1 00:00:03,680 --> 00:00:10,080 Speaker 1: I'm t T and I'm Zakiah, and this is Dope Labs. 2 00:00:11,360 --> 00:00:14,600 Speaker 1: Welcome to Dope Labs, a weekly podcast that mixes hardcore 3 00:00:14,680 --> 00:00:17,639 Speaker 1: science with pop culture and a healthy dose of friendship. 4 00:00:22,400 --> 00:00:24,800 Speaker 1: Me and as a Kia met back in what was 5 00:00:24,840 --> 00:00:26,040 Speaker 1: that twenty e ten. 6 00:00:27,200 --> 00:00:30,760 Speaker 2: To go about the outfits we were wearing, well, I 7 00:00:30,880 --> 00:00:34,280 Speaker 2: was wearing dressed like business with bright pink lipstick. 8 00:00:34,520 --> 00:00:37,639 Speaker 1: I had a lot of eyeshadow on from my eyebrow 9 00:00:37,760 --> 00:00:40,440 Speaker 1: to my lash line, so it had to have been 10 00:00:40,479 --> 00:00:41,519 Speaker 1: the twenty tens. 11 00:00:41,640 --> 00:00:43,440 Speaker 2: I think you had. 12 00:00:43,280 --> 00:00:49,040 Speaker 1: Great bangs, Thank you friend. The rest of it was 13 00:00:49,159 --> 00:00:52,519 Speaker 1: not right. It was just fine. When I think about 14 00:00:52,680 --> 00:00:57,520 Speaker 1: like us being in grad school and having a good time, 15 00:00:57,520 --> 00:01:00,000 Speaker 1: but also being like, hey, we need to have some balance, 16 00:01:00,240 --> 00:01:03,720 Speaker 1: you know, pushing each other said and remember I would 17 00:01:03,760 --> 00:01:05,520 Speaker 1: set those crazy deadlines, and I was like, I have 18 00:01:05,560 --> 00:01:08,680 Speaker 1: to sprint to get this done in the next three weeks. 19 00:01:08,680 --> 00:01:11,160 Speaker 1: I'm going to get this many mutants into the chromosome. 20 00:01:11,240 --> 00:01:13,399 Speaker 2: I was moving there. I was trying to do a 21 00:01:13,400 --> 00:01:17,319 Speaker 2: lot of recombineering, doing a lot of genetic manipulation to 22 00:01:17,480 --> 00:01:18,240 Speaker 2: your bacteria. 23 00:01:18,360 --> 00:01:20,560 Speaker 1: These are a lot of words exactly how you're feeling 24 00:01:20,600 --> 00:01:22,360 Speaker 1: right now. That exactly how I felt when she was 25 00:01:22,360 --> 00:01:25,320 Speaker 1: explained it to me. Yes, girl, my friend is very, 26 00:01:25,440 --> 00:01:28,200 Speaker 1: very smart. But if somebody would have told me, oh, 27 00:01:28,240 --> 00:01:30,360 Speaker 1: you know, you and Zakia are going to have a 28 00:01:30,400 --> 00:01:35,400 Speaker 1: podcast together in a few years, I would have believed them, honestly, 29 00:01:35,480 --> 00:01:39,520 Speaker 1: because we we had been saying it. We had been 30 00:01:39,800 --> 00:01:43,360 Speaker 1: since true, Like there is evidence on the Internet of 31 00:01:43,360 --> 00:01:44,399 Speaker 1: where we were like, oh, we should do. 32 00:01:44,400 --> 00:01:46,480 Speaker 2: A podcast together, we should do a podcast together. 33 00:01:46,520 --> 00:01:49,000 Speaker 1: But you know, lots of people at that time were 34 00:01:49,000 --> 00:01:51,920 Speaker 1: saying they wanted to do a podcast. We just actually 35 00:01:51,920 --> 00:01:53,520 Speaker 1: did it, which is wild. 36 00:01:53,200 --> 00:01:53,400 Speaker 2: You know. 37 00:01:54,160 --> 00:01:56,640 Speaker 1: And I think what makes it so wild is just 38 00:01:56,680 --> 00:02:01,080 Speaker 1: how rewarding. It's been challenging and reporting, and I think 39 00:02:01,160 --> 00:02:03,520 Speaker 1: that makes the reward so much sweeter. You know. 40 00:02:04,480 --> 00:02:08,400 Speaker 2: I really appreciate everybody that has been riding with us. 41 00:02:08,480 --> 00:02:12,280 Speaker 2: I can remember February fourteenth, twenty nineteen, our