1 00:00:00,840 --> 00:00:03,119 Speaker 1: Chloe, and welcome to Cool People Who Did Cool Stuff? 2 00:00:03,160 --> 00:00:07,360 Speaker 1: Your favorite podcast? That well, it's actually just your favorite podcast. UM. 3 00:00:07,400 --> 00:00:09,560 Speaker 1: I know you love all of your podcasts equally, but 4 00:00:09,800 --> 00:00:12,400 Speaker 1: basic you love this one a little bit more. I'm 5 00:00:12,400 --> 00:00:14,560 Speaker 1: your host, Margaret Kiljoy, and I'm ready to tell you 6 00:00:14,600 --> 00:00:17,920 Speaker 1: all about cool people. And one of those cool people 7 00:00:17,920 --> 00:00:19,880 Speaker 1: I'm going to tell you about is this week's guest, 8 00:00:19,920 --> 00:00:22,959 Speaker 1: Bridget Todd, who is a feminist and activist and the 9 00:00:23,000 --> 00:00:25,600 Speaker 1: host of the show There Are No Girls on the Internet, 10 00:00:25,720 --> 00:00:29,000 Speaker 1: which is also allowed to be your favorite podcast. How 11 00:00:29,000 --> 00:00:31,600 Speaker 1: are you doing, Bridget, I'm good. I'm so excited to 12 00:00:31,640 --> 00:00:36,040 Speaker 1: be here. And we've got Sophie on the call to Um, 13 00:00:36,080 --> 00:00:38,919 Speaker 1: how are you Sophie as our producer, How are you doing, Sophie? 14 00:00:39,560 --> 00:00:45,920 Speaker 1: I'm doing I'm doing, Margaret. That's all I got for you. Yeah. Okay, 15 00:00:46,520 --> 00:00:49,760 Speaker 1: So today I want to talk about computers and space, 16 00:00:50,720 --> 00:00:53,720 Speaker 1: and I'm gonna call this episode When Women Were Computers, 17 00:00:53,760 --> 00:00:56,520 Speaker 1: because we're going to talk about how computer used to 18 00:00:56,520 --> 00:01:00,200 Speaker 1: be a job description. But when I started looking into that, 19 00:01:00,280 --> 00:01:03,440 Speaker 1: I started turning up more and more weird ship. So, 20 00:01:03,760 --> 00:01:06,479 Speaker 1: in addition to this being a story about women computers, 21 00:01:06,480 --> 00:01:11,320 Speaker 1: both white and black. It's also about abolitionist astronomers, religious 22 00:01:11,319 --> 00:01:13,720 Speaker 1: fanatics who are trying to raise the dead as well 23 00:01:13,800 --> 00:01:19,200 Speaker 1: as explore the universe, bisexual goth rockets, scientists, and a 24 00:01:19,200 --> 00:01:21,119 Speaker 1: gay man who saved millions of lives in World War 25 00:01:21,160 --> 00:01:23,080 Speaker 1: Two and was oppressed as hell by the government that 26 00:01:23,120 --> 00:01:26,200 Speaker 1: he just saved. And I'm sure I'm leaving more stuff out. 27 00:01:26,480 --> 00:01:29,280 Speaker 1: It's a weird story today, but I think it's gonna 28 00:01:29,280 --> 00:01:32,880 Speaker 1: be a cool one to bear with me. Oh, this 29 00:01:32,959 --> 00:01:35,679 Speaker 1: is right up my alley. I love talking about how 30 00:01:35,720 --> 00:01:40,240 Speaker 1: women used to be the the o g computers like us, 31 00:01:40,520 --> 00:01:45,880 Speaker 1: you know, yeah, I like, I don't even know. I 32 00:01:45,880 --> 00:01:47,560 Speaker 1: was probably in my thirties when I figured out that 33 00:01:47,560 --> 00:01:49,520 Speaker 1: computer was used to be a job description, and I 34 00:01:49,680 --> 00:01:52,560 Speaker 1: grew up a like computer kid, you know, I was 35 00:01:52,640 --> 00:01:56,200 Speaker 1: like interested in computers from whatever. Anyway, I want to 36 00:01:56,240 --> 00:01:58,960 Speaker 1: start with a quote from Stephen J. Gould, who was 37 00:01:59,000 --> 00:02:02,200 Speaker 1: an evolutionary biolog just a science educator. And it's a 38 00:02:02,280 --> 00:02:03,880 Speaker 1: quote people have heard before, but I feel like it's 39 00:02:03,880 --> 00:02:07,080 Speaker 1: relevant to kind of frame what we're talking about today. 40 00:02:07,520 --> 00:02:10,679 Speaker 1: I am somehow less interested in the weight and convolutions 41 00:02:10,680 --> 00:02:13,680 Speaker 1: of Einstein's brain than then the near certainty that people 42 00:02:13,720 --> 00:02:16,440 Speaker 1: of equal talent have lived and died in cotton fields 43 00:02:16,440 --> 00:02:22,000 Speaker 1: and sweatshops, and because so the show cool people who 44 00:02:22,000 --> 00:02:25,000 Speaker 1: did cool stuff, it's it's not about heroes. Like I 45 00:02:25,040 --> 00:02:27,480 Speaker 1: don't want to just be like this person is the 46 00:02:27,639 --> 00:02:30,760 Speaker 1: single best person anytime I'm talking about someone. And I 47 00:02:30,800 --> 00:02:33,880 Speaker 1: really basically hate the great man theory of history that 48 00:02:34,080 --> 00:02:39,160 Speaker 1: says that history was just moved forward by single spectacular individuals. Rather, 49 00:02:39,240 --> 00:02:42,720 Speaker 1: I really like that the accurate story, which is that 50 00:02:43,200 --> 00:02:45,480 Speaker 1: ship gets done by a thousand hands doing the work 51 00:02:45,520 --> 00:02:50,880 Speaker 1: together and um including spectacular individuals, but it's not solely them, 52 00:02:50,919 --> 00:02:54,880 Speaker 1: and it's absolutely not them working alone. So like, I 53 00:02:54,880 --> 00:02:56,600 Speaker 1: don't know, Einstein was smart at fun, right, but he 54 00:02:56,639 --> 00:02:58,280 Speaker 1: wasn't the only person as smart as fuck. And there 55 00:02:58,280 --> 00:03:01,000 Speaker 1: are so many people who are artists funk who are 56 00:03:01,000 --> 00:03:05,080 Speaker 1: prevented by systemic barriers from exercising their talents and contributing 57 00:03:05,120 --> 00:03:06,840 Speaker 1: in the way that they would otherwise be able to. 58 00:03:07,320 --> 00:03:10,000 Speaker 1: So today I'm basically excited to talk about smartest fun 59 00:03:10,120 --> 00:03:13,520 Speaker 1: people who had to push past systemic barriers and then 60 00:03:13,680 --> 00:03:17,120 Speaker 1: advanced human knowledge by leaps and bounds. I love that. 61 00:03:17,200 --> 00:03:20,240 Speaker 1: I love that idea that I don't know. There's something 62 00:03:20,280 --> 00:03:23,680 Speaker 1: about engaging with history in this way where the people 63 00:03:23,720 --> 00:03:28,200 Speaker 1: that you admire have to be hero figures. I understand 64 00:03:28,240 --> 00:03:32,080 Speaker 1: the inclination to to lionize and hero eze these people, 65 00:03:32,120 --> 00:03:36,480 Speaker 1: but then you have this really surface engagement with them, 66 00:03:36,480 --> 00:03:40,200 Speaker 1: like you don't. They don't get to be the full, messy, flog, complex, 67 00:03:40,280 --> 00:03:42,680 Speaker 1: dynamic people that we know they are. They get to 68 00:03:42,720 --> 00:03:44,680 Speaker 1: be like a stick around a notebook, right, And how 69 00:03:44,720 --> 00:03:48,040 Speaker 1: boring is that? Yeah? Totally yeah, and like and the 70 00:03:48,080 --> 00:03:50,840 Speaker 1: warts and all thing kind of like keeps us locked 71 00:03:50,840 --> 00:03:52,400 Speaker 1: out of it because we're like, oh, well, I'm not 72 00:03:52,480 --> 00:03:55,240 Speaker 1: as cool as that person because I did bad stuff 73 00:03:55,280 --> 00:03:57,520 Speaker 1: when I was a teenager, or I don't know, I 74 00:03:57,560 --> 00:04:00,480 Speaker 1: lose my temper sometimes or whatever the thing is, um, 75 00:04:00,520 --> 00:04:03,880 Speaker 1: you know, being able to like, yeah, I really want 76 00:04:03,880 --> 00:04:05,760 Speaker 1: to try and warts in all things as much as 77 00:04:05,840 --> 00:04:10,320 Speaker 1: I can. And the two biggest warts that need to 78 00:04:10,320 --> 00:04:12,240 Speaker 1: be talked about before we talk about anything has to 79 00:04:12,240 --> 00:04:14,440 Speaker 1: do with space are the fact that a lot of 80 00:04:14,440 --> 00:04:16,560 Speaker 1: what I'm gonna be talking about our accomplishments that are 81 00:04:16,600 --> 00:04:20,560 Speaker 1: claimed by two nations, neither of which do I have 82 00:04:20,600 --> 00:04:23,080 Speaker 1: any love for. One of those nations is the United 83 00:04:23,080 --> 00:04:29,160 Speaker 1: States of America, and one of them is the the USSRUM. 84 00:04:31,320 --> 00:04:34,960 Speaker 1: I love the just straight up like fuck the USA energy, 85 00:04:35,640 --> 00:04:38,880 Speaker 1: you just ground us in. Yeah, and it's not because 86 00:04:38,920 --> 00:04:40,479 Speaker 1: it's not because I'm like, oh well, if you hate 87 00:04:40,480 --> 00:04:42,960 Speaker 1: the USA, you love the USSR. Like, no, they're they're 88 00:04:42,960 --> 00:04:47,240 Speaker 1: both bad things, like hate them both. Yeah, but but 89 00:04:47,360 --> 00:04:50,320 Speaker 1: cool people within those structures figured out how to advance 90 00:04:50,400 --> 00:04:53,400 Speaker 1: human knowledge as best as they could. Yeah, I don't know. 91 00:04:53,480 --> 00:04:57,000 Speaker 1: And so most of these people get talked about in 92 00:04:57,040 --> 00:05:00,200 Speaker 1: patriotic terms. But as far as I can tell, most 93 00:05:00,240 --> 00:05:02,159 Speaker 1: of these people, and I'll mark some who did, most 94 00:05:02,160 --> 00:05:04,240 Speaker 1: of these people did not see things in patriotic terms. 95 00:05:04,279 --> 00:05:07,800 Speaker 1: They saw things basically. I mean, they care about science 96 00:05:07,839 --> 00:05:10,680 Speaker 1: by and large more than anything else. But I'm I'm 97 00:05:10,720 --> 00:05:12,960 Speaker 1: cutting curious, Bridget, since you you do a lot of 98 00:05:13,000 --> 00:05:16,800 Speaker 1: work around this sort of thing, Like, how do you 99 00:05:16,839 --> 00:05:21,200 Speaker 1: handle talking about people who do good things within bad frameworks? 100 00:05:21,279 --> 00:05:24,239 Speaker 1: You know, like like people like now we're all stock 101 00:05:24,279 --> 00:05:27,039 Speaker 1: working these capitalist jobs and things like that, or you know, 102 00:05:28,080 --> 00:05:31,160 Speaker 1: all the science that ends up being used by governments, 103 00:05:31,160 --> 00:05:34,520 Speaker 1: by by forces of colonization and all that. Ship. Yeah, 104 00:05:34,560 --> 00:05:37,640 Speaker 1: what a good question. I think it's really complicated and 105 00:05:37,680 --> 00:05:39,400 Speaker 1: I guess I try to remember kind of like you 106 00:05:39,480 --> 00:05:43,280 Speaker 1: just pointed out, Margaret, that we're talking about people within systems, right, 107 00:05:43,279 --> 00:05:46,120 Speaker 1: So like I'm an anti capitalist. I don't really funk 108 00:05:46,160 --> 00:05:48,920 Speaker 1: with our government like that, Like I'm consider myself a radical, 109 00:05:49,240 --> 00:05:51,200 Speaker 1: but I'm still living in the United States, and so 110 00:05:51,279 --> 00:05:53,400 Speaker 1: I still have to engage in commerce. They still have to, 111 00:05:53,880 --> 00:05:57,440 Speaker 1: you know, do all the machinations that come with living 112 00:05:57,480 --> 00:06:02,600 Speaker 1: in a white supremacist like how Herrow patriarchy fucked up society, 113 00:06:02,640 --> 00:06:06,080 Speaker 1: and so I just try to I I'm it's really 114 00:06:06,080 --> 00:06:08,080 Speaker 1: easy for me to give myself that grace, and I 115 00:06:08,200 --> 00:06:11,000 Speaker 1: tried to extend that to the people that I'm like 116 00:06:11,120 --> 00:06:14,040 Speaker 1: reading about and and hearing about and learning about, because 117 00:06:14,520 --> 00:06:18,080 Speaker 1: you know, there are also individuals who did cool ship, 118 00:06:18,480 --> 00:06:21,359 Speaker 1: but we're trapped within systems that are very oppressive, and 119 00:06:21,400 --> 00:06:24,200 Speaker 1: so it's a bummer to see like, oh, this cool 120 00:06:24,240 --> 00:06:27,360 Speaker 1: ship was used to do something horrible that I don't 121 00:06:27,360 --> 00:06:29,560 Speaker 1: agree with, but you got to remember that it's like 122 00:06:29,960 --> 00:06:35,000 Speaker 1: against that backdrop that none of us can really escape. Yeah, um, 123 00:06:35,040 --> 00:06:39,080 Speaker 1: I was. There's this amazing trans woman named Lynn Conway 124 00:06:39,160 --> 00:06:42,080 Speaker 1: who is super cool. She's still alive, and she is 125 00:06:42,480 --> 00:06:44,640 Speaker 1: used to work for IBM back in the fifties, and 126 00:06:44,680 --> 00:06:47,440 Speaker 1: she is like the person who developed the technology for 127 00:06:47,440 --> 00:06:49,480 Speaker 1: the cell phone, right, and like she was fired from 128 00:06:49,480 --> 00:06:52,080 Speaker 1: IBM for being trans and all this stuff, and reading 129 00:06:52,080 --> 00:06:54,440 Speaker 1: about her story, I was like, wow, I'm so inspired 130 00:06:54,480 --> 00:06:56,919 Speaker 1: by her, Like what a life. But then I continued 131 00:06:56,960 --> 00:06:58,719 Speaker 1: reading about her story and it's like, oh, she was 132 00:06:58,760 --> 00:07:03,880 Speaker 1: designing the pen for the government. Cool cool Google like, 133 00:07:04,120 --> 00:07:06,640 Speaker 1: But that doesn't mean I admire her and her bravery 134 00:07:06,680 --> 00:07:09,920 Speaker 1: and her you know, ability to like do cool ship 135 00:07:10,040 --> 00:07:12,960 Speaker 1: and persevere any less, even though I don't love the 136 00:07:13,000 --> 00:07:16,120 Speaker 1: fact that, you know, building defense for the government isn't 137 00:07:16,160 --> 00:07:20,679 Speaker 1: really my cup of tea, right, totally. No, that that 138 00:07:20,680 --> 00:07:22,640 Speaker 1: that nails it, And I think that's the similar story. Now. 139 00:07:22,680 --> 00:07:24,640 Speaker 1: I actually want to find out more about this this woman. 