of 513 00:28:27,880 --> 00:28:31,560 Speaker 1: children with sort of hippie dream child names changing them 514 00:28:31,560 --> 00:28:35,240 Speaker 1: to more socially normal acceptable names, because again that comes 515 00:28:35,240 --> 00:28:37,520 Speaker 1: back to just the whole idea of the name is 516 00:28:37,520 --> 00:28:40,360 Speaker 1: so weird, because like, I have a really normal name, 517 00:28:40,480 --> 00:28:43,480 Speaker 1: Robert Lamb. There's nothing phenomenal about it except that the 518 00:28:43,560 --> 00:28:46,160 Speaker 1: last name inspires the image of an animal and forces 519 00:28:46,400 --> 00:28:49,760 Speaker 1: children to make buying noises actually throughout school. But for 520 00:28:49,800 --> 00:28:51,320 Speaker 1: the most part, it's a normal name. So I've never 521 00:28:51,320 --> 00:28:54,840 Speaker 1: really felt a particular attachment to it. I've never hated it, 522 00:28:54,920 --> 00:28:56,160 Speaker 1: but I'm just kind of like, oh, I guess I'm 523 00:28:56,240 --> 00:28:58,960 Speaker 1: Robert Lamb. But so it made me want to give 524 00:28:59,040 --> 00:29:01,720 Speaker 1: my son a name that really stood out and was amazing. 525 00:29:02,520 --> 00:29:05,040 Speaker 1: But then, as we've discussed here, that's not necessarily the 526 00:29:05,080 --> 00:29:07,560 Speaker 1: way to go well, and that's what some of this, uh, 527 00:29:07,680 --> 00:29:09,719 Speaker 1: some of the articles that we read sort of touched on. 528 00:29:09,840 --> 00:29:13,360 Speaker 1: When you look at a name. Essentially, it is it 529 00:29:13,440 --> 00:29:15,760 Speaker 1: is sort of all the hopes and fears that a 530 00:29:15,920 --> 00:29:19,720 Speaker 1: parent puts into that name for the child. So it 531 00:29:19,800 --> 00:29:22,000 Speaker 1: kind of makes sense that, you know, people would name 532 00:29:22,200 --> 00:29:26,240 Speaker 1: their children, uh more normal names if they really thought 533 00:29:26,280 --> 00:29:29,480 Speaker 1: that was important that you assimilate to society, or a 534 00:29:29,760 --> 00:29:33,240 Speaker 1: unique name, if they really thought that individualism was very important. 535 00:29:33,920 --> 00:29:36,080 Speaker 1: So you can kind of see all of that at plane. 536 00:29:36,080 --> 00:29:38,480 Speaker 1: It's fascinating. Yeah, and I guess that's where middle names 537 00:29:38,480 --> 00:29:40,280 Speaker 1: are nice. You can throw a little something in there 538 00:29:41,000 --> 00:29:44,280 Speaker 1: so that they can eventually choose. Do they want to 539 00:29:44,280 --> 00:29:45,560 Speaker 1: go by the first name, they want to go by 540 00:29:45,600 --> 00:29:47,400 Speaker 1: the middle name, do they want to go with initials? 541 00:29:47,800 --> 00:29:50,160 Speaker 1: Give them some this is my take on the matter. Anyway, 542 00:29:50,200 --> 00:29:53,320 Speaker 1: give them some options so that they can change their 543 00:29:53,320 --> 00:29:56,280 Speaker 1: identity around in a way that that suits their needs 544 00:29:56,280 --> 00:29:58,520 Speaker 1: at the time. Because inevitably, children are going to go 545 00:29:58,520 --> 00:30:01,520 Speaker 1: through periods where they're going to really want to assimilate, 546 00:30:01,600 --> 00:30:05,200 Speaker 1: where assimilation is part of their genetic mission to blend 547 00:30:05,240 --> 