first episode 42 00:02:12,400 --> 00:02:15,480 Speaker 2: and people were responding and finding us on social media 43 00:02:15,560 --> 00:02:20,320 Speaker 2: and saying they liked the episode. Great price memory. Emory, 44 00:02:20,760 --> 00:02:21,040 Speaker 2: I go. 45 00:02:21,200 --> 00:02:25,400 Speaker 1: By everybody's Instagram name. Yes, everybody, Yes, I know you 46 00:02:25,400 --> 00:02:29,040 Speaker 1: by your handle exactly. The Emory is my cousin in 47 00:02:29,080 --> 00:02:33,040 Speaker 1: my head. Honestly. The key key sessions we have in 48 00:02:33,120 --> 00:02:36,359 Speaker 1: DMS is just it's top tier. 49 00:02:37,480 --> 00:02:40,239 Speaker 2: Kiki, well, we actually got to meet her in person. 50 00:02:40,440 --> 00:02:44,400 Speaker 1: Oh Kiki, my ye, Yes, we did meet her in person. 51 00:02:44,560 --> 00:02:47,000 Speaker 1: And it's crazy because when you say Kiky, I was 52 00:02:47,040 --> 00:02:50,760 Speaker 1: like our friend Kiki, it's hard to remember that we 53 00:02:50,800 --> 00:02:53,880 Speaker 1: did not know these people before the show, right, Cat Purcell, 54 00:02:54,200 --> 00:02:59,600 Speaker 1: Cat Percell absolutely absolutely running to our episodes on her 55 00:02:59,680 --> 00:03:02,560 Speaker 1: daily runs. Yeah, but even the new folks, the new 56 00:03:02,600 --> 00:03:04,640 Speaker 1: folks that have been showing up and saying, hey, I 57 00:03:04,720 --> 00:03:07,520 Speaker 1: just found your podcast, we really appreciate y'all as well, 58 00:03:08,000 --> 00:03:11,000 Speaker 1: and so welcome, come on, get in here with us. 59 00:03:11,000 --> 00:03:13,920 Speaker 1: We're gonna snuggle up real tight and close. But in 60 00:03:14,000 --> 00:03:16,399 Speaker 1: this week's lab, we're gonna be talking about what we 61 00:03:16,440 --> 00:03:19,000 Speaker 1: do here at DOPE last with just science communication, and 62 00:03:19,040 --> 00:03:22,480 Speaker 1: we're gonna be talking to some of our favorite science communicators. 63 00:03:22,880 --> 00:03:26,679 Speaker 1: We have Raven the Science Maven, doctor Raven Baxter. She's 64 00:03:26,720 --> 00:03:30,680 Speaker 1: a molecular biologist and a science educator. We also have 65 00:03:30,760 --> 00:03:34,200 Speaker 1: Lindsay Edo who is a PhD student in neuroscience at 66 00:03:34,240 --> 00:03:37,840 Speaker 1: the University of Pennsylvania researching pain. And then we have 67 00:03:38,080 --> 00:03:42,400 Speaker 1: doctor Andre Isaacs, who is a chemistry professor at College 68 00:03:42,400 --> 00:03:45,840 Speaker 1: of the Holy Cross, and if you are on TikTok 69 00:03:46,520 --> 00:03:48,640 Speaker 1: you've seen doctor Isaacs. 70 00:03:49,920 --> 00:03:53,440 Speaker 2: You've seen them, you absolutely have. He is one of 71 00:03:53,440 --> 00:03:57,840 Speaker 2: my faves. I can't wait to share these folks stories 72 00:03:57,960 --> 00:04:01,240 Speaker 2: because you know, I think people come to science and 73 00:04:01,320 --> 00:04:04,920 Speaker 2: stem broadly through many different avenues, right. 74 00:04:05,400 --> 00:04:05,600 Speaker 3: You know. 75 00:04:05,760 --> 00:04:08,240 Speaker 1: I love t t when you share the story of 76 00:04:08,320 --> 00:04:11,560 Speaker 1: your grandfather being an engineer. That was the first time 77 00:04:11,560 --> 00:04:14,080 Speaker 1: I'd ever heard of engineering was when my I'd asked 78 00:04:14,120 --> 00:04:16,279 Speaker 1: my mother, you know what my grandparents did, and she 79 00:04:16,320 --> 00:04:18,680 Speaker 1: talked about my grandfather and said that he was an engineer. 80 00:04:18,680 --> 00:04:21,719 Speaker 1: And I was like, well, then I shall be an engineer. 