140 00:07:24,720 --> 00:07:27,520 Speaker 1: But um, a lot of the people that are going 141 00:07:27,560 --> 00:07:30,240 Speaker 1: to end up interwoven into this story have a very 142 00:07:30,880 --> 00:07:33,720 Speaker 1: you'll learn You'll learn this when you ever I'm talking 143 00:07:33,760 --> 00:07:36,480 Speaker 1: with Bridget, I end up like spending like four hours googling, 144 00:07:40,120 --> 00:07:43,200 Speaker 1: and like the best possible way. I'm gonna take that 145 00:07:43,200 --> 00:07:47,760 Speaker 1: as a compliment, absolutely, all right. So I want to 146 00:07:47,800 --> 00:07:50,400 Speaker 1: start by going way back in time, just because it's fun. 147 00:07:50,720 --> 00:07:52,320 Speaker 1: And the first thing that I want to make like 148 00:07:52,400 --> 00:07:55,320 Speaker 1: really clear to anyone um which I think everyone knows 149 00:07:55,320 --> 00:07:58,240 Speaker 1: this unless you swallowed a lot of really Eurocentric history, 150 00:07:58,280 --> 00:08:00,880 Speaker 1: which is that the first people doing complex were not 151 00:08:00,920 --> 00:08:05,960 Speaker 1: white people. The oldest undisputed mathematical documents are from Egypt 152 00:08:06,000 --> 00:08:09,360 Speaker 1: and Mesopotamia which is modern day Iraq, and there are 153 00:08:09,400 --> 00:08:12,320 Speaker 1: from the second century BC. The concept of zero was 154 00:08:12,520 --> 00:08:15,679 Speaker 1: imported into Europe from Africa. China was the first place 155 00:08:15,680 --> 00:08:18,440 Speaker 1: to make use of negative numbers. To be fair, as 156 00:08:18,480 --> 00:08:20,520 Speaker 1: far as I can tell, ancient Greece wasn't like terribly 157 00:08:20,600 --> 00:08:23,520 Speaker 1: far behind, but they, you know, got these ideas from 158 00:08:23,560 --> 00:08:26,440 Speaker 1: other places, and then the Celts picked some of it up. 159 00:08:26,480 --> 00:08:30,559 Speaker 1: But but overall, quote unquote Western knowledge is absolutely based 160 00:08:30,600 --> 00:08:34,120 Speaker 1: on Asian and African knowledge as far as anything I 161 00:08:34,120 --> 00:08:36,959 Speaker 1: can tell. And then the other thing in which I 162 00:08:37,120 --> 00:08:39,720 Speaker 1: guess I recovered in the introduction is to know is 163 00:08:39,720 --> 00:08:43,080 Speaker 1: that the first computers were people. So someone who computes, 164 00:08:43,200 --> 00:08:47,000 Speaker 1: someone who solves mathematical problems, which a lot of it 165 00:08:47,040 --> 00:08:49,360 Speaker 1: was about astronomy, a lot of it back in the day. 166 00:08:49,400 --> 00:08:51,920 Speaker 1: A lot of the first complex math that people were 167 00:08:51,960 --> 00:08:54,760 Speaker 1: doing was tracking the position of stars, which I like 168 00:08:54,880 --> 00:08:57,559 Speaker 1: because it ties neatly back into the story that we're 169 00:08:57,559 --> 00:09:01,960 Speaker 1: gonna be telling today. And the word computer itself dates 170 00:09:01,960 --> 00:09:06,080 Speaker 1: back to at least six from some really weird quote 171 00:09:06,080 --> 00:09:07,520 Speaker 1: that I could not figure how to parse, and I 172 00:09:07,520 --> 00:09:09,320 Speaker 1: like asked the Internet, and the Internet's like, we don't 173 00:09:09,320 --> 00:09:11,840 Speaker 1: know how to parse this either, some quote about the 174 00:09:11,880 --> 00:09:14,400 Speaker 1: mortality of man and how God or maybe Moses is 175 00:09:14,440 --> 00:09:20,960 Speaker 1: the computer who counts your days. Oh yeah, And everyone's like, 176 00:09:21,000 --> 00:09:22,960 Speaker 1: is this about God or Moses or something, or is 177 00:09:22,960 --> 00:09:25,440 Speaker 1: it just like some guy who's like counting all your 178 00:09:25,480 --> 00:09:27,600 Speaker 1: days who just like, I don't know, maybe a profit 179 00:09:27,679 --> 00:09:30,280 Speaker 1: or something. I'm not sure. Someone listening to this nose 180 00:09:30,360 --> 00:09:32,800 Speaker 1: and will be very upset that I didn't focus on 181 00:09:32,800 --> 00:09:36,240 Speaker 1: this particular aspect. But originally it was interchangeable with the 182 00:09:36,240 --> 00:09:39,920 Speaker 1: word mathematician, until eventually mathematicians started implying someone who was 183 00:09:39,920 --> 00:09:43,240 Speaker 1: doing the thinking about math and computer was involving someone 184 00:09:43,640 --> 00:09:47,560 Speaker 1: solving the math, which of course makes a hierarchy. And 185 00:09:47,640 --> 00:09:49,920 Speaker 1: when you figure out how to make a hierarchy, people 186 00:09:49,960 --> 00:09:52,040 Speaker 1: figure out how to shove humans onto it based on 187 00:09:52,120 --> 00:09:56,800 Speaker 1: existing systems of discrimination. So for a computer, they went 188 00:09:56,840 --> 00:09:59,720 Speaker 1: with one of the classics. Men do the thinking. Women 189 00:09:59,760 --> 00:10:03,400 Speaker 1: do the solving, which is obviously thinking also, but you know, 190 00:10:04,160 --> 00:10:08,800 Speaker 1: try explaining that to the patriarch. I love that people 191 00:10:08,800 --> 00:10:12,000 Speaker 1: were able to get away with saying that solving didn't 192 00:10:12,040 --> 00:10:19,319 Speaker 1: involve like complex thought evolved. Yeah, they're not doing the 193 00:10:19,400 --> 00:10:21,480 Speaker 1: higher level thinking about it. I'm like, I can't do 194 00:10:21,520 --> 00:10:26,520 Speaker 1: either of these things. So and it's actually something that 195 00:10:26,559 --> 00:10:28,920 Speaker 1: I've noticed in a lot of fields that I've worked in, 196 00:10:29,080 --> 00:10:32,080 Speaker 1: is that, for example, and publishing and a lot of 197 00:10:32,080 --> 00:10:34,840 Speaker 1: my work and publishing as a writer, it's a lot 198 00:10:34,880 --> 00:10:37,559 Speaker 1: of this is not universal and I'm not trying to 199 00:10:37,600 --> 00:10:40,840 Speaker 1: call out individual publishers, but there's a lot of women 200 00:10:40,880 --> 00:10:44,240 Speaker 1: doing the back end work and who are to publish men? Right, 201 00:10:44,320 --> 00:10:46,360 Speaker 1: A lot of the people who make books happen, who 202 00:10:46,360 --> 00:10:48,600 Speaker 1: are the editors, who are the type setters, who are 203 00:10:49,240 --> 00:10:52,360 Speaker 1: just doing all the work, not all the work. Writing 204 00:10:52,440 --> 00:10:56,679 Speaker 1: is work too, but I don't know it, and it 205 00:10:56,679 --> 00:11:00,360 Speaker 1: it annoys me when I've noticed that publishers work for 206 00:11:00,400 --> 00:11:03,240 Speaker 1: it annoys me. Yeah, it is annoying, and I see it. 207 00:11:03,400 --> 00:11:05,319 Speaker 1: I agree with you, and I've seen it in so 208 00:11:05,360 --> 00:11:08,119 Speaker 1: many places. And I think that labor that we associate 209 00:11:08,160 --> 00:11:11,680 Speaker 1: with women, it's always going to be devalued. And so 210 00:11:12,120 --> 00:11:14,880 Speaker 1: even if it's the labor that like literally the thing 211 00:11:14,920 --> 00:11:18,360 Speaker 1: would not exist without this labor. It is the grease 212 00:11:18,400 --> 00:11:21,400 Speaker 1: that keeps the wheels running if it's associated with women 213 00:11:21,640 --> 00:11:24,720 Speaker 1: or somehow like perceived as feminine, and we just don't 214 00:11:24,800 --> 00:11:27,319 Speaker 1: value it, and that you can see that in I 215 00:11:27,360 --> 00:11:31,880 Speaker 1: mean everywhere, all all the all the way down. Yeah, no, absolutely, 216 00:11:32,520 --> 00:11:34,800 Speaker 1: But it took a while for for Western men to 217 00:11:34,840 --> 00:11:36,880 Speaker 1: actually figure out that they can make women do this work, 218 00:11:36,880 --> 00:11:39,440 Speaker 1: because they were like not convinced that women were smart 219 00:11:39,559 --> 00:11:42,840 Speaker 1: enough to do the solving or whatever. So so most 220 00:11:42,880 --> 00:11:45,280 Speaker 1: computers started off men as far as I can tell, 221 00:11:45,640 --> 00:11:48,640 Speaker 1: until about the second half of the nineteenth century, and 222 00:11:49,760 --> 00:11:51,680 Speaker 1: the first one I found, there's no part of me 223 00:11:51,720 --> 00:11:54,040 Speaker 1: that believes is the first woman computer, even under that name, 224 00:11:54,480 --> 00:11:59,760 Speaker 1: but the first white english woman Mary Edwards. Mary Edwards 225 00:11:59,800 --> 00:12:02,880 Speaker 1: was a white english woman born sometimes around seventeen fifty 226 00:12:03,080 --> 00:12:06,160 Speaker 1: and her husband, John Edwards, was a clergyman who couldn't 227 00:12:06,200 --> 00:12:08,240 Speaker 1: make ends meet, so in seventeen seventy three he got 228 00:12:08,280 --> 00:12:11,959 Speaker 1: himself hired by the British Nautical Almanac, among other people, 229 00:12:12,200 --> 00:12:14,920 Speaker 1: to do astronomical calculations for their almanac. And so he 230 00:12:14,960 --> 00:12:17,559 Speaker 1: became a computer, which is cool until you realize that 231 00:12:17,600 --> 00:12:19,360 Speaker 1: probably mostly what he did is make an almac that 232 00:12:19,400 --> 00:12:21,320 Speaker 1: was used by British sailors to go around and impress 233 00:12:21,320 --> 00:12:25,319 Speaker 1: people all over the world. But you know, um, the 234 00:12:25,320 --> 00:12:27,000 Speaker 1: people who can afford to pay people to do the 235 00:12:27,040 --> 00:12:29,880 Speaker 1: math there often up to no good. So John Edwards 236 00:12:30,040 --> 00:12:32,280 Speaker 1: he's getting paid as a computer, but he's not a computer. 237 00:12:32,360 --> 00:12:34,800 Speaker 1: His wife as a computer. His wife is doing all 238 00:12:34,840 --> 00:12:37,520 Speaker 1: of the computing work. It's possible that he was doing 239 00:12:37,559 --> 00:12:38,840 Speaker 1: some of it. I'm not sure, but I believe she 240 00:12:38,920 --> 00:12:41,960 Speaker 1: was doing the majority or all of it. And I 241 00:12:42,000 --> 00:12:44,720 Speaker 1: actually kind of wonder how many times throughout history this happens, 242 00:12:44,800 --> 00:12:47,720 Speaker 1: where some man just literally gets the credit in the 243 00:12:47,720 --> 00:12:50,920 Speaker 1: pay and and sometimes maybe in a mean way, being 244 00:12:50,920 --> 00:12:52,559 Speaker 1: like ha ha, I'm going to take all the credit. 245 00:12:52,600 --> 00:12:55,160 Speaker 1: And maybe sometimes it's like a woman is like, all right, well, 246 00:12:55,200 --> 00:12:57,000 Speaker 1: I can't get any ship done unless I marry this 247 00:12:57,080 --> 00:12:59,000 Speaker 1: dude and get him to take the credit. You know, 248 00:13:00,360 --> 00:13:03,920 Speaker 1: So he dies in God only knows what he dies from, 249 00:13:03,960 --> 00:13:06,880 Speaker 1: probably just from being alive in the eighteenth century, which 250 00:13:07,160 --> 00:13:10,839 Speaker 1: killed a lot of people young. And when he died, 251 00:13:11,360 --> 00:13:13,840 Speaker 1: she wrote the Nautical Board a letter and was like, hey, 252 00:13:14,640 --> 00:13:17,480 Speaker 1: it was actually me the entire time. Can I can 253 00:13:17,520 --> 00:13:21,040 Speaker 1: I keep having this job? I like having this job? 254 00:13:21,880 --> 00:13:24,080 Speaker 1: And they said yes, and she became one of the 255 00:13:24,080 --> 00:13:27,960 Speaker 1: their thirty five computers and the first woman to work 256 00:13:28,120 --> 00:13:31,840 Speaker 1: under the job title computer, at least in English. Probably 257 00:13:31,880 --> 00:13:33,920 Speaker 1: a bad sign that I was like, oh wow, Luke 258 00:13:33,960 --> 00:13:39,000 Speaker 1: said yes, I know, right, really bad, very progressive of 259 00:13:39,760 --> 00:13:42,440 Speaker 1: But the sad part is it probably was there was 260 00:13:42,480 --> 00:13:47,840 Speaker 1: probably that's a woman taking credit for her labor and 261 00:13:47,920 --> 00:13:51,240 Speaker 1: like being able to continue to do it. Who would 262 00:13:51,280 --> 00:13:54,520 Speaker 1: have thought. There's probably like an entire movies worth of 263 00:13:54,600 --> 00:13:57,760 Speaker 1: drama that happened around that decision. You know, there's probably 264 00:13:57,800 --> 00:14:00,120 Speaker 1: like one of the guys was like, I think we 265 00:14:00,120 --> 00:14:02,320 Speaker 1: should let her do it, and then he like loses 266 00:14:02,360 --> 00:14:05,400 Speaker 1: his job, but then like the head of it all, 267 00:14:05,440 --> 00:14:07,680 Speaker 1: his wife is like, I won't suck you until you 268 00:14:07,880 --> 00:14:11,320 Speaker 1: let him come back, you know whatever. Starring Meryl Streep. 269 00:14:11,440 --> 00:14:15,959 Speaker 1: Obviously I would watch that and one of the things 270 00:14:15,960 --> 00:14:17,520 Speaker 1: that was kind of interesting, right You're like, oh, wow, 271 00:14:17,559 --> 00:14:19,120 Speaker 1: she's and then you're like, oh, she's one of thirty 272 00:14:19,120 --> 00:14:20,840 Speaker 1: five people doing this work, and this is something that 273 00:14:20,880 --> 00:14:22,120 Speaker 1: seems to get left out and a lot of the 274 00:14:22,120 --> 00:14:25,600 Speaker 1: stuff that talks about this is it's less about individual genius, 275 00:14:25,640 --> 00:14:27,640 Speaker 1: although it is about individual genius, but it's about the 276 00:14:27,680 --> 00:14:30,760 Speaker 1: collective genius of people getting together and you know, they're 277 00:14:30,840 --> 00:14:33,160 Speaker 1: checking and rechecking each other's work, and they even end 278 00:14:33,280 --> 00:14:36,200 Speaker 1: up like splitting problems to work on them as if 279 00:14:37,120 --> 00:14:40,040 Speaker 1: basically parallel processing all of the mathematical problems, which I 280 00:14:40,040 --> 00:14:44,680 Speaker 1: think is cool. So her daughter, Eliza Edwards takes up 281 00:14:44,720 --> 00:14:47,600 Speaker 1: the family business when her mom died, and then she 282 00:14:47,720 --> 00:14:50,320 Speaker 1: had that job until they centralized the job until London 283 00:14:50,520 --> 00:14:52,920 Speaker 1: and since she didn't live in London. Uh oh, and 284 00:14:52,960 --> 00:14:55,080 Speaker 1: then England also passed a bunch of laws making harder 285 00:14:55,120 --> 00:14:58,920 Speaker 1: for women to find work because progress isn't linear and 286 00:14:59,000 --> 00:15:01,960 Speaker 1: sometimes people have it better and worse and things get 287 00:15:02,000 --> 00:15:04,120 Speaker 1: better and then they get worse, which I don't like 288 00:15:04,200 --> 00:15:09,200 Speaker 1: reminding myself right now. Hopeful. Yeah, pretty grim reminder, especially 289 00:15:09,480 --> 00:15:15,240 Speaker 1: at today these days. Yeah. Uh well, gay marriage was nice, 290 00:15:15,240 --> 00:15:17,760 Speaker 1: while no, I'm kidding, we're gonna hold onto it all right. 