00:30:09,080 Speaker 1: in so that they can actually survive long enough to breed. Uh. 548 00:30:09,280 --> 00:30:10,520 Speaker 1: But then on the other hand, they're going to reach 549 00:30:10,560 --> 00:30:14,240 Speaker 1: a point inevitably or hopefully inevitably where they want to 550 00:30:14,240 --> 00:30:15,960 Speaker 1: stand out where they want to be their own person 551 00:30:16,000 --> 00:30:19,760 Speaker 1: and be unique. All right, So there you go a little, 552 00:30:19,920 --> 00:30:23,760 Speaker 1: a little insight into the naming process. All of you 553 00:30:23,840 --> 00:30:26,320 Speaker 1: have names, and if and if you don't have a name, 554 00:30:26,360 --> 00:30:30,200 Speaker 1: actually that's even more amazing. Is that even possible? Can 555 00:30:30,240 --> 00:30:33,000 Speaker 1: you not name? I don't think so to name somebody 556 00:30:33,720 --> 00:30:35,840 Speaker 1: just a blank, you know, just an absence of name 557 00:30:36,280 --> 00:30:39,440 Speaker 1: and that becomes the name whoa And how emotionally saddled 558 00:30:39,520 --> 00:30:42,000 Speaker 1: would you be with the absence of a being, of 559 00:30:42,040 --> 00:30:44,880 Speaker 1: a name of a sound. Right, I was about to 560 00:30:44,880 --> 00:30:46,280 Speaker 1: wrap that up with a being with a name with 561 00:30:46,320 --> 00:30:51,680 Speaker 1: a sound. But in round. So all of you have names, 562 00:30:52,280 --> 00:30:55,400 Speaker 1: A number of you have have engaged in the naming process. 563 00:30:55,680 --> 00:30:57,560 Speaker 1: So we'd love to hear from everyone. How have you 564 00:30:57,600 --> 00:30:59,680 Speaker 1: grown up with your name? How is it affected your 565 00:30:59,720 --> 00:31:01,720 Speaker 1: out come in life? What kind of thought did you 566 00:31:01,760 --> 00:31:05,720 Speaker 1: put into naming your child? If you happen to have 567 00:31:05,800 --> 00:31:07,880 Speaker 1: one of those, let us know. We would love to 568 00:31:07,920 --> 00:31:09,880 Speaker 1: hear from. You can find us in all the normal places. 569 00:31:10,600 --> 00:31:12,440 Speaker 1: The mothership is of course stuff to blow your mind 570 00:31:12,440 --> 00:31:14,400 Speaker 1: dot com. That is deep place to go for your 571 00:31:14,400 --> 00:31:17,040 Speaker 1: stuff to blow your mind fix you will find all 572 00:31:17,080 --> 00:31:20,040 Speaker 1: of the podcast episodes. You will find over a thousand 573 00:31:20,040 --> 00:31:22,719 Speaker 1: blog posts and counting. You will find videos. You will 574 00:31:22,760 --> 00:31:26,520 Speaker 1: find links out to our social media accounts such as Facebook, Twitter, Tumbler, 575 00:31:26,600 --> 00:31:30,200 Speaker 1: our YouTube account, Mind Stuff Show and Hey. If you 576 00:31:30,240 --> 00:31:32,320 Speaker 1: have name regret and you want to share with us 577 00:31:32,360 --> 00:31:34,960 Speaker 1: the name you wish you had been given, you can 578 00:31:35,120 --> 00:31:37,320 Speaker 1: do that. Um you can share any other stories you 579 00:31:37,320 --> 00:31:39,680 Speaker 1: have with us about names, so send us an email 580 00:31:39,720 --> 00:31:46,360 Speaker 1: at below The mind at Discovery dot com For more 581 00:31:46,400 --> 00:31:48,719 Speaker 1: on this and thousands of other topics, Does it How 582 00:31:48,760 --> 00:31:55,880 Speaker 1: stuff works dot com