81 00:04:22,360 --> 00:04:24,800 Speaker 2: Crowned yourself. That's right, yourself, that's right. 82 00:04:24,920 --> 00:04:28,600 Speaker 1: I was like, let me tell you, Frederick Akufu, you 83 00:04:28,640 --> 00:04:31,400 Speaker 1: did that. You did that, And so he blazed the 84 00:04:31,440 --> 00:04:33,520 Speaker 1: trail and I just walked behind him. 85 00:04:33,640 --> 00:04:34,279 Speaker 2: Very grateful. 86 00:04:34,920 --> 00:04:37,200 Speaker 1: I love your stories about how you got involved in 87 00:04:37,240 --> 00:04:39,839 Speaker 1: step because it's all over the place. 88 00:04:41,000 --> 00:04:43,600 Speaker 2: He started it. You started wanting to be a nurse 89 00:04:43,839 --> 00:04:46,880 Speaker 2: and then realized, yes, hey girl, you don't have the 90 00:04:46,880 --> 00:04:51,400 Speaker 2: stomach for that. Okay, you don't. You said it was 91 00:04:51,720 --> 00:04:54,479 Speaker 2: passing out. I was like, oh no, baby, I don't 92 00:04:54,480 --> 00:04:57,400 Speaker 2: think I'm in the wrong place, and I went all 93 00:04:57,440 --> 00:04:59,480 Speaker 2: the way to being a certified nursing assistant. I was 94 00:04:59,520 --> 00:05:03,040 Speaker 2: a CNA, and so then I was like, I can't 95 00:05:03,040 --> 00:05:04,640 Speaker 2: go to school for this. I switched to be in 96 00:05:04,640 --> 00:05:08,799 Speaker 2: a biology major. But even before that program, summer exposure 97 00:05:08,880 --> 00:05:12,000 Speaker 2: programs at North Carolina A and T. That was really 98 00:05:12,120 --> 00:05:15,000 Speaker 2: my route into science broadly. That's why I was even 99 00:05:15,000 --> 00:05:17,560 Speaker 2: in the nursing area. There was a woman, her name 100 00:05:17,600 --> 00:05:19,720 Speaker 2: was Miss Manley. She ran a Saturday program that was 101 00:05:19,760 --> 00:05:22,000 Speaker 2: called GAMSEK at North Carolina A and T. It was 102 00:05:22,000 --> 00:05:24,760 Speaker 2: a Greensboro area math and science enrichment camp. And I 103 00:05:24,760 --> 00:05:27,200 Speaker 2: went on Saturdays, but my mom was going back to school. 104 00:05:27,920 --> 00:05:30,680 Speaker 2: I would go to that. We were doing SAT pre SAT, 105 00:05:30,800 --> 00:05:32,560 Speaker 2: we were doing programs, We're doing stuff I wasn't even 106 00:05:32,640 --> 00:05:35,479 Speaker 2: learning yet. And I was getting such exposure to so 107 00:05:35,520 --> 00:05:38,039 Speaker 2: many different things. And in high school I went on 108 00:05:38,080 --> 00:05:40,200 Speaker 2: and did I was doing civil engineering over at A 109 00:05:40,279 --> 00:05:44,360 Speaker 2: and T, which is wild because you're the engineer exactly. 110 00:05:44,520 --> 00:05:47,000 Speaker 1: I didn't know my friend was an engineer too, but 111 00:05:47,080 --> 00:05:49,719 Speaker 1: I'm not surprised. She's very, very smart. She could do anything. 112 00:05:49,800 --> 00:05:52,159 Speaker 1: But you know, what your story reminds me of is 113 00:05:52,200 --> 00:05:55,400 Speaker 1: what doctor Isaac's andre. What he was saying was his 114 00:05:55,600 --> 00:06:00,440 Speaker 1: first introduction into stem was also a similar experience where 115 00:06:00,880 --> 00:06:04,320 Speaker 1: he got involved because someone else was teaching him chemistry 116 00:06:04,680 --> 00:06:05,760 Speaker 1: and it happened to be his uncle. 117 00:06:06,440 --> 00:06:08,280 Speaker 4: It started for me in high school. 118 00:06:08,680 --> 00:06:10,880 Speaker 3: I will be the first to say I wanted to 119 00:06:10,920 --> 00:06:13,960 Speaker 3: love chemistry so bad, but chemistry didn't love me. When 120 00:06:14,000 --> 00:06:17,919 Speaker 3: I was in high school, I really struggled with specifically stoycheometry. 