291 00:15:18,400 --> 00:15:22,040 Speaker 1: So the first American woman computer I run across is 292 00:15:22,040 --> 00:15:24,600 Speaker 1: a woman named Maria Mitchell who's also a white woman, 293 00:15:24,640 --> 00:15:27,560 Speaker 1: and she was born in Nantucket in eighteen eighteen and 294 00:15:27,720 --> 00:15:29,280 Speaker 1: she had the good fortune to be born into a 295 00:15:29,320 --> 00:15:31,400 Speaker 1: Quaker family. And usually say the good fortune and kind 296 00:15:31,400 --> 00:15:33,760 Speaker 1: of a sarcastic way, but this time I'm not being sarcastic. 297 00:15:34,440 --> 00:15:37,040 Speaker 1: Quakers come up disproportionately on this podcast, or at least 298 00:15:37,040 --> 00:15:39,040 Speaker 1: in my research, because they're one of the only groups 299 00:15:39,040 --> 00:15:41,480 Speaker 1: of white people are actually they weren't actually exclusively white, 300 00:15:41,480 --> 00:15:45,360 Speaker 1: but majority white people in the United States who actually 301 00:15:45,360 --> 00:15:49,000 Speaker 1: consistently risked their lives to stop slavery, and relevant to 302 00:15:49,000 --> 00:15:51,680 Speaker 1: today's story, they raised their daughters with the same education 303 00:15:51,720 --> 00:15:55,040 Speaker 1: and opportunities as they raised their sons. So like, Quakers 304 00:15:55,240 --> 00:15:57,760 Speaker 1: keep doing cool stuff in history way more than I 305 00:15:58,280 --> 00:16:02,120 Speaker 1: very disproportionately. Yeah, I funk with Quakers. I've been to 306 00:16:02,160 --> 00:16:04,680 Speaker 1: Quaker church and it's like cool. Like I'm not religious, 307 00:16:04,720 --> 00:16:08,080 Speaker 1: but like a Quaker church, their ceremonies are very cool. 308 00:16:08,120 --> 00:16:11,560 Speaker 1: Like sometimes you sit in silence sometimes and whatever comes 309 00:16:11,600 --> 00:16:13,280 Speaker 1: to you, you can speak to the group. It's like 310 00:16:13,320 --> 00:16:16,440 Speaker 1: a very I keep keep being cool Quakers. I like, 311 00:16:16,560 --> 00:16:19,560 Speaker 1: I like what you're doing. Yeah, no, that's cool. So 312 00:16:19,680 --> 00:16:22,880 Speaker 1: Maria she grows up into an educated, maybe middle class family. 313 00:16:23,080 --> 00:16:25,440 Speaker 1: Her her mom is a library worker and her father 314 00:16:25,520 --> 00:16:29,280 Speaker 1: is a school teacher who's into amateur astronomy. Apparents like 315 00:16:29,280 --> 00:16:32,280 Speaker 1: ten fucking kids, and they still found the time to 316 00:16:32,320 --> 00:16:36,360 Speaker 1: teach her all kinds of weird astronomical devices and math ship. 317 00:16:37,000 --> 00:16:39,240 Speaker 1: When she was twelve, she helped her dad calculate the 318 00:16:39,240 --> 00:16:42,200 Speaker 1: solar eclipse, and then she grew up to be even cooler. 319 00:16:42,240 --> 00:16:44,560 Speaker 1: When she was seventeen, she founded a school for girls, 320 00:16:44,960 --> 00:16:46,920 Speaker 1: and the first girls that she took in were three 321 00:16:47,080 --> 00:16:51,080 Speaker 1: quote Portuguese girls, which was slang for immigrant women of color, 322 00:16:51,200 --> 00:16:56,480 Speaker 1: regardless of what nationality. And since schools weren't integrated, basically, 323 00:16:56,480 --> 00:16:59,160 Speaker 1: by by teaching these three girls, she knew that like 324 00:16:59,280 --> 00:17:00,840 Speaker 1: the rich white women and we're going to send their 325 00:17:00,960 --> 00:17:04,120 Speaker 1: kids to her school. And she did it anyway or whatever, 326 00:17:04,400 --> 00:17:05,960 Speaker 1: just like one of these like wow, you passed this 327 00:17:06,040 --> 00:17:09,159 Speaker 1: like bare minimum bar, you know, like I don't know, 328 00:17:11,600 --> 00:17:13,439 Speaker 1: I mean it's like, I mean, get back then. It 329 00:17:13,480 --> 00:17:17,160 Speaker 1: probably was like a very like a very cool radical 330 00:17:17,200 --> 00:17:21,800 Speaker 1: thing to do. Yeah, no, totally. But the downside is 331 00:17:21,800 --> 00:17:23,960 Speaker 1: that since she's seventeen when she starts this school, she's 332 00:17:23,960 --> 00:17:26,119 Speaker 1: a teenager, and so she pretty quickly gets bored I 333 00:17:26,160 --> 00:17:32,280 Speaker 1: think of teaching. Uh so I don't know, when she's eighteen, 334 00:17:32,359 --> 00:17:35,439 Speaker 1: she gets offered a librarian ship at the Nantucket Athenium. 335 00:17:35,480 --> 00:17:37,680 Speaker 1: And I've never heard of an athenium. Have you heard 336 00:17:37,720 --> 00:17:39,600 Speaker 1: of an athenium? I don't even know if they still exist. 337 00:17:40,000 --> 00:17:42,199 Speaker 1: I've never heard of it. My spell check knows what 338 00:17:42,240 --> 00:17:43,600 Speaker 1: they are, so I think it must be a thing. 339 00:17:44,080 --> 00:17:48,560 Speaker 1: But it was this cultural center slash learning center slash 340 00:17:48,640 --> 00:17:51,280 Speaker 1: library hybrid thing that they had going on at least 341 00:17:51,280 --> 00:17:53,879 Speaker 1: in n Tuckett. It seems really cool, and so she 342 00:17:53,880 --> 00:17:57,320 Speaker 1: shakes this job I think maybe closes her school. I 343 00:17:57,320 --> 00:18:00,760 Speaker 1: don't know. I hopefully someone else took it on. And 344 00:18:01,560 --> 00:18:04,200 Speaker 1: so she now starts working at the Atheneum. When five 345 00:18:04,280 --> 00:18:07,040 Speaker 1: years later, when she's twenty three, there's this twenty three 346 00:18:07,119 --> 00:18:09,560 Speaker 1: year old who had just escaped slavery a couple of 347 00:18:09,600 --> 00:18:11,640 Speaker 1: years earlier who shows up to give his very first 348 00:18:11,640 --> 00:18:16,080 Speaker 1: public address at anti slavery conference at the Nantucket Antheneum. 349 00:18:16,119 --> 00:18:19,760 Speaker 1: And the guy's name is Frederick Douglas. And so he 350 00:18:19,800 --> 00:18:23,800 Speaker 1: gives his very first public address about the need for 351 00:18:23,840 --> 00:18:26,119 Speaker 1: abolition and all that ship at this thing, and everyone 352 00:18:26,160 --> 00:18:29,560 Speaker 1: gets really excited about him because he's fucking awesome. Can 353 00:18:29,600 --> 00:18:31,600 Speaker 1: you imagine here, like like I know he was known 354 00:18:31,640 --> 00:18:35,040 Speaker 1: as an orator, Like can you imagine being in the crowd, 355 00:18:35,280 --> 00:18:38,040 Speaker 1: probably like being like, oh yeah, I was there for 356 00:18:38,359 --> 00:18:44,200 Speaker 1: Nirvana's Unplugged totally, totally because this is the very first one, 357 00:18:44,200 --> 00:18:45,560 Speaker 1: and the stuff I was reading about it was like 358 00:18:45,560 --> 00:18:47,200 Speaker 1: he was really nervous. He was like, I don't know 359 00:18:47,200 --> 00:18:48,960 Speaker 1: if these people are gonna like me. And then like 360 00:18:49,400 --> 00:18:52,040 Speaker 1: everyone's just like, he like steals the show. He's just 361 00:18:52,080 --> 00:18:54,560 Speaker 1: like an opening speaker or whatever, and everyone's just just like, no, 362 00:18:54,680 --> 00:18:58,040 Speaker 1: this guy, this guy rules. And so she's she stays 363 00:18:58,080 --> 00:19:01,000 Speaker 1: friends with him, and they reign friends the rest of 364 00:19:01,000 --> 00:19:04,920 Speaker 1: their lives. And I know this is not actually synchronicity 365 00:19:05,000 --> 00:19:07,879 Speaker 1: or it's probably coincidence, but he called his newspaper the 366 00:19:07,920 --> 00:19:10,840 Speaker 1: north Star, and I just anything that's astronomical, I'm going 367 00:19:10,880 --> 00:19:18,400 Speaker 1: to shove into this story. And it's like shameless, yeah 368 00:19:19,880 --> 00:19:23,760 Speaker 1: for you, Yeah, y'all hired a science fiction writer to 369 00:19:23,840 --> 00:19:27,280 Speaker 1: tell a history podcast. I'm not gonna lie, but I'm 370 00:19:27,280 --> 00:19:29,560 Speaker 1: going to look for anything I can't that fits. I 371 00:19:29,560 --> 00:19:33,399 Speaker 1: wouldn't want you to be any other way, Margaret. And 372 00:19:33,480 --> 00:19:36,000 Speaker 1: so this is something that I actually am trying to 373 00:19:36,080 --> 00:19:38,040 Speaker 1: learn more about right now. And I don't totally know 374 00:19:38,040 --> 00:19:40,120 Speaker 1: how I feel, because I I've known for a long 375 00:19:40,160 --> 00:19:42,120 Speaker 1: time that the suffragette movement and a lot of early 376 00:19:42,160 --> 00:19:45,359 Speaker 1: feminism and in the US and UK was racists, and 377 00:19:45,400 --> 00:19:47,560 Speaker 1: there was a lot of like, we want the vote 378 00:19:47,600 --> 00:19:49,440 Speaker 1: for white women and we don't give a shit about 379 00:19:49,440 --> 00:19:53,760 Speaker 1: anyone else. But when I'm looking through the nineteenth century abolitionists, 380 00:19:53,800 --> 00:19:57,520 Speaker 1: I keep coming across all of these places where they 381 00:19:57,520 --> 00:20:02,440 Speaker 1: intertwined with early feminism, and and Maria Mitchell is one 382 00:20:02,480 --> 00:20:04,639 Speaker 1: of these people, and it is part of the abolitionist movement, 383 00:20:04,640 --> 00:20:07,920 Speaker 1: and it seems like there must have been like a 384 00:20:07,920 --> 00:20:10,280 Speaker 1: a bad split, or maybe I'm just like spoiled and 385 00:20:10,320 --> 00:20:12,199 Speaker 1: only reading the people who I come across, you know, 386 00:20:12,760 --> 00:20:15,199 Speaker 1: I don't know, Yeah, I mean, I think it's one 387 00:20:15,240 --> 00:20:18,879 Speaker 1: of those things where I see this a lot where 388 00:20:19,200 --> 00:20:24,199 Speaker 1: people who are historically like marginalized, there's this idea that 389 00:20:24,240 --> 00:20:27,000 Speaker 1: we need to be working against one another, and the 390 00:20:27,080 --> 00:20:29,600 Speaker 1: times where you work alongside each other, it's like you 391 00:20:29,640 --> 00:20:32,159 Speaker 1: really see so clearly that we're strong, our movements are 392 00:20:32,200 --> 00:20:35,960 Speaker 1: stronger together, that unity is so much more powerful than division, 393 00:20:36,080 --> 00:20:39,080 Speaker 1: like the times where there's that, you know, alignment. I 394 00:20:39,119 --> 00:20:42,760 Speaker 1: think in history has always been so powerful. Yeah, no, totally, 395 00:20:42,760 --> 00:20:45,760 Speaker 1: and it's when she gets done, you know. Like so 396 00:20:45,800 --> 00:20:48,280 Speaker 1: she was part of this movement, this abolitionist movement called 397 00:20:48,280 --> 00:20:51,440 Speaker 1: the free product produce movement, which was a slave labor 398 00:20:51,480 --> 00:20:56,240 Speaker 1: boycott movement that was originally started shocker by Quakers. Um, 399 00:20:56,280 --> 00:21:00,119 Speaker 1: and I think both white and black Quakers, but even 400 00:21:00,119 --> 00:21:02,840 Speaker 1: when I'm talking about abolitionists, it's annoyingly hard to find 401 00:21:02,840 --> 00:21:06,160 Speaker 1: information about the Black Quakers. The free Produce movement starts 402 00:21:06,200 --> 00:21:09,080 Speaker 1: in the late eighteenth century, and by the early eighteen hundreds, 403 00:21:09,119 --> 00:21:12,119 Speaker 1: various organizations of free black people are involved, and they 404 00:21:12,200 --> 00:21:15,560 Speaker 1: opened stores that sold only slave labor free goods, including 405 00:21:15,680 --> 00:21:19,480 Speaker 1: sugar and fabric. Maria Mitchell famously wore mostly silk because 406 00:21:19,480 --> 00:21:22,560 Speaker 1: she wouldn't wear cotton grown by enslaved people, which sounds 407 00:21:22,560 --> 00:21:27,560 Speaker 1: like the boogist way to protest slavery. Yeah, you're protesting slavery. 408 00:21:27,560 --> 00:21:33,320 Speaker 1: And also like looking look like like drippy, Yeah, good 409 00:21:33,359 --> 00:21:36,600 Speaker 1: look um. And so they had to set up their 410 00:21:36,640 --> 00:21:40,840 Speaker 1: whole alternate um distribution networks for goods, and they did, 411 00:21:41,359 --> 00:21:43,640 Speaker 1: and this movement ran in one form or another until 412 00:21:43,640 --> 00:21:46,520 Speaker 1: the eighteen fifties into to the decade before the Civil War. 413 00:21:46,920 --> 00:21:49,119 Speaker 1: And overall it was not actually a success. It was 414 00:21:49,400 --> 00:21:51,119 Speaker 1: a valiant effort that a lot of people put a 415 00:21:51,160 --> 00:21:54,200 Speaker 1: lot of work into, but like a lot of boycott movements, 416 00:21:54,200 --> 00:21:58,359 Speaker 1: it did end up failing. And um, basically it was 417 00:21:58,400 --> 00:22:00,840 Speaker 1: too hard for the these goods to compete on the 418 00:22:00,880 --> 00:22:04,320 Speaker 1: open market. Some of them were less high quality, some 419 00:22:04,359 --> 00:22:07,200 Speaker 1: of them were just too expensive. Not everyone can afford 420 00:22:07,240 --> 00:22:10,120 Speaker 1: to roll around in silk, I don't know, and actually 421 00:22:10,359 --> 00:22:13,439 Speaker 1: just to not The Quakers get a lot of credit, 422 00:22:13,480 --> 00:22:17,120 Speaker 1: but she, actually, Maria Mitchell converted to Unitarian, so they 423 00:22:17,160 --> 00:22:19,879 Speaker 1: also get to claim her, I think, And she was 424 00:22:19,920 --> 00:22:22,080 Speaker 1: not afraid of mixing science and religion. One of her 425 00:22:22,119 --> 00:22:26,080 Speaker 1: quotes about her astronomical work is every formula which expresses 426 00:22:26,080 --> 00:22:28,240 Speaker 1: a law of nature is a hymn of praise to God. 427 00:22:29,600 --> 00:22:31,320 Speaker 1: And this is going to be a theme that's going 428 00:22:31,359 --> 00:22:33,199 Speaker 1: to come through as the religious beliefs of all these 429 00:22:33,200 --> 00:22:35,520 Speaker 1: people who are supposed to be like cold heart atheists 430 00:22:35,600 --> 00:22:39,919 Speaker 1: working on science. I love that because, like how many 431 00:22:39,720 --> 00:22:41,879 Speaker 1: I love when someone has like a scientist or like 432 00:22:41,920 --> 00:22:45,760 Speaker 1: a math background, but they're also into astrology or something 433 00:22:45,800 --> 00:22:47,639 Speaker 1: like that. Like I love you know, I love the 434 00:22:47,800 --> 00:22:50,679 Speaker 1: I love the duality. Yeah, well, that's almost everyone I'm 435 00:22:50,720 --> 00:22:52,800 Speaker 1: going to talk about, which wasn't even my plan. I 436 00:22:52,840 --> 00:22:54,879 Speaker 1: just was like writing about all these people and then 437 00:22:54,920 --> 00:22:58,399 Speaker 1: I was like, all these people are really interesting, and 438 00:22:58,440 --> 00:23:01,639 Speaker 1: you know what else is really interesting is the complications 439 00:23:01,760 --> 00:23:04,480 Speaker 1: of being anti capit lists who are supported by advertising. 440 00:23:07,760 --> 00:23:17,240 Speaker 1: Abert you did not, so we have decided um you also, um, Bridget, 441 00:23:17,280 --> 00:23:20,160 Speaker 1: if you have any ideas for sponsors, like very wholesome sponsors. 442 00:23:20,200 --> 00:23:21,720 Speaker 1: One of my favorite sponsors of the show is the 443 00:23:21,720 --> 00:23:24,920 Speaker 1: concept of potatoes. I'm also really excited about tap water, 444 00:23:25,160 --> 00:23:28,720 Speaker 1: like potable water for free and on demand. UM. I've 445 00:23:28,720 --> 00:23:31,560 Speaker 1: also would like our new sponsor, Sophie, would you be 446 00:23:31,600 --> 00:23:34,479 Speaker 1: able to get um don't say anything to cops as 447 00:23:34,520 --> 00:23:40,680 Speaker 1: a sponsor. Yeah concept UM. Shout out to that person 448 00:23:40,680 --> 00:23:44,560 Speaker 1: who sent us that they got an actual water sponsor Twitter. 449 00:23:44,920 --> 00:23:50,240 Speaker 1: I really appreciate you, Bridget. Do you have a wholesome 450 00:23:50,280 --> 00:23:52,080 Speaker 1: sponsor that you would like you you would like us 451 00:23:52,080 --> 00:23:54,640 Speaker 1: to re sponsored by? Uh? Yeah, I think you should 452 00:23:54,680 --> 00:23:57,880 Speaker 1: be sponsored by a good Comb. You know, I really 453 00:23:57,880 --> 00:24:01,639 Speaker 1: appreciate in respect of good Comb me all right, but 454 00:24:01,720 --> 00:24:04,879 Speaker 1: not a specific brand, just the concept, yeah, just the 455 00:24:04,920 --> 00:24:08,160 Speaker 1: concept of a reliable come all right, here's some other 456 00:24:08,200 --> 00:24:10,360 Speaker 1: ads that may may or may not be as cool 457 00:24:10,400 --> 00:24:20,080 Speaker 1: as that. All right, and we are back. So. One 458 00:24:20,080 --> 00:24:22,040 Speaker 1: of the other things that Maria Mitchell did actually that 459 00:24:22,080 --> 00:24:24,280 Speaker 1: I found interesting is that when she was a teenager, 460 00:24:24,320 --> 00:24:26,840 Speaker 1: her older sister bought a piano and Maria pitched in. 461 00:24:27,240 --> 00:24:30,080 Speaker 1: And this was this massive local scandal because Quakers at 462 00:24:30,080 --> 00:24:34,280 Speaker 1: the time didn't approve of music, and her father at 463 00:24:34,320 --> 00:24:36,719 Speaker 1: first was like really disapproving. But basically, when as far 464 00:24:36,720 --> 00:24:38,480 Speaker 1: as as far as I can tell, when the rest 465 00:24:38,480 --> 00:24:40,000 Speaker 1: of the community was like, you need to be mad 466 00:24:40,000 --> 00:24:41,679 Speaker 1: at your daughter's for having a piano, he was like, 467 00:24:41,720 --> 00:24:43,639 Speaker 1: I will not be mad at my daughter's And it 468 00:24:43,760 --> 00:24:46,600 Speaker 1: ended up again, there's so many little micro moments that 469 00:24:46,600 --> 00:24:48,880 Speaker 1: I would absolutely watch movies of. It ended up being 470 00:24:48,880 --> 00:24:51,480 Speaker 1: this thing where like the local Quaker community came around 471 00:24:51,560 --> 00:24:55,960 Speaker 1: and started incorporating music more into the stuff they do. Oh, 472 00:24:56,000 --> 00:24:59,040 Speaker 1: this sounds like a like an old school version of Um, 473 00:24:59,119 --> 00:25:02,320 Speaker 1: what's the movie where dancing is illegal? And then at 474 00:25:02,320 --> 00:25:07,920 Speaker 1: the ends, like the quicker version of foot Loose? Yeah, exactly, Um, 475 00:25:07,920 --> 00:25:12,240 Speaker 1: maybe that's where this foot Loose got it from. UM. 476 00:25:12,280 --> 00:25:15,600 Speaker 1: In eighty seven, she discovers a telescopic comment that is 477 00:25:15,640 --> 00:25:17,240 Speaker 1: one that can't be seen by the naked eye because 478 00:25:17,280 --> 00:25:19,600 Speaker 1: she's doing astronomy this whole time while she's doing everything else. 479 00:25:19,880 --> 00:25:22,600 Speaker 1: And she wins this Astronomy award, which is a gold 480 00:25:22,640 --> 00:25:25,120 Speaker 1: medal from the King of Denmark, whose father had said 481 00:25:25,160 --> 00:25:28,199 Speaker 1: anyone who discovers a comment gets a gold medal, and 482 00:25:28,280 --> 00:25:30,560 Speaker 1: she was the first American to win the award and 483 00:25:30,680 --> 00:25:35,280 Speaker 1: the first woman to win any astronomy award. So uh, 484 00:25:35,320 --> 00:25:37,720 Speaker 1: and some some places will say it's the first telescopic comment, 485 00:25:37,760 --> 00:25:41,840 Speaker 1: but I don't think that's true. But regardless, she became 486 00:25:41,880 --> 00:25:44,200 Speaker 1: one of America's first like science celebrities, or one of 487 00:25:44,240 --> 00:25:47,320 Speaker 1: America's early science celebrities, and she became a household name 488 00:25:47,320 --> 00:25:50,520 Speaker 1: for a while, and she stayed working at the Atheneum. 489 00:25:50,560 --> 00:25:53,639 Speaker 1: She also got computer work for nautical almanacs, which she 490 00:25:53,680 --> 00:25:56,480 Speaker 1: did for nineteen years. And she was the first woman 491 00:25:56,560 --> 00:25:59,960 Speaker 1: computer in the US, which is it's kind of impressive 492 00:26:00,160 --> 00:26:02,240 Speaker 1: that being the first woman computer in the US was 493 00:26:02,280 --> 00:26:05,000 Speaker 1: like the least impressive thing that she did in all 494 00:26:05,000 --> 00:26:08,280 Speaker 1: of the things that I'm talking about about her, because 495 00:26:08,280 --> 00:26:10,240 Speaker 1: that would have been enough, you know, like we would 496 00:26:10,240 --> 00:26:12,080 Speaker 1: be talking about her if that was what she had done. 497 00:26:12,680 --> 00:26:15,080 Speaker 1: She became a professor of astronomy at Vassar College in 498 00:26:15,160 --> 00:26:18,199 Speaker 1: upstate New York. And the reason that rules from my 499 00:26:18,280 --> 00:26:20,080 Speaker 1: point of view is that she did not have a degree. 500 00:26:20,320 --> 00:26:23,840 Speaker 1: But she started teaching as a professor at college, and 501 00:26:23,920 --> 00:26:26,560 Speaker 1: she immediately started turning it around in at least in 502 00:26:26,600 --> 00:26:30,080 Speaker 1: her classes. She abolished grades, she didn't track absences, she 503 00:26:30,160 --> 00:26:34,040 Speaker 1: dropped her class sizes, She refused to enforce social norms 504 00:26:34,040 --> 00:26:37,000 Speaker 1: on her female students, Like female students were supposed to 505 00:26:37,000 --> 00:26:39,000 Speaker 1: go out at night, and she would like hold classes 506 00:26:39,000 --> 00:26:40,879 Speaker 1: at night because they're supposed to look at the fucking stars, 507 00:26:40,960 --> 00:26:44,400 Speaker 1: you know. Yeah, how else would you study astronomy if 508 00:26:44,440 --> 00:26:47,240 Speaker 1: not at night? And I don't know, maybe like you're 509 00:26:47,240 --> 00:26:49,720 Speaker 1: supposed to be escorted by a man or something, you know, 510 00:26:49,760 --> 00:26:52,840 Speaker 1: but not alone because that would also be scandal. And 511 00:26:52,880 --> 00:26:56,159 Speaker 1: so she was such a popular teacher that Vassar College 512 00:26:56,200 --> 00:26:59,400 Speaker 1: was attracting more astronomy students than Harvard. And she took 513 00:26:59,440 --> 00:27:02,199 Speaker 1: the first real photos of the fucking sun, like in 514 00:27:02,280 --> 00:27:05,040 Speaker 1: order to track sun spots. She brought all kinds of 515 00:27:05,040 --> 00:27:07,680 Speaker 1: prestige to the college. Two men named a crater on 516 00:27:07,720 --> 00:27:11,560 Speaker 1: the moon after her, and eventually she realized this is 517 00:27:11,560 --> 00:27:13,879 Speaker 1: gonna shock you. Nothing like this has ever happened again. 518 00:27:14,640 --> 00:27:17,240 Speaker 1: She was getting less money. She was getting less than 519 00:27:17,320 --> 00:27:20,480 Speaker 1: half as much money as the men her male colleagues. 520 00:27:21,040 --> 00:27:27,200 Speaker 1: I'm shocked. I know, I was scandalous. She was getting 521 00:27:27,240 --> 00:27:29,560 Speaker 1: eight hundred dollars a year, plus room and board for 522 00:27:29,560 --> 00:27:33,119 Speaker 1: herself and her father, and that's about two dollars today. 523 00:27:33,240 --> 00:27:39,399 Speaker 1: Her male colleagues were getting plus room and boards, really 524 00:27:39,400 --> 00:27:41,879 Speaker 1: making a lot more than she was. Yeah, yeah, like 525 00:27:41,960 --> 00:27:44,040 Speaker 1: twice as much, more than twice as much, and am 526 00:27:44,119 --> 00:27:47,520 Speaker 1: twice as much. And she's like the biggest draw at 527 00:27:47,520 --> 00:27:52,240 Speaker 1: this fucking college. So and it's this long drawn out 528 00:27:52,320 --> 00:27:55,280 Speaker 1: fight where her in one of another woman professor have 529 00:27:55,400 --> 00:27:58,640 Speaker 1: to like file appeal after appeal, and then they had 530 00:27:58,680 --> 00:28:02,120 Speaker 1: to pass three entire provisions in order to get like 531 00:28:02,119 --> 00:28:04,119 Speaker 1: like that's how fucked up their system was that it 532 00:28:04,160 --> 00:28:06,959 Speaker 1: took three different provisions to get it fixed. But she 533 00:28:07,080 --> 00:28:10,919 Speaker 1: actually got guaranteed equal pay for women at Vassar College 534 00:28:10,920 --> 00:28:14,280 Speaker 1: in the eighteen seventies, which is the Equal Pay Act 535 00:28:14,280 --> 00:28:17,560 Speaker 1: wasn't signed until nineteen sixty three, and of course it's 536 00:28:17,600 --> 00:28:21,160 Speaker 1: now sixty years after that, and women overall earned eighty 537 00:28:21,200 --> 00:28:23,680 Speaker 1: three cents on the white male dollar. Black women earned 538 00:28:23,680 --> 00:28:26,440 Speaker 1: sixty four cents on the white male dollar, and Hispanic women, 539 00:28:26,480 --> 00:28:29,040 Speaker 1: which is the name the term used by this study. 540 00:28:29,080 --> 00:28:32,240 Speaker 1: I'm exciting, earned fifty seven cents on the white male dollar, 541 00:28:32,840 --> 00:28:36,719 Speaker 1: so ahead of her time, ahead of her time. And 542 00:28:36,760 --> 00:28:38,760 Speaker 1: also I have to just shout out that like she 543 00:28:38,920 --> 00:28:41,120 Speaker 1: it sounds like she wasn't just interested in getting equal 544 00:28:41,120 --> 00:28:43,720 Speaker 1: pay for herself, but for other women who came after her, 545 00:28:43,760 --> 00:28:46,720 Speaker 1: so really like lifting as she climbed, making sure that 546 00:28:46,760 --> 00:28:49,280 Speaker 1: she had a legacy. That wasn't just It would be 547 00:28:49,280 --> 00:28:51,480 Speaker 1: so easy to say, well, I got my equal pay 548 00:28:51,560 --> 00:28:54,480 Speaker 1: because I'm the superstar professor here and I'm not really 549 00:28:54,520 --> 00:28:56,640 Speaker 1: worried about women coming behind me. But she didn't do 550 00:28:56,680 --> 00:29:01,840 Speaker 1: that totally. And she also she stays involved in feminist politics. 551 00:29:02,000 --> 00:29:04,880 Speaker 1: She founds the American Association for the Advancement of Women, 552 00:29:05,000 --> 00:29:08,040 Speaker 1: serves as as president for two years. And then the 553 00:29:08,080 --> 00:29:09,840 Speaker 1: weirder part of what she did, at least from my 554 00:29:09,880 --> 00:29:12,240 Speaker 1: point of view, she corresponded a bunch with the Moby 555 00:29:12,280 --> 00:29:15,640 Speaker 1: Dick guy um and provide information about Nintucket for his book. 556 00:29:15,880 --> 00:29:17,320 Speaker 1: And he has he has a name. It's a term 557 00:29:17,320 --> 00:29:18,880 Speaker 1: in Melville but we all know his real name is 558 00:29:18,960 --> 00:29:27,400 Speaker 1: Moby Dick guy. Um, and then call me moby Dick. Sorry, okay, 559 00:29:28,000 --> 00:29:30,200 Speaker 1: it's fine. Well no, wait, wait and see if I 560 00:29:30,200 --> 00:29:32,040 Speaker 1: can do my favorite joke about this off top of 561 00:29:32,080 --> 00:29:34,960 Speaker 1: my head. So there's a fab assigned female at birth, 562 00:29:35,440 --> 00:29:38,760 Speaker 1: a mab assigned male at birth, a cab all cops 563 00:29:38,760 --> 00:29:41,800 Speaker 1: are bastards, and a hab from Hell's heart. I stab 564 00:29:41,840 --> 00:29:47,480 Speaker 1: at the thank you. Yeah pretty good. Yeah, I definitely 565 00:29:47,520 --> 00:29:50,320 Speaker 1: did not make that Radios five Stars and Apple podcast. 566 00:29:53,280 --> 00:29:55,920 Speaker 1: So okay. So she's friends with moby Dick guy and 567 00:29:55,920 --> 00:29:58,120 Speaker 1: then in her thirties, she's traveling around Italy in a 568 00:29:58,120 --> 00:30:00,640 Speaker 1: bunch of Europe doing all this astronomical word and she 569 00:30:00,680 --> 00:30:02,480 Speaker 1: does this thing where she's strong arms her way into 570 00:30:02,520 --> 00:30:05,840 Speaker 1: like the popes of the thing where you look at 571 00:30:05,880 --> 00:30:09,520 Speaker 1: the stars. I didn't write down this word in my observatory. 