121 00:06:18,040 --> 00:06:19,880 Speaker 1: And I. 122 00:06:21,400 --> 00:06:24,800 Speaker 3: Know, I know, I'm like balancing equations, that's easy, but 123 00:06:25,160 --> 00:06:27,520 Speaker 3: I really struggled, you know, as a high schooler. And 124 00:06:27,600 --> 00:06:31,000 Speaker 3: it was my uncle, who back when I lived in Jamaica, 125 00:06:31,040 --> 00:06:32,960 Speaker 3: by the way, I grew up in Kingston, Jamaica, who 126 00:06:33,440 --> 00:06:36,320 Speaker 3: had this evening school that he taught adults who were 127 00:06:36,320 --> 00:06:39,200 Speaker 3: going back to school for to get like high school degrees. 128 00:06:39,279 --> 00:06:42,160 Speaker 3: So he said, come to my evening school. I'll help 129 00:06:42,200 --> 00:06:44,520 Speaker 3: you with whatever you need. So I went and an 130 00:06:44,600 --> 00:06:48,919 Speaker 3: hour later I was a master at stoycheometry. So I think, really, 131 00:06:48,960 --> 00:06:52,120 Speaker 3: for me, what that showed there's no subject is impossible. 132 00:06:52,160 --> 00:06:55,000 Speaker 4: You just need to write instruction or instructor. 133 00:06:55,680 --> 00:06:57,920 Speaker 3: And someone who can explain it in a way that's 134 00:06:57,960 --> 00:07:01,520 Speaker 3: accessible to you. And in that moment, I recognized that 135 00:07:01,600 --> 00:07:02,640 Speaker 3: I could conquer. 136 00:07:02,320 --> 00:07:05,800 Speaker 4: Anything, even chemistry, and so I really just took to it. 137 00:07:06,080 --> 00:07:10,360 Speaker 3: Went to college, started doing research, was killing all my classes. 138 00:07:10,440 --> 00:07:12,480 Speaker 4: My professors are like, dude, you need to do a PhD. 139 00:07:12,560 --> 00:07:16,320 Speaker 4: Are too good at this, and I just kept going. 140 00:07:16,360 --> 00:07:18,040 Speaker 3: And I think a lot of it really came back to, 141 00:07:18,680 --> 00:07:22,480 Speaker 3: you know, that initial experience of seeing a hurdle that 142 00:07:22,520 --> 00:07:24,680 Speaker 3: I didn't think I could cross and having someone just 143 00:07:24,760 --> 00:07:27,400 Speaker 3: break it down for me in ways that were accessible 144 00:07:27,400 --> 00:07:29,360 Speaker 3: to me, and then I was able to do it. 145 00:07:29,400 --> 00:07:33,320 Speaker 3: And so for me, that's definitely key to my own pedagogy. 146 00:07:33,400 --> 00:07:34,880 Speaker 3: When I see a student who was struggling, I'm like, 147 00:07:34,880 --> 00:07:37,080 Speaker 3: I just need to find a way to make that 148 00:07:37,120 --> 00:07:39,920 Speaker 3: student understand this sort of make it connect in a 149 00:07:39,960 --> 00:07:42,040 Speaker 3: way that works for them. And I think that's one 150 00:07:42,040 --> 00:07:43,720 Speaker 3: of the things many of us as educators need to 151 00:07:43,760 --> 00:07:44,360 Speaker 3: really think about. 152 00:07:44,600 --> 00:07:47,320 Speaker 2: I think this was one of the guiding principles for 153 00:07:47,400 --> 00:07:50,200 Speaker 2: me when I was teaching. I was like, how can 154 00:07:50,240 --> 00:07:53,920 Speaker 2: I make this connectment how you're already thinking, what you're 155 00:07:53,960 --> 00:07:54,840 Speaker 2: already thinking about. 156 00:07:54,920 --> 00:07:59,480 Speaker 1: When my friend was a professor, Okay, y'all didn't know 157 00:07:59,520 --> 00:08:02,120 Speaker 1: the key when she was in her professor era, she 158 00:08:02,960 --> 00:08:07,000 Speaker 1: was that girl. Okay, when I tell you I went 159 00:08:07,040 --> 00:08:09,040 Speaker 1: to one of her classes, I'm not. 160 00:08:09,040 --> 00:08:10,760 Speaker 2: Good at biology. You already know that. 161 00:08:10,960 --> 00:08:16,080 Speaker 1: Okay, my friend holds my hand through every biology episode. 