572 00:30:09,720 --> 00:30:11,800 Speaker 1: She's trying to get into the Pope's observatory and they're like, well, 573 00:30:11,800 --> 00:30:13,280 Speaker 1: you're a woman, you can't come in here. And he 574 00:30:13,640 --> 00:30:16,000 Speaker 1: she gets like special dispensation from the Pope to go 575 00:30:16,040 --> 00:30:19,040 Speaker 1: into the like no women allowed observatory. But the guy 576 00:30:19,120 --> 00:30:21,920 Speaker 1: she's bumming around with around Italy is the Scarlet letter 577 00:30:21,960 --> 00:30:24,920 Speaker 1: guy who also has another name, which is Nathaniel Hawthorne, 578 00:30:25,760 --> 00:30:28,240 Speaker 1: and they probably weren't fucking I know that's what you 579 00:30:28,280 --> 00:30:31,960 Speaker 1: were thinking. She described the Scarlet letter guy as not handsome, 580 00:30:32,000 --> 00:30:33,920 Speaker 1: but he looks as the author of his work should 581 00:30:33,960 --> 00:30:36,720 Speaker 1: look a little strange and odd, as if not point 582 00:30:36,720 --> 00:30:42,120 Speaker 1: of the earth out because all of his books and 583 00:30:42,160 --> 00:30:44,560 Speaker 1: short stories are like kind of creepy and weird. So 584 00:30:44,600 --> 00:30:46,040 Speaker 1: I it's like, oh, yeah, he looks at the kind 585 00:30:46,040 --> 00:30:49,560 Speaker 1: of guy who would write creepy, weird short stories as 586 00:30:49,600 --> 00:30:52,280 Speaker 1: he does. Yeah, he's a fucking edge lord. I'm gonna 587 00:30:52,320 --> 00:30:56,840 Speaker 1: get to them in that moment um. So she's actually 588 00:30:56,920 --> 00:31:00,520 Speaker 1: probably either gay or a sexual. And it's really hard 589 00:31:00,560 --> 00:31:03,880 Speaker 1: to figure that out about women, especially in the nineteenth century, 590 00:31:04,480 --> 00:31:07,680 Speaker 1: um whereas the Scarlet letter guy was absolutely gay for 591 00:31:07,800 --> 00:31:11,080 Speaker 1: Moby Dick Guy and vice versa. Melville once wrote about 592 00:31:11,080 --> 00:31:14,320 Speaker 1: his bud Nathan Already, I feel that Hawthorne has dropped 593 00:31:14,360 --> 00:31:18,080 Speaker 1: Germanist seeds into my soul. He expands and deepens down 594 00:31:18,160 --> 00:31:21,400 Speaker 1: the more I contemplate him, and further and further shoots 595 00:31:21,400 --> 00:31:24,719 Speaker 1: his strong New England roots into the hot soil of 596 00:31:24,760 --> 00:31:32,200 Speaker 1: my southern soul. The strong New England roots. This is 597 00:31:32,200 --> 00:31:33,720 Speaker 1: the only time I'm going to say I hope they 598 00:31:33,720 --> 00:31:38,440 Speaker 1: didn't funk about a gay couple, because the fucking Hawthorne 599 00:31:38,480 --> 00:31:41,400 Speaker 1: is a racist, little fucking edge lord. All of his 600 00:31:41,480 --> 00:31:44,960 Speaker 1: friends are Northern abolitionists. But he was like, no, we 601 00:31:45,000 --> 00:31:49,280 Speaker 1: can't risk breaking up the Union over slavery, whereas fucking 602 00:31:49,360 --> 00:31:51,920 Speaker 1: Melville wrote a whole last book about how shitty slavery 603 00:31:52,040 --> 00:31:54,400 Speaker 1: was ten years before the Civil War and then wrote 604 00:31:54,440 --> 00:31:56,960 Speaker 1: this like book of poems about how great all of 605 00:31:56,960 --> 00:31:59,240 Speaker 1: the people who went and fucking killed the Confederates are, 606 00:31:59,320 --> 00:32:02,240 Speaker 1: And so Melville was, I hope they broke up over that, 607 00:32:02,280 --> 00:32:04,200 Speaker 1: is what I'm trying to say. Oh my god, can 608 00:32:04,200 --> 00:32:07,840 Speaker 1: you imagine like the annoying ask conversations where Hawthorne's just like, 609 00:32:08,080 --> 00:32:11,040 Speaker 1: I'm just asking questions, I'm just playing Devil's advocate or 610 00:32:11,040 --> 00:32:14,160 Speaker 1: are you getting so upset? He is absolutely that guy. 611 00:32:14,320 --> 00:32:17,840 Speaker 1: That is him. I feel like I dated a guy 612 00:32:17,880 --> 00:32:26,240 Speaker 1: like that before. I'm sorry me too. So anyway back 613 00:32:26,240 --> 00:32:29,280 Speaker 1: to Maria. Two years before she died, she finally got 614 00:32:29,280 --> 00:32:32,120 Speaker 1: her degree, which was when Columbia University gave her an 615 00:32:32,120 --> 00:32:35,320 Speaker 1: honorary doctorate, And I like this especially because this is 616 00:32:35,360 --> 00:32:37,160 Speaker 1: my plan. I don't have a college degree. I just 617 00:32:37,240 --> 00:32:39,080 Speaker 1: want someone to fucking hand me one for being cool. 618 00:32:39,160 --> 00:32:43,520 Speaker 1: That is my long term plan. Anyway, that's that's Maria Mitchell, 619 00:32:43,560 --> 00:32:46,480 Speaker 1: America's first female computer, and I think she fucking ruled. 620 00:32:47,440 --> 00:32:49,800 Speaker 1: But while we're talking about words for how we describe people, 621 00:32:50,040 --> 00:32:52,360 Speaker 1: it turns out the words scientist was coined by a man, 622 00:32:52,480 --> 00:32:56,640 Speaker 1: William why Hill, to describe a specific woman, Mary Somerville, 623 00:32:57,160 --> 00:33:01,240 Speaker 1: to quote historian Maria Popova, The commonly used term up 624 00:33:01,280 --> 00:33:04,440 Speaker 1: to that point man of science clearly couldn't apply to 625 00:33:04,440 --> 00:33:07,280 Speaker 1: a woman, nor to what way will considered the peculiar 626 00:33:07,320 --> 00:33:10,959 Speaker 1: illumination of the female mind, the ability to synthesize ideas 627 00:33:10,960 --> 00:33:14,320 Speaker 1: and connect seemingly disparate disciplines into a clear lens on reality. 628 00:33:14,800 --> 00:33:17,200 Speaker 1: Because he couldn't call her a physicist, a geologist, or 629 00:33:17,240 --> 00:33:19,680 Speaker 1: a chemist. She had written with deep knowledge of all 630 00:33:19,720 --> 00:33:22,440 Speaker 1: of these disciplines and more way well unified them all 631 00:33:22,480 --> 00:33:25,720 Speaker 1: into scientists. Wow, I I this is so fascinating, And 632 00:33:25,760 --> 00:33:27,600 Speaker 1: I guess I have a question for the both of 633 00:33:27,640 --> 00:33:31,040 Speaker 1: you if that's okay, Like you know, time and time again, 634 00:33:31,160 --> 00:33:34,240 Speaker 1: I'll hear something where it's like, actually, this was first 635 00:33:34,240 --> 00:33:36,040 Speaker 1: coin to talk about a woman, or the first computer 636 00:33:36,160 --> 00:33:38,719 Speaker 1: was a woman. So this it blows my mind at 637 00:33:38,720 --> 00:33:41,840 Speaker 1: the first that the term scientists was coined to have 638 00:33:42,000 --> 00:33:44,760 Speaker 1: a you know, gender neutral way to talk about a 639 00:33:44,800 --> 00:33:47,200 Speaker 1: woman who practiced science. But why do you think this 640 00:33:47,360 --> 00:33:49,640 Speaker 1: history goes over looks? Like why is that not common 641 00:33:49,680 --> 00:33:52,520 Speaker 1: knowledge even to people who are interested in this kind 642 00:33:52,520 --> 00:33:55,880 Speaker 1: of thing. So if you want to go first, I mean, 643 00:33:55,960 --> 00:33:59,280 Speaker 1: because the patriarchy has had too much power for far 644 00:33:59,320 --> 00:34:02,760 Speaker 1: too long and it's depressing. But I feel like we're 645 00:34:02,760 --> 00:34:05,360 Speaker 1: finally fighting back on it enough where we're learning about 646 00:34:05,360 --> 00:34:07,040 Speaker 1: things that we should have known a long time ago. 647 00:34:07,440 --> 00:34:09,880 Speaker 1: And it's also that there's so many different ways to 648 00:34:09,920 --> 00:34:12,640 Speaker 1: communicate now, and so people that might have been afraid 649 00:34:12,719 --> 00:34:15,000 Speaker 1: to have spoken up face to face are able to 650 00:34:15,000 --> 00:34:20,480 Speaker 1: speak up on what they believe in a safer environment. M. Yeah, 651 00:34:20,520 --> 00:34:23,480 Speaker 1: that's interesting. I'm gonna go with that one. Wait now 652 00:34:23,520 --> 00:34:26,359 Speaker 1: I had another. I had another one too, though. Um 653 00:34:26,400 --> 00:34:28,080 Speaker 1: So I think that one of the things that happens 654 00:34:28,280 --> 00:34:31,120 Speaker 1: is that when you know, I get asked like why 655 00:34:31,120 --> 00:34:33,160 Speaker 1: does it matter if this person in history was gay? 656 00:34:33,480 --> 00:34:35,560 Speaker 1: Or like why does it matter that this person who 657 00:34:35,600 --> 00:34:38,000 Speaker 1: invented this thing or that thing was a woman or something. 658 00:34:38,080 --> 00:34:42,640 Speaker 1: Can it just be about the knowledge? And so because 659 00:34:43,160 --> 00:34:46,640 Speaker 1: because identity matters, basically, but people don't want to pretend 660 00:34:46,680 --> 00:34:48,680 Speaker 1: like identity matters, and so that's a way to kind 661 00:34:48,719 --> 00:34:51,000 Speaker 1: of keep us invisible. If like, any time a woman 662 00:34:51,040 --> 00:34:54,719 Speaker 1: does something, you're like, humanity did this thing. And and 663 00:34:54,760 --> 00:34:57,280 Speaker 1: that's also what people say when Aman does something. But 664 00:34:57,280 --> 00:34:59,040 Speaker 1: but if you don't draw attention to the fact that 665 00:34:59,080 --> 00:35:01,759 Speaker 1: someone who has been silenced and shut up and had 666 00:35:01,760 --> 00:35:05,759 Speaker 1: to overcome systemic barriers because of you know, race or 667 00:35:05,800 --> 00:35:08,640 Speaker 1: gender or sexual orientation or whatever, I don't know. That's 668 00:35:08,680 --> 00:35:11,680 Speaker 1: that's my take. Yeah, I think that's so true. And 669 00:35:11,719 --> 00:35:14,840 Speaker 1: I think of all the ways that different people have 670 00:35:15,080 --> 00:35:17,960 Speaker 1: spent further people who are already marginalized are like further 671 00:35:18,160 --> 00:35:21,239 Speaker 1: marginalized by the way that we tell their stories or 672 00:35:21,280 --> 00:35:23,680 Speaker 1: don't tell their stories. Like I'm a huge fan of 673 00:35:23,680 --> 00:35:25,600 Speaker 1: the painter Freed to Carlo. I didn't know she had 674 00:35:25,600 --> 00:35:28,759 Speaker 1: a disability until like recently, because we don't think of, 675 00:35:29,080 --> 00:35:30,880 Speaker 1: you know, her story as being like a story of 676 00:35:30,920 --> 00:35:33,680 Speaker 1: disability justice. Right, Like all the different ways that like 677 00:35:34,200 --> 00:35:37,640 Speaker 1: these pieces of our identity, that things that make us 678 00:35:37,640 --> 00:35:40,319 Speaker 1: who we are and inform our experiences and all of that. 679 00:35:40,800 --> 00:35:44,240 Speaker 1: We are just unseen, and if we're unseen, it takes 680 00:35:44,239 --> 00:35:46,000 Speaker 1: away our power. I think it's I think the work 681 00:35:46,040 --> 00:35:49,400 Speaker 1: that you're doing to like retell these stories and like 682 00:35:49,600 --> 00:35:52,600 Speaker 1: make them gay, make them queer, make them who they were, 683 00:35:52,719 --> 00:35:55,680 Speaker 1: I think is so important and powerful. I think we're 684 00:35:55,719 --> 00:35:59,320 Speaker 1: also a like world of headlines. We read the headline, 685 00:35:59,320 --> 00:36:02,239 Speaker 1: we don't actually read the article. We don't actually read 686 00:36:02,280 --> 00:36:05,000 Speaker 1: the article. People read the the snazzy headline. I think 687 00:36:05,080 --> 00:36:07,560 Speaker 1: that was the same since the beginning of time. You 688 00:36:07,640 --> 00:36:10,200 Speaker 1: don't actually do the work to find out the information. 689 00:36:10,320 --> 00:36:14,080 Speaker 1: And and like, I feel like shows like this where 690 00:36:14,080 --> 00:36:17,040 Speaker 1: we're going and you're learning all these things are so 691 00:36:17,239 --> 00:36:21,719 Speaker 1: vital to our story as as as people. Yeah, And 692 00:36:21,760 --> 00:36:23,759 Speaker 1: it's like and the people who are writing those headlines 693 00:36:24,200 --> 00:36:26,920 Speaker 1: are going to come at it with their biases. Whereas 694 00:36:27,000 --> 00:36:28,920 Speaker 1: you know, when I write short, when I do a 695 00:36:29,000 --> 00:36:31,520 Speaker 1: very quick version of someone's story, I'm absolutely going to 696 00:36:31,600 --> 00:36:34,759 Speaker 1: be like, and he loved fucking dudes, you know, because 697 00:36:34,760 --> 00:36:36,600 Speaker 1: it's not going to get included and the other versions 698 00:36:36,600 --> 00:36:38,680 Speaker 1: of the story, even though that makes no sense, It 699 00:36:38,719 --> 00:36:41,360 Speaker 1: makes no sense to disclude that. And I mean you know. 700 00:36:41,400 --> 00:36:43,000 Speaker 1: I mean it guess depends what you're talking about, like 701 00:36:43,000 --> 00:36:45,400 Speaker 1: maybe not like if I'm talking about someone who, like, 702 00:36:45,760 --> 00:36:48,520 Speaker 1: I don't know, runs a gay bar, like maybe like 703 00:36:48,880 --> 00:36:51,560 Speaker 1: maybe that's implicit, you know that maybe instead of like 704 00:36:51,719 --> 00:36:54,760 Speaker 1: and he was a sexual I don't know. Anyway, writing 705 00:36:54,840 --> 00:36:59,319 Speaker 1: us back into history it's important and so so after 706 00:36:59,360 --> 00:37:03,439 Speaker 1: Maria Mitchell, it wasn't too long before computing became women's work. 707 00:37:03,760 --> 00:37:05,640 Speaker 1: And actually a lot of the early computers I think 708 00:37:05,719 --> 00:37:08,160 Speaker 1: came from her students, basically because she was teaching so 709 00:37:08,200 --> 00:37:11,080 Speaker 1: many women astronomy. And that's something else that also gets 710 00:37:11,160 --> 00:37:13,400 Speaker 1: left out is that you know, you have this like 711 00:37:13,520 --> 00:37:17,320 Speaker 1: individual genius who discovers ideas, whereas teaching isn't as important. 712 00:37:17,360 --> 00:37:19,200 Speaker 1: And and that's actually something that come up a lot, 713 00:37:19,840 --> 00:37:22,400 Speaker 1: comes up a lot in terms of I think women 714 00:37:22,400 --> 00:37:26,600 Speaker 1: in particular breaking through boundaries is that we like teach 715 00:37:26,640 --> 00:37:29,839 Speaker 1: each other and we we take people along with us, 716 00:37:29,840 --> 00:37:31,840 Speaker 1: like what you were talking about earlier about like not 717 00:37:32,040 --> 00:37:35,120 Speaker 1: I got mine, fuck you? You know, So computing becomes 718 00:37:35,120 --> 00:37:38,520 Speaker 1: women's work, and eventually black women's work in particular first 719 00:37:38,560 --> 00:37:40,879 Speaker 1: and foremost, because you can get away with paying women 720 00:37:40,920 --> 00:37:45,000 Speaker 1: less than men. Harvard observatory starting in eighteen seventy seven, 721 00:37:45,160 --> 00:37:47,879 Speaker 1: was excited to maximize their budget. There's there's so many 722 00:37:47,960 --> 00:37:50,360 Speaker 1: numbers they have to crunch, and they could pay women 723 00:37:51,239 --> 00:37:53,840 Speaker 1: cents to fifty cents an hour, or roughly seven to 724 00:37:53,920 --> 00:37:57,800 Speaker 1: fourteen dollars an hour in today's wages. So for decades, 725 00:37:57,960 --> 00:38:00,200 Speaker 1: these people who are doing all of the important, like 726 00:38:00,360 --> 00:38:04,520 Speaker 1: crazy complicated math, we're getting paid seven dollars an hour. Uh, 727 00:38:04,640 --> 00:38:08,560 Speaker 1: to quote that writer Maria Popova again. Decades before they 728 00:38:08,560 --> 00:38:11,280 Speaker 1: were allowed to vote. In a century before NASA's unheralded 729 00:38:11,320 --> 00:38:13,719 Speaker 1: women mathematicians helped put the first man on the moon. 730 00:38:14,160 --> 00:38:16,080 Speaker 1: These women, who came to be known as the quote 731 00:38:16,120 --> 00:38:20,400 Speaker 1: Harvard computers illuminated the composition of stars and classified hundreds 732 00:38:20,440 --> 00:38:22,920 Speaker 1: of thousands of stars according to a system they invented, 733 00:38:23,120 --> 00:38:27,080 Speaker 1: which astronomers continue to use today. Their calculations became the 734 00:38:27,080 --> 00:38:30,719 Speaker 1: basis for the discovery that the universe is expanding. So 735 00:38:30,760 --> 00:38:32,720 Speaker 1: that's what they're So I'm like, oh, they're just crunching 736 00:38:32,800 --> 00:38:36,719 Speaker 1: numbers and discovering that the universe is expanding, and you know, 737 00:38:37,800 --> 00:38:42,240 Speaker 1: learning how to classify stars. Yeah, not actual like stuff 738 00:38:42,280 --> 00:38:47,520 Speaker 1: that would involve you know, analytical thinking or totally the 739 00:38:47,600 --> 00:38:51,320 Speaker 1: secretarial work really yea. And so this goes on for decades, 740 00:38:51,360 --> 00:38:54,160 Speaker 1: and I actually didn't find in a quick search. I 741 00:38:54,200 --> 00:38:56,040 Speaker 1: wasn't able to find the end date of when Harvard's 742 00:38:56,040 --> 00:38:58,040 Speaker 1: computers came to an end, but it ran up until 743 00:38:58,040 --> 00:39:02,440 Speaker 1: at least seven was the one person I specifically tracked 744 00:39:02,440 --> 00:39:05,200 Speaker 1: her employment at that and I think it probably lasted 745 00:39:05,280 --> 00:39:08,080 Speaker 1: until the era of the electronic computer. But I prefer 746 00:39:08,120 --> 00:39:10,640 Speaker 1: to think that they're still there, hopefully better paid doing 747 00:39:10,680 --> 00:39:13,480 Speaker 1: astronomical math by hand, just like some weird caball of 748 00:39:14,120 --> 00:39:18,920 Speaker 1: people hanging out at Harvard, I don't know. So, so 749 00:39:19,080 --> 00:39:21,400 Speaker 1: women started working as computers because they were cheaper to 750 00:39:21,480 --> 00:39:24,920 Speaker 1: hire than During World War Two, computing and programming were 751 00:39:24,920 --> 00:39:27,080 Speaker 1: cemented as women's work because all the boys were off 752 00:39:27,120 --> 00:39:30,600 Speaker 1: at war. So then some women's supervisors come in, like 753 00:39:30,719 --> 00:39:34,160 Speaker 1: Macy Roberts, who oversaw California's Jet Propulsion Laboratory in the 754 00:39:34,239 --> 00:39:37,080 Speaker 1: nineteen forties, which is later part of NASA and designed 755 00:39:37,120 --> 00:39:39,760 Speaker 1: the first artificial satellite that the US ever put in space. 756 00:39:40,719 --> 00:39:43,359 Speaker 1: And she hired only women because she thought it made 757 00:39:43,360 --> 00:39:46,759 Speaker 1: for a more cohesive team and teamwork focused group and 758 00:39:46,880 --> 00:39:49,400 Speaker 1: the way that they would code. Women can apply to 759 00:39:49,440 --> 00:39:52,759 Speaker 1: this job into job applications because they couldn't say, hey, 760 00:39:52,800 --> 00:39:57,719 Speaker 1: women can apply to so they would say no degree necessary, Oh, 761 00:39:57,840 --> 00:40:01,840 Speaker 1: I like that. And so this attitude of hiring women spread, 762 00:40:01,880 --> 00:40:05,920 Speaker 1: and soon women were calculating everything from the lift for 763 00:40:06,080 --> 00:40:09,960 Speaker 1: World War two bombers to rocket paths. And of course, 764 00:40:10,040 --> 00:40:11,960 Speaker 1: as cool as looking at the stars is, it's even 765 00:40:12,000 --> 00:40:13,920 Speaker 1: cooler to figure how to reach them and reach out 766 00:40:13,960 --> 00:40:17,319 Speaker 1: and touch them, which brings us to Dorothy Vaughn. But 767 00:40:17,640 --> 00:40:21,120 Speaker 1: before we talk about Dorothy Vaughn, we need to talk 768 00:40:21,160 --> 00:40:24,839 Speaker 1: about never talked to cops. The sponsor of this show. 769 00:40:25,200 --> 00:40:27,359 Speaker 1: The sponsor of the show is shut the funk up. 770 00:40:27,360 --> 00:40:29,319 Speaker 1: It doesn't do you any good. Ever, you'd always think 771 00:40:29,320 --> 00:40:31,360 Speaker 1: it's going to do you good, but it doesn't. It 772 00:40:31,400 --> 00:40:37,160 Speaker 1: does not. Yeah, as well as potatoes, I really like potatoes. 773 00:40:37,160 --> 00:40:42,399 Speaker 1: I'm gonna keep hitting good, good, comb and water. I'd 774 00:40:42,440 --> 00:40:44,799 Speaker 1: like to throw out songs that are nostalgic in a 775 00:40:44,840 --> 00:40:48,719 Speaker 1: good way. Yes, that is what we are as a concept. Yes, 776 00:40:49,960 --> 00:40:58,239 Speaker 1: as well as these other things. And we are back 777 00:40:58,360 --> 00:41:00,600 Speaker 1: and we're talking about Dorothy Vaughn was black woman who 778 00:41:00,680 --> 00:41:03,279 Speaker 1: was born in nineteen ten in Missouri. But then moved 779 00:41:03,320 --> 00:41:05,880 Speaker 1: at age seven to West Virginia, kicked ass in school, 780 00:41:06,000 --> 00:41:10,439 Speaker 1: kicked ass in college at Wilberforce University, historically black university, 781 00:41:10,600 --> 00:41:12,960 Speaker 1: and then decided not to go to grad school but 782 00:41:12,960 --> 00:41:15,080 Speaker 1: instead of teach math in high school because the Great 783 00:41:15,120 --> 00:41:18,600 Speaker 1: Depression hit and her family really needed the money, especially 784 00:41:18,640 --> 00:41:20,440 Speaker 1: if her sister was going to get to go to 785 00:41:20,520 --> 00:41:26,120 Speaker 1: college too. In one President Roosevelt desegregated the defense industry, 786 00:41:26,200 --> 00:41:29,400 Speaker 1: which like sort of he sort of desegregated it. He like, 787 00:41:29,680 --> 00:41:31,520 Speaker 1: I think on a federal level he disegregated it, but 788 00:41:31,520 --> 00:41:34,640 Speaker 1: didn't get disegregated at a state level. But it allowed 789 00:41:34,640 --> 00:41:36,799 Speaker 1: black people to start working on the war effort at home. 790 00:41:37,280 --> 00:41:41,200 Speaker 1: So so NAKA, the precursor of NASA, went about hiring 791 00:41:41,239 --> 00:41:43,719 Speaker 1: black women in their quest to make airplanes because they 792 00:41:43,719 --> 00:41:46,359 Speaker 1: were trying to ramp up the US's production from three 793 00:41:46,440 --> 00:41:49,080 Speaker 1: thousand airplanes a year to fifty thousand airplanes a year 794 00:41:49,480 --> 00:41:53,560 Speaker 1: with the slogan victory through air power, and Vaughan left 795 00:41:53,560 --> 00:41:56,280 Speaker 1: teaching and started doing sky math and space math instead, 796 00:41:56,400 --> 00:41:58,880 Speaker 1: even though she'd never flown on an airplane, which fucking 797 00:41:59,000 --> 00:42:01,200 Speaker 1: rules doesn't rule that she never got to flying. The 798 00:42:01,280 --> 00:42:03,719 Speaker 1: play I'm sure she did eventually, but fucking rules that 799 00:42:03,760 --> 00:42:06,839 Speaker 1: she did Space Math and she's one of the She's 800 00:42:06,880 --> 00:42:10,839 Speaker 1: one of the characters in the Hidden Figures, the book 801 00:42:10,880 --> 00:42:14,480 Speaker 1: and then the movie that is really cool and people 802 00:42:14,520 --> 00:42:19,840 Speaker 1: should see. I think it's um Octavia Spencer is her 803 00:42:20,080 --> 00:42:23,279 Speaker 1: plays her character Ma from the movie Mam You've ever 804 00:42:23,320 --> 00:42:26,720 Speaker 1: seen that? I haven't. No. I liked all the actors 805 00:42:26,719 --> 00:42:29,719 Speaker 1: in that movie so much. I have, but exactly what 806 00:42:29,840 --> 00:42:37,360 Speaker 1: you're talking. Octavia is a phenomenal actress. She's so good, 807 00:42:37,640 --> 00:42:40,480 Speaker 1: she's she's fantastic. I personally think she should be cast 808 00:42:40,480 --> 00:42:46,080 Speaker 1: in every movie, just every movie. I think, yeah, maybe 809 00:42:46,080 --> 00:42:50,200 Speaker 1: every character. We got a Ma reference on. This is amazing. 810 00:42:50,400 --> 00:42:53,200 Speaker 1: You know, I saw my opening night in the theater 811 00:42:53,400 --> 00:42:54,960 Speaker 1: drunk and it was one of the best nights of 812 00:42:55,000 --> 00:42:59,160 Speaker 1: my life. Ted out of ten. I love that for you. 813 00:43:01,800 --> 00:43:04,440 Speaker 1: I love that. I have no idea. I have no 814 00:43:04,480 --> 00:43:06,000 Speaker 1: idea what you're talking about. I live under a rock, 815 00:43:06,280 --> 00:43:12,160 Speaker 1: imbarrass I just don't know about ship. You could ask 816 00:43:12,200 --> 00:43:14,239 Speaker 1: me low brush just gonna go over my head to this. 817 00:43:14,800 --> 00:43:17,200 Speaker 1: There was a low brow one last one we recorded that. 818 00:43:18,320 --> 00:43:21,400 Speaker 1: It's so funny working with with Margaret and Robert Evans. 819 00:43:21,440 --> 00:43:26,160 Speaker 1: They don't know, they don't know anything. It's great, it's rushing. 820 00:43:26,239 --> 00:43:28,440 Speaker 1: It makes me feel better and also feel worse at 821 00:43:28,440 --> 00:43:35,320 Speaker 1: the same time. So anyways, before we were all making 822 00:43:35,360 --> 00:43:39,279 Speaker 1: fun of me. Now I'm just kidding. Alright. So, so 823 00:43:39,360 --> 00:43:41,200 Speaker 1: after the war, a lot of the white women went 824 00:43:41,239 --> 00:43:44,279 Speaker 1: back home, but most of the black women stayed for 825 00:43:44,320 --> 00:43:45,920 Speaker 1: a lot of reasons, one of which I believe was 826 00:43:45,920 --> 00:43:48,160 Speaker 1: that they were basically earning about four times as much 827 00:43:48,200 --> 00:43:50,520 Speaker 1: as they would if even though they were getting paid 828 00:43:50,560 --> 00:43:53,000 Speaker 1: way less than the men, they were still getting paid 829 00:43:53,160 --> 00:43:55,719 Speaker 1: way more than they were as black school teachers, and 830 00:43:55,920 --> 00:43:59,720 Speaker 1: you know, especially in racially segregated schools. I believe Duchess 831 00:43:59,719 --> 00:44:01,920 Speaker 1: Hair is the granddaughter of one of the black computers 832 00:44:01,920 --> 00:44:04,759 Speaker 1: at NASA, and she wrote a book called Hidden Human Computers, 833 00:44:05,080 --> 00:44:08,120 Speaker 1: which came out around the same time as Shadowley's book 834 00:44:08,160 --> 00:44:10,840 Speaker 1: Hidden Figures, which is the one that became a movie. 835 00:44:11,080 --> 00:44:13,880 Speaker 1: But they I was like really confused because there's two 836 00:44:13,880 --> 00:44:15,839 Speaker 1: books with basically the same name, But they actually were 837 00:44:15,840 --> 00:44:17,839 Speaker 1: working on the books around the same time, and they 838 00:44:17,840 --> 00:44:19,640 Speaker 1: cover sort of different topics, and they ended up kind 839 00:44:19,640 --> 00:44:22,400 Speaker 1: of teaming up on like going to NASA to do 840 00:44:22,440 --> 00:44:23,960 Speaker 1: some of their like tours and stuff together. So it 841 00:44:23,960 --> 00:44:25,840 Speaker 1: actually became a really cool story about the two books 842 00:44:25,840 --> 00:44:28,240 Speaker 1: as compared to how it first appears. When you realize 843 00:44:28,239 --> 00:44:29,560 Speaker 1: that there's two books that came at the same time 844 00:44:29,600 --> 00:44:31,680 Speaker 1: with the same name. That's my long tangent about the 845 00:44:31,680 --> 00:44:35,279 Speaker 1: two books. So Duchess Harris, when she's interviewed about the 846 00:44:35,320 --> 00:44:39,400 Speaker 1: Black computers and and race relations, she says, this is 847 00:44:39,400 --> 00:44:41,960 Speaker 1: not a story of healing race relations. The government was 848 00:44:42,000 --> 00:44:44,480 Speaker 1: desperate for help. These black women were hired as a 849 00:44:44,560 --> 00:44:46,759 Speaker 1: last resort when they ran out of white women. The 850 00:44:46,800 --> 00:44:49,239 Speaker 1: government wanted to win the war and later to put 851 00:44:49,280 --> 00:44:51,719 Speaker 1: an American in space after the Russians launched spot Nick 852 00:44:51,760 --> 00:44:55,160 Speaker 1: in ninety seven. So a lot of the like feel 853 00:44:55,200 --> 00:45:00,800 Speaker 1: good stuff, you know. Yeah, I mean the movie Hidden Figures, 854 00:45:01,040 --> 00:45:02,640 Speaker 1: it really makes it. I don't know if you all 855 00:45:02,640 --> 00:45:04,799 Speaker 1: have seen it, but it really goes out of its 856 00:45:04,840 --> 00:45:08,920 Speaker 1: way to suggest that, like this was about feel good equality. 