162 00:08:16,200 --> 00:08:19,200 Speaker 1: I came out of that class like I think I 163 00:08:19,280 --> 00:08:22,520 Speaker 1: might be able to be a geneticist. She makes it 164 00:08:22,880 --> 00:08:28,400 Speaker 1: so accessible, she roots it and stuff that you're already 165 00:08:28,800 --> 00:08:31,520 Speaker 1: thinking about talking about singing. 166 00:08:32,200 --> 00:08:34,400 Speaker 2: And it was just so so good. 167 00:08:34,440 --> 00:08:39,439 Speaker 1: And so you were teaching biology to non non majors, 168 00:08:39,520 --> 00:08:42,360 Speaker 1: and so these are folks who don't have the background 169 00:08:42,880 --> 00:08:45,720 Speaker 1: and they're trying to get their credits. But let me 170 00:08:45,760 --> 00:08:49,280 Speaker 1: tell you something, those students are forever changed. 171 00:08:49,640 --> 00:08:52,920 Speaker 2: I think that's one of the things I really loved. 172 00:08:53,200 --> 00:08:54,920 Speaker 2: I saw a lot of non majors switch to be 173 00:08:54,920 --> 00:08:56,840 Speaker 2: a major. Some of them ended up in my research lab. 174 00:08:57,120 --> 00:09:00,560 Speaker 2: One of them is a science teacher right now, Kelly 175 00:09:00,720 --> 00:09:04,719 Speaker 2: oh DiGeronimo. But it's so cool to see, you know 176 00:09:04,960 --> 00:09:07,640 Speaker 2: how these kind of experiences. I had those experiences in 177 00:09:07,679 --> 00:09:09,719 Speaker 2: my life. I had a biology teacher. I used to 178 00:09:09,760 --> 00:09:11,480 Speaker 2: you know, I went into biology because I had a 179 00:09:11,520 --> 00:09:13,200 Speaker 2: biology teacher that was like flowing what you know, and 180 00:09:13,240 --> 00:09:18,280 Speaker 2: I said, this is hard, I'll do this. And I 181 00:09:18,320 --> 00:09:19,920 Speaker 2: was like I don't know anything. I don't have anything 182 00:09:19,960 --> 00:09:20,520 Speaker 2: to flow into. 183 00:09:20,679 --> 00:09:23,480 Speaker 1: Hey, come on, I mean it's crazy how one minute 184 00:09:23,520 --> 00:09:25,520 Speaker 1: you're just living your life and then you get an 185 00:09:25,600 --> 00:09:29,160 Speaker 1: idea and that idea turns into something bigger that you 186 00:09:29,520 --> 00:09:30,240 Speaker 1: probably could. 187 00:09:30,040 --> 00:09:30,959 Speaker 2: Have never imagined. 188 00:09:31,040 --> 00:09:35,680 Speaker 1: And Lindsey, Raven, and Andre had similar experiences to us, 189 00:09:35,760 --> 00:09:38,520 Speaker 1: where it's like, how do we get here? We are 190 00:09:39,360 --> 00:09:42,920 Speaker 1: doing this podcast, doing something that we really love. Raven, 191 00:09:43,160 --> 00:09:45,000 Speaker 1: who you're gonna hear from first, she's a little bit 192 00:09:45,000 --> 00:09:48,360 Speaker 1: of an og and so she uses music as a 193 00:09:48,440 --> 00:09:49,880 Speaker 1: means to connect with folks. 194 00:09:50,240 --> 00:09:52,040 Speaker 2: I remember first discovering Raven. 