857 00:45:08,960 --> 00:45:12,000 Speaker 1: Like there's a scene where, um, the white man who's 858 00:45:12,080 --> 00:45:15,080 Speaker 1: running their lab, I want to say, it's a it's 859 00:45:15,120 --> 00:45:20,239 Speaker 1: a famous dude. Yeah, he's portrayed by Kevin Costner. Costner, Yeah, yeah, 860 00:45:20,280 --> 00:45:23,160 Speaker 1: like he like thought but the women are having to 861 00:45:23,239 --> 00:45:25,120 Speaker 1: like walk very far away to go to the bathroom 862 00:45:25,160 --> 00:45:28,680 Speaker 1: because it's a segregated bathroom, and he dramatically like, Harrison 863 00:45:28,840 --> 00:45:32,760 Speaker 1: is the name of the character, thank you? Yeah. Uh. 864 00:45:32,840 --> 00:45:36,360 Speaker 1: He dramatically like takes the whites only sign off of 865 00:45:36,400 --> 00:45:38,600 Speaker 1: the bathroom to be like, no, we can use any 866 00:45:38,600 --> 00:45:42,040 Speaker 1: bathroom you want. And I think I like the movie 867 00:45:42,040 --> 00:45:45,960 Speaker 1: and I like this sort of like warm, fuzzy equality stuff, 868 00:45:46,280 --> 00:45:50,759 Speaker 1: but it does obscure the reality that you Margaret just 869 00:45:50,840 --> 00:45:54,279 Speaker 1: said that, like they were trying to win. This was 870 00:45:54,680 --> 00:45:56,160 Speaker 1: you know, I think it really goes back to this 871 00:45:56,200 --> 00:45:59,480 Speaker 1: idea of like, you know, nationalism can be kind of 872 00:45:59,520 --> 00:46:02,440 Speaker 1: an oppressed system that doesn't really see you when it's 873 00:46:02,480 --> 00:46:06,440 Speaker 1: not really interested in your inequality or like seeing you 874 00:46:06,480 --> 00:46:08,480 Speaker 1: as an individual or a person. And so, you know, 875 00:46:08,520 --> 00:46:10,520 Speaker 1: against that backdrop, it was like, yeah, it was we 876 00:46:10,600 --> 00:46:14,040 Speaker 1: wanted to win. We wanted to you know, further our 877 00:46:14,400 --> 00:46:18,400 Speaker 1: nationalist agenda, and these people were useful to us, and 878 00:46:18,440 --> 00:46:22,360 Speaker 1: so we quote cared about them insofar as they were useful. 879 00:46:22,480 --> 00:46:28,080 Speaker 1: Their labor was useful. Uh yeah, these systems don't see us. Yeah. Uh. 880 00:46:28,120 --> 00:46:30,720 Speaker 1: When I found out what actually happened with the the 881 00:46:30,800 --> 00:46:33,279 Speaker 1: segregation signs and the people who actually did that work. 882 00:46:33,320 --> 00:46:37,279 Speaker 1: I'm gonna get to that in a moment. Okay. Oh no, yeah, no, 883 00:46:37,360 --> 00:46:39,959 Speaker 1: I like I knew some of it before I watched 884 00:46:40,000 --> 00:46:42,520 Speaker 1: the movie. I watched the movie as part of preparing 885 00:46:42,520 --> 00:46:45,359 Speaker 1: the script, and I read some articles about it before 886 00:46:45,360 --> 00:46:46,920 Speaker 1: about some of the stuff it gets right and wrong. 887 00:46:47,719 --> 00:46:50,359 Speaker 1: But um, I don't know. I still really like the movie, 888 00:46:50,480 --> 00:46:54,279 Speaker 1: but with especially that scene. Okay. So a lot of 889 00:46:54,320 --> 00:46:57,359 Speaker 1: Dorothy Vaughan's career gets talked about in Hidden Figures, which 890 00:46:57,400 --> 00:46:59,920 Speaker 1: focuses on three black women who got the first uss 891 00:47:00,120 --> 00:47:02,840 Speaker 1: not into space, and it a lot of it's true, 892 00:47:02,920 --> 00:47:05,880 Speaker 1: although it skims over Vaughan's own math genius. It mostly 893 00:47:05,880 --> 00:47:08,200 Speaker 1: talks about her as like a supervisor. Right, but she 894 00:47:08,239 --> 00:47:10,520 Speaker 1: helped write the manuals and set the standards for all 895 00:47:10,560 --> 00:47:14,319 Speaker 1: of the computers at NAKA, and she worked in the 896 00:47:14,320 --> 00:47:17,359 Speaker 1: West Area Computing Unit, which was a segregated black unit. 897 00:47:18,120 --> 00:47:21,319 Speaker 1: When her white supervisor died in ninety nine, she became 898 00:47:21,360 --> 00:47:24,319 Speaker 1: acting supervisor, and it took two years for that to 899 00:47:24,360 --> 00:47:26,120 Speaker 1: be made official and for her to get the raise 900 00:47:26,200 --> 00:47:29,080 Speaker 1: that should have come along with the increase of responsibility. 901 00:47:29,760 --> 00:47:32,960 Speaker 1: And she was naka's first black supervisor and one of 902 00:47:33,440 --> 00:47:36,920 Speaker 1: one of the only women supervisors, but as a supervisor, 903 00:47:36,960 --> 00:47:39,239 Speaker 1: she intervened to fight for promotions and pay raises for 904 00:47:39,280 --> 00:47:42,560 Speaker 1: all women computers, both both black and white. And when 905 00:47:42,640 --> 00:47:46,320 Speaker 1: NACA became NASA Night, it desegregated the West End Computing 906 00:47:46,440 --> 00:47:49,319 Speaker 1: Unit and integrated the rest of NASA, and she then 907 00:47:49,400 --> 00:47:54,160 Speaker 1: joined a race and gender diverse division working on electronic computing. 908 00:47:54,200 --> 00:47:56,680 Speaker 1: She taught herself the programming language for TROUN and then 909 00:47:56,719 --> 00:47:59,560 Speaker 1: taught it to all her co workers. She fucking ruled 910 00:48:00,080 --> 00:48:05,040 Speaker 1: UM and West Area computers ran from eight They got 911 00:48:05,040 --> 00:48:08,040 Speaker 1: paid an awful lot less than the men. The The 912 00:48:08,120 --> 00:48:10,200 Speaker 1: article I read implied that they were paid the same 913 00:48:10,200 --> 00:48:13,399 Speaker 1: as white women. I don't know, but women in general 914 00:48:13,480 --> 00:48:15,880 Speaker 1: were getting paid a salary, a starting salary, but the 915 00:48:15,920 --> 00:48:19,120 Speaker 1: equivalent of twenty three thousand dollars a year in today's money, 916 00:48:19,200 --> 00:48:22,359 Speaker 1: whereas men were getting a starting salary at forty dollars 917 00:48:22,400 --> 00:48:25,880 Speaker 1: a year, which, like Jesus, not only that disparity, but 918 00:48:25,960 --> 00:48:30,000 Speaker 1: also like damn, even the men are getting fucking ripped off. Yeah, 919 00:48:30,080 --> 00:48:35,720 Speaker 1: everyone's getting exploited here. It's like I know that they're working, 920 00:48:35,800 --> 00:48:38,000 Speaker 1: they're not working eight hour days and then going home. 921 00:48:38,239 --> 00:48:40,719 Speaker 1: You know, but they make about four times as much 922 00:48:41,000 --> 00:48:43,319 Speaker 1: the black women working, and NASA are making about four 923 00:48:43,320 --> 00:48:46,040 Speaker 1: times as much as they would be elsewhere, which doesn't 924 00:48:46,040 --> 00:48:49,640 Speaker 1: make the fucking pay balance not fucked up. It really 925 00:48:49,680 --> 00:48:52,520 Speaker 1: just shows how fucked up everything is, you know, all 926 00:48:52,520 --> 00:48:55,719 Speaker 1: the way down. So Hidden Figures is all about the 927 00:48:55,719 --> 00:48:58,760 Speaker 1: segregated bathrooms. That's one of the main points of tension 928 00:48:58,800 --> 00:49:02,520 Speaker 1: in the story. And Kevin Costner comes and I'm sorry, 929 00:49:02,560 --> 00:49:04,080 Speaker 1: I'm reading this all my script, even we just talked 930 00:49:04,080 --> 00:49:05,759 Speaker 1: about it. But I don't know how to skim fast enough. 931 00:49:06,680 --> 00:49:08,360 Speaker 1: So he gets out of crowb already ripped down the 932 00:49:08,400 --> 00:49:10,960 Speaker 1: colored women's restroom sign and he announces, in the worst 933 00:49:11,000 --> 00:49:13,000 Speaker 1: line in the entire movie, we all pe the same 934 00:49:13,040 --> 00:49:17,680 Speaker 1: color here at NASA. I forgot about that. It is bad, 935 00:49:18,520 --> 00:49:21,719 Speaker 1: not good, I know. And the thing is, there was 936 00:49:21,800 --> 00:49:24,799 Speaker 1: someone ripping down segregation signs during the Naka years when 937 00:49:24,800 --> 00:49:27,960 Speaker 1: the place was segregated, a black woman who worked as 938 00:49:27,960 --> 00:49:32,839 Speaker 1: a computer named Miriam Mann. She was actually the grandmother 939 00:49:32,960 --> 00:49:35,200 Speaker 1: of this the woman I was saying who wrote this book. 940 00:49:36,320 --> 00:49:38,759 Speaker 1: So Miriam Man is all of four ft eleven, so 941 00:49:38,840 --> 00:49:42,960 Speaker 1: her friends call her Big Mama, and there's separate tables 942 00:49:42,960 --> 00:49:44,719 Speaker 1: at the back of the dining hall that are marked 943 00:49:44,719 --> 00:49:47,280 Speaker 1: with a sign that say colored computers. And Miriam didn't 944 00:49:47,320 --> 00:49:50,000 Speaker 1: like that. So finally one day she stole the sign 945 00:49:50,000 --> 00:49:52,080 Speaker 1: put it in her purse. The next day they put 946 00:49:52,080 --> 00:49:53,799 Speaker 1: the sign back, so she stole let it a kid, 947 00:49:54,920 --> 00:49:56,640 Speaker 1: And so she just did this over and over and 948 00:49:56,680 --> 00:49:58,959 Speaker 1: over again before they just stopped putting the sign back. 949 00:50:00,080 --> 00:50:02,640 Speaker 1: I don't know. And so the fact that that, particularly 950 00:50:02,640 --> 00:50:04,319 Speaker 1: because it's already kind of bad that it's a white 951 00:50:04,320 --> 00:50:07,600 Speaker 1: savior move, to have Kevin Costner come to it, it's 952 00:50:07,640 --> 00:50:09,520 Speaker 1: an extra little dig that it was a black woman 953 00:50:09,560 --> 00:50:13,000 Speaker 1: who did it. Yeah, I mean what, like, I I 954 00:50:13,520 --> 00:50:16,439 Speaker 1: know all the like I bet I can imagine some 955 00:50:16,719 --> 00:50:20,440 Speaker 1: Hollywood studio somewhere being like, we have to make Kevin Costner, 956 00:50:20,640 --> 00:50:22,920 Speaker 1: we have to give him this like dramatic moment to 957 00:50:23,000 --> 00:50:26,319 Speaker 1: have him be the like savior, the ally YadA YadA YadA. 958 00:50:26,320 --> 00:50:29,839 Speaker 1: I get it. But like, imagine if they depicted a 959 00:50:29,880 --> 00:50:32,440 Speaker 1: truth a more truthful version of that scene and had 960 00:50:32,480 --> 00:50:35,560 Speaker 1: it be Big Mama who did it, Like I don't know, 961 00:50:35,640 --> 00:50:37,799 Speaker 1: like what would be the I don't know, I just 962 00:50:37,920 --> 00:50:42,799 Speaker 1: I know how Hollywood thinks, But it would have been 963 00:50:42,920 --> 00:50:45,439 Speaker 1: that much more authentic and powerful to have a black 964 00:50:45,480 --> 00:50:48,000 Speaker 1: woman be the person who who did that, because also 965 00:50:48,440 --> 00:50:50,680 Speaker 1: like it would honor the fact that doing that took 966 00:50:50,719 --> 00:50:53,400 Speaker 1: a lot of risk and a lot of like gumph 967 00:50:53,600 --> 00:50:57,200 Speaker 1: and hutzpah. You know, like it's sort of races that 968 00:50:57,200 --> 00:50:59,400 Speaker 1: that fact, Like having a white the white guy who's 969 00:50:59,440 --> 00:51:02,839 Speaker 1: running ship do it, it's not as cool as having 970 00:51:02,880 --> 00:51:05,239 Speaker 1: the black woman with everything to lose do it. But 971 00:51:05,320 --> 00:51:07,719 Speaker 1: that's what happened, Like the like the reality is more 972 00:51:07,800 --> 00:51:11,080 Speaker 1: badass than the Hollywood version, totally, yeah, because he's taking 973 00:51:11,120 --> 00:51:17,720 Speaker 1: no risk and exactly. Yeah, And apparently her husband was like, honey, 974 00:51:17,800 --> 00:51:19,920 Speaker 1: probably shouldn't do that. You're gonna get fired and we 975 00:51:19,960 --> 00:51:23,240 Speaker 1: need this job, you know. Um, And she was like, 976 00:51:23,160 --> 00:51:25,560 Speaker 1: I can't fucking know. I'm taking this fucking sign. You know. 977 00:51:25,600 --> 00:51:28,040 Speaker 1: It's this thing that like seems like a little petty 978 00:51:28,160 --> 00:51:31,680 Speaker 1: thing like had it's mischief. I stole the side, you know, 979 00:51:31,800 --> 00:51:34,920 Speaker 1: but it wasn't she like really put herself out there 980 00:51:34,960 --> 00:51:40,000 Speaker 1: to do it. Yeah, So another West Virginia raised black 981 00:51:40,040 --> 00:51:42,320 Speaker 1: girl who did math there. Well, she was a woman, 982 00:51:42,360 --> 00:51:43,880 Speaker 1: but I wrote it in the script about she's a 983 00:51:43,880 --> 00:51:47,960 Speaker 1: girl because she was raised in anyway, Katherine Johnson, who 984 00:51:48,000 --> 00:51:49,640 Speaker 1: did a lot of the math, who put the first 985 00:51:49,640 --> 00:51:52,960 Speaker 1: people into space, who's also in this movie. And I'm 986 00:51:52,960 --> 00:51:54,920 Speaker 1: not actually from West Virginia, but I live here now, 987 00:51:54,960 --> 00:51:56,560 Speaker 1: so I have to do this whole thing where I'm 988 00:51:56,560 --> 00:51:58,719 Speaker 1: like contractually obliged to get excited about anything that's to 989 00:51:58,760 --> 00:52:01,879 Speaker 1: do with West Virginia. So that's why I'm pointing this out. 990 00:52:02,560 --> 00:52:06,040 Speaker 1: And her county didn't even offer public school for black 991 00:52:06,120 --> 00:52:09,040 Speaker 1: kids past eighth grade, so her entire fucking family knew 992 00:52:09,040 --> 00:52:11,239 Speaker 1: how smart she was and how important school was for her. 993 00:52:11,440 --> 00:52:13,279 Speaker 1: So they moved two hours away so that they could 994 00:52:13,320 --> 00:52:17,040 Speaker 1: go to school elsewhere, and they spent like basically, and 995 00:52:17,080 --> 00:52:18,719 Speaker 1: then summers they would come back home to where the 996 00:52:18,760 --> 00:52:21,400 Speaker 1: rest of their extended family live, I believe. But she 997 00:52:21,480 --> 00:52:23,560 Speaker 1: was smartest, fucking her parents weren't gonna see that go 998 00:52:23,640 --> 00:52:25,680 Speaker 1: to waste. So she graduated high school, which she was 999 00:52:25,760 --> 00:52:29,040 Speaker 1: fucking fourteen, because I she was smart at fuck. She 1000 00:52:29,080 --> 00:52:31,960 Speaker 1: went to West Virginia State University, which is another HBU, 1001 00:52:32,120 --> 00:52:36,120 Speaker 1: historically black university. She graduates at eighteen from fucking college, 1002 00:52:36,600 --> 00:52:39,120 Speaker 1: and then for grad school, She's one of three black 1003 00:52:39,200 --> 00:52:42,120 Speaker 1: students who went off to West Virginia University, a white school, 1004 00:52:42,320 --> 00:52:45,720 Speaker 1: to be the first students to integrate it. In nineteen 1005 00:52:45,719 --> 00:52:48,320 Speaker 1: fifty two, she got hired by NAKA as a computer 1006 00:52:48,800 --> 00:52:50,839 Speaker 1: and soon she was assigned to the all male, all 1007 00:52:50,920 --> 00:52:54,320 Speaker 1: white flight research team, where she was quickly and aggressive. Basically, 1008 00:52:54,400 --> 00:52:56,200 Speaker 1: she showed up and and actually did kind of act 1009 00:52:56,280 --> 00:52:58,319 Speaker 1: like she does in the movie where she pretty aggressively 1010 00:52:58,800 --> 00:53:01,160 Speaker 1: proves herself and I'm not going to take any ship, 1011 00:53:01,560 --> 00:53:03,400 Speaker 1: and she ends up being like the First Woman and 1012 00:53:03,480 --> 00:53:05,680 Speaker 1: her planning meetings just by saying like, no, I need 1013 00:53:05,719 --> 00:53:09,560 Speaker 1: to go into this fucking meeting. She calculated the trajectory 1014 00:53:09,600 --> 00:53:12,920 Speaker 1: for Alan Shepherd's May five flight, the first time a 1015 00:53:13,000 --> 00:53:16,279 Speaker 1: US astronaut went into space, the first US astronaut to 1016 00:53:16,280 --> 00:53:18,800 Speaker 1: actually or with the Earth. John Glenn had his trajectory 1017 00:53:18,840 --> 00:53:22,040 Speaker 1: calculated by a computer like an IBM, not a person, 1018 00:53:22,760 --> 00:53:25,560 Speaker 1: and so he insisted that Katherine Johnson double check all 1019 00:53:25,600 --> 00:53:28,760 Speaker 1: the numbers, like specifically asked for her by name, which 1020 00:53:29,520 --> 00:53:31,360 Speaker 1: is kind of interesting to me because he was a 1021 00:53:31,440 --> 00:53:35,360 Speaker 1: hell of sexist, which I'll get to later. Um. And 1022 00:53:35,400 --> 00:53:37,520 Speaker 1: then she goes on to help Apollo eleven get to 1023 00:53:37,520 --> 00:53:41,680 Speaker 1: the moon. As she described her time after NACA became 1024 00:53:41,760 --> 00:53:45,200 Speaker 1: NASA and segregation ended. We needed to be assertive as 1025 00:53:45,239 --> 00:53:48,480 Speaker 1: women in those days, assertive and aggressive, and the degree 1026 00:53:48,480 --> 00:53:50,239 Speaker 1: to which we had to be that way depended on 1027 00:53:50,320 --> 00:53:52,960 Speaker 1: where you were. I had to be. In the early 1028 00:53:53,000 --> 00:53:55,040 Speaker 1: days of NASA, women were not allowed to put their 1029 00:53:55,120 --> 00:53:57,640 Speaker 1: names on the reports. No woman in my division had 1030 00:53:57,680 --> 00:53:59,880 Speaker 1: had her name on a report. I was working with 1031 00:54:00,000 --> 00:54:03,000 Speaker 1: at Skapinski and he wanted to leave and go to Houston. 1032 00:54:03,239 --> 00:54:05,640 Speaker 1: But Henry Pearson, our supervisor, he was not a fan 1033 00:54:05,680 --> 00:54:08,279 Speaker 1: of women, kept pushing him to finish the report when 1034 00:54:08,320 --> 00:54:11,160 Speaker 1: we that we were working on. Finally Ted told him 1035 00:54:11,640 --> 00:54:13,759 Speaker 1: Katherine should finish the report. She's done most of the 1036 00:54:13,800 --> 00:54:16,880 Speaker 1: work anyway, So Ted left Pearson with no choice. I 1037 00:54:16,960 --> 00:54:19,239 Speaker 1: finished the report and my name went on it, and 1038 00:54:19,280 --> 00:54:21,080 Speaker 1: that was the first time a woman in our division 1039 00:54:21,080 --> 00:54:24,319 Speaker 1: had her name on something. I don't know. She fucking ruled. 1040 00:54:24,360 --> 00:54:26,680 Speaker 1: She lived to be a hundred and one. She lived 1041 00:54:26,719 --> 00:54:29,000 Speaker 1: long enough to see herself as a major character in 1042 00:54:29,040 --> 00:54:33,680 Speaker 1: a major film, which I can't even imagine what that would. Yes, Oh, 1043 00:54:33,800 --> 00:54:35,520 Speaker 1: we have that like, you know, the saying like give 1044 00:54:35,560 --> 00:54:38,640 Speaker 1: people their flowers while they can still smell them. I've 1045 00:54:38,640 --> 00:54:42,520 Speaker 1: seen pictures of her like getting celebrated while she was alive, 1046 00:54:42,560 --> 00:54:45,680 Speaker 1: which I love and fun fact, I have a picture 1047 00:54:45,680 --> 00:54:48,440 Speaker 1: of her on my water bottle here, see that, a 1048 00:54:48,440 --> 00:54:54,359 Speaker 1: little car, a little cartoon, a sticker of her. That's cool. No, 1049 00:54:54,400 --> 00:54:57,120 Speaker 1: I mean like it's like that, Like people should google 1050 00:54:57,160 --> 00:54:59,919 Speaker 1: pictures of her later in her life. Getting to meet 1051 00:55:00,040 --> 00:55:02,319 Speaker 1: I think it was Taraji p Henson who portrayed her, 1052 00:55:02,360 --> 00:55:05,359 Speaker 1: and like getting to meet Obama, Like, I'm happy that 1053 00:55:05,400 --> 00:55:08,560 Speaker 1: she was on this earth while she got to really 1054 00:55:08,600 --> 00:55:12,279 Speaker 1: see people celebrate her legacy. It really is an important thing. Yeah, yeah, 1055 00:55:12,360 --> 00:55:16,759 Speaker 1: cool people who did cool stuff. The last person I'm 1056 00:55:16,760 --> 00:55:20,080 Speaker 1: going to talk really briefly about today is the opposite 1057 00:55:20,080 --> 00:55:24,320 Speaker 1: of a cool person. Oh good. Chief architect of US's 1058 00:55:24,400 --> 00:55:30,239 Speaker 1: lunar mission was a fucking Nazi. Oh no, like in 1059 00:55:30,280 --> 00:55:32,960 Speaker 1: a had been a member of the Nazi Party since 1060 00:55:33,920 --> 00:55:37,480 Speaker 1: Verner von Bione was the director of the Marshall Space 1061 00:55:37,520 --> 00:55:41,000 Speaker 1: Flight Center in Alabama, but before that he lived in Germany. 1062 00:55:41,040 --> 00:55:44,040 Speaker 1: In ninety seven, he joined the Nazi Party. Later, when 1063 00:55:44,080 --> 00:55:45,920 Speaker 1: he defected to the US, he claimed he joined in 1064 00:55:46,000 --> 00:55:49,080 Speaker 1: nineteen thirty nine, but he was lying. I think he 1065 00:55:49,120 --> 00:55:51,520 Speaker 1: wanted to look a little bit less zealous of a fascist, 1066 00:55:52,640 --> 00:55:56,479 Speaker 1: but he really was. Probably he's like the ultimate bad 1067 00:55:56,600 --> 00:55:58,279 Speaker 1: version of the I don't care as long as I 1068 00:55:58,320 --> 00:56:02,239 Speaker 1: get to do science guy, which kind of underpins the 1069 00:56:02,239 --> 00:56:04,960 Speaker 1: whole thing about how science is often divorced from politics 1070 00:56:04,960 --> 00:56:07,200 Speaker 1: and sometimes that's sort of cool and sometimes it's really 1071 00:56:07,239 --> 00:56:11,080 Speaker 1: really not cool. So he's a Nazi rocket scientist who 1072 00:56:11,200 --> 00:56:13,279 Speaker 1: joined the s S and used slave labor to build 1073 00:56:13,280 --> 00:56:16,160 Speaker 1: his rockets. Like literally he would walk down the halls 1074 00:56:16,160 --> 00:56:18,560 Speaker 1: of concentration camps and pick out prisoners he wanted to 1075 00:56:18,640 --> 00:56:21,799 Speaker 1: enslave to make his war machines. And then he became 1076 00:56:21,840 --> 00:56:24,400 Speaker 1: one of six hundred scientists and engineers and ship that 1077 00:56:24,440 --> 00:56:26,279 Speaker 1: the U S grabbed from Germany and what gets called 1078 00:56:26,280 --> 00:56:29,480 Speaker 1: Operation paper Clip, as they were looking for an advantage 1079 00:56:30,000 --> 00:56:32,960 Speaker 1: in the Cold War against Russia. But to be clear, 1080 00:56:33,280 --> 00:56:35,520 Speaker 1: just to both sides of the ship, the USSR was 1081 00:56:35,719 --> 00:56:39,360 Speaker 1: no better. They recruited folks of their own from the 1082 00:56:39,440 --> 00:56:43,799 Speaker 1: Nazi scientists, just fighting over the spoils of war. And 1083 00:56:43,840 --> 00:56:47,600 Speaker 1: I feel like the like the understanding of what you're 1084 00:56:47,600 --> 00:56:50,000 Speaker 1: talking about, how like like the US government is like, 1085 00:56:50,040 --> 00:56:51,480 Speaker 1: we don't give a ship, We just want to win 1086 00:56:51,480 --> 00:56:54,080 Speaker 1: this fucking war. It goes both ways in a really 1087 00:56:54,760 --> 00:56:58,279 Speaker 1: a grim way. So that's where I want to break 1088 00:56:58,280 --> 00:57:01,400 Speaker 1: it today. With all the women computers who did all 1089 00:57:01,440 --> 00:57:04,759 Speaker 1: the wildest calculations in history, How are you feeling about 1090 00:57:04,760 --> 00:57:08,080 Speaker 1: these people? Well? I I like that so many of 1091 00:57:08,120 --> 00:57:12,399 Speaker 1: them were, like you said, doing cool ship, even if 1092 00:57:12,440 --> 00:57:16,400 Speaker 1: it was for like not like nations that couldn't really 1093 00:57:16,440 --> 00:57:18,919 Speaker 1: it's it's almost like I wish that they were living 1094 00:57:18,960 --> 00:57:20,400 Speaker 1: at a time where they could do this ship for 1095 00:57:20,440 --> 00:57:25,960 Speaker 1: institutions or organizations that could really see them like you know, yeah, 1096 00:57:26,040 --> 00:57:29,000 Speaker 1: but I I this is very much like these are 1097 00:57:29,120 --> 00:57:31,040 Speaker 1: These are my heroes, These are my idols. These are 1098 00:57:31,040 --> 00:57:33,480 Speaker 1: the people that like allowed me to see myself in 1099 00:57:33,680 --> 00:57:37,120 Speaker 1: technology and computing and all of that. Um, yeah, I 1100 00:57:37,160 --> 00:57:39,160 Speaker 1: love them. Yeah. Is there anything I missed about them 1101 00:57:39,200 --> 00:57:41,600 Speaker 1: that you want to like shout out or talk about, Like, 1102 00:57:42,880 --> 00:57:45,120 Speaker 1: uh no, I think you really did a great job. 1103 00:57:45,200 --> 00:57:47,160 Speaker 1: But only the only thing I love, the only little 1104 00:57:47,200 --> 00:57:50,480 Speaker 1: thing that I love is when I was researching this 1105 00:57:50,760 --> 00:57:55,080 Speaker 1: for another project, I learned that the word kill a girl. 1106 00:57:55,160 --> 00:57:59,240 Speaker 1: Did you come across that in your that like computing 1107 00:57:59,480 --> 00:58:03,160 Speaker 1: was so associated with like women and secretarial work that 1108 00:58:03,520 --> 00:58:06,160 Speaker 1: the phrase kill a girl kind of like kill a 1109 00:58:06,160 --> 00:58:10,600 Speaker 1: lot was that meant roughly the computing power of one 1110 00:58:10,720 --> 00:58:13,360 Speaker 1: girl working for one hour, and so they used to 1111 00:58:13,400 --> 00:58:17,040 Speaker 1: describe it as like, oh, kill a girl, like that's 1112 00:58:17,080 --> 00:58:20,000 Speaker 1: the computing power of one girl working for one hour. 1113 00:58:20,680 --> 00:58:28,120 Speaker 1: So fun fact, that's amazing. Cool. Well, when we come 1114 00:58:28,120 --> 00:58:31,120 Speaker 1: back on Wednesday, we're going to talk about gay computer scientists, 1115 00:58:31,120 --> 00:58:37,120 Speaker 1: Soviet space cults, astronauts, cosmonauts, weird people, a whole bunch 1116 00:58:37,120 --> 00:58:44,160 Speaker 1: of people, cool people that did cool stuff, perhaps mostly amazing. Bridget, 1117 00:58:44,160 --> 00:58:48,560 Speaker 1: you have any plugables for us? Yeah, this has been great. Um, 1118 00:58:48,640 --> 00:58:50,800 Speaker 1: please check out my podcast. There are no girls on 1119 00:58:50,840 --> 00:58:53,680 Speaker 1: the Internet on this very network. You can follow me 1120 00:58:53,720 --> 00:58:56,800 Speaker 1: on Twitter at Bridget Mariana on Instagram at Bridget Marie 1121 00:58:56,800 --> 00:58:58,680 Speaker 1: in d C. I want you to know it's very 1122 00:58:58,720 --> 00:59:00,920 Speaker 1: hard for me to not write a terrible joke that 1123 00:59:00,960 --> 00:59:02,960 Speaker 1: you've heard a thousand times about the title of your 1124 00:59:03,000 --> 00:59:06,920 Speaker 1: podcast into my introduction to you about what it's just 1125 00:59:06,920 --> 00:59:09,000 Speaker 1: gonna be, something like you say there's no girls on 1126 00:59:09,040 --> 00:59:11,480 Speaker 1: the Internet, but here we are or whatever. I don't know. 1127 00:59:11,680 --> 00:59:15,160 Speaker 1: I really the world is better served that I took 1128 00:59:15,200 --> 00:59:18,080 Speaker 1: it out of the script, but you added at the 1129 00:59:18,160 --> 00:59:21,960 Speaker 1: end of goodness, you know, they say there's no girls 1130 00:59:21,960 --> 00:59:24,120 Speaker 1: on the internet, but here's three of them talking about 1131 00:59:24,160 --> 00:59:29,280 Speaker 1: technology and computer so you tell me, yeah, there it is, 1132 00:59:30,720 --> 00:59:39,439 Speaker 1: and we'll be back on Wednesday. Cool People Who Did 1133 00:59:39,440 --> 00:59:42,160 Speaker 1: Cool Stuff is a production of cool Zone Media. For 1134 00:59:42,280 --> 00:59:45,320 Speaker 1: more podcasts on cool zone Media, visit our website cool 1135 00:59:45,360 --> 00:59:47,760 Speaker 1: zone media dot com, or check us out on the 1136 00:59:47,880 --> 00:59:50,840 Speaker 1: I Heart Radio app, Apple Podcasts, or wherever you get 1137 00:59:50,880 --> 00:59:51,600 Speaker 1: your podcasts.