195 00:09:52,240 --> 00:09:56,040 Speaker 1: Hey, it was a lot of feelings, a lot of fun. 196 00:09:56,000 --> 00:09:57,120 Speaker 5: As far as I go. 197 00:09:57,559 --> 00:10:01,240 Speaker 6: You know, music historically has and a means to share 198 00:10:01,800 --> 00:10:06,319 Speaker 6: messages and at the same time, music is a language 199 00:10:06,960 --> 00:10:10,960 Speaker 6: that unites us all and when it comes to blending 200 00:10:11,040 --> 00:10:13,840 Speaker 6: science and music, it really was a no brainer for me. 201 00:10:14,840 --> 00:10:18,040 Speaker 6: And so my first music video was called Big Old Geeks, 202 00:10:18,200 --> 00:10:25,400 Speaker 6: and it is a rap video that like displays norms 203 00:10:25,400 --> 00:10:28,440 Speaker 6: that you see in hip hop culture, you know, especially 204 00:10:28,840 --> 00:10:33,920 Speaker 6: like contemporary hip hop culture. We're looking at fast cars, 205 00:10:34,120 --> 00:10:39,080 Speaker 6: hot ladies, and bars, and that's what I was giving. 206 00:10:39,360 --> 00:10:42,680 Speaker 6: And so it featured me. I was like the main character, 207 00:10:42,800 --> 00:10:46,320 Speaker 6: but I also cast in my friends as dancers and 208 00:10:46,440 --> 00:10:49,640 Speaker 6: just actresses in the background, and they were all black 209 00:10:49,679 --> 00:10:54,600 Speaker 6: women of various shape, sizes, and colors. And the lyrics 210 00:10:54,760 --> 00:10:58,080 Speaker 6: I was delivering were very technical, some big old geeks, 211 00:10:58,080 --> 00:11:01,080 Speaker 6: but the tennis place was on my ytic sciences talking. 212 00:11:01,160 --> 00:11:03,040 Speaker 5: I kind of like I'm doing both. I'm Biana nothing 213 00:11:03,120 --> 00:11:05,600 Speaker 5: you buck periodic. I can like an enzigme and we're 214 00:11:05,640 --> 00:11:08,599 Speaker 5: cutting it up. Proteens in the job and we're running. 215 00:11:08,360 --> 00:11:11,160 Speaker 6: Them up the message like, the science is still the 216 00:11:11,160 --> 00:11:13,160 Speaker 6: same no matter what I look like or act like. 217 00:11:13,600 --> 00:11:16,800 Speaker 6: That video was the first video I put out, and 218 00:11:17,440 --> 00:11:19,400 Speaker 6: I kind of took a chance. You know, as a 219 00:11:19,440 --> 00:11:22,600 Speaker 6: black woman in science, you don't really get a lot 220 00:11:22,600 --> 00:11:26,680 Speaker 6: of liberty right as far as self expression goes, and 221 00:11:26,720 --> 00:11:28,040 Speaker 6: so I really took a gamble. 222 00:11:28,160 --> 00:11:30,079 Speaker 5: I'm just like, I know in my. 223 00:11:30,160 --> 00:11:32,280 Speaker 6: Heart that there are other people that need to see this, 224 00:11:32,400 --> 00:11:34,120 Speaker 6: and so I'm just going to put this out there. 225 00:11:34,320 --> 00:11:38,720 Speaker 6: And that's where my journey started. And I did release 226 00:11:39,160 --> 00:11:42,079 Speaker 6: other music and music videos after that, but that's. 227 00:11:41,920 --> 00:11:42,680 Speaker 5: Where it all began. 228 00:11:43,280 --> 00:11:46,600 Speaker 1: Lindsey and Andre they both use their downtime during the 229 00:11:46,640 --> 00:11:50,840 Speaker 1: pandemic to start creating science communication on their social media. 230 00:11:50,920 --> 00:11:51,480 Speaker 5: It's funny. 231 00:11:51,520 --> 00:11:54,800 Speaker 7: I started on TikTok twenty twenty one. 232 00:11:55,679 --> 00:11:57,440 Speaker 8: And I don't know, it was just one of those 233 00:11:57,559 --> 00:12:01,560 Speaker 8: like during the COVID, developing a technok things, you. 234 00:12:01,600 --> 00:12:03,600 Speaker 5: Know, I had to do a lot of people. 235 00:12:05,000 --> 00:12:08,720 Speaker 8: So I started watching all these data life videos and 236 00:12:08,760 --> 00:12:10,600 Speaker 8: I figured, oh, let me try one, because I figured 237 00:12:10,640 --> 00:12:13,040 Speaker 8: not many people know what the day in life of like. 238 00:12:12,960 --> 00:12:15,320 Speaker 7: A neuroscientist is, or even a PhD student. 239 00:12:15,880 --> 00:12:18,400 Speaker 8: So I tried one out and then it randomly got 240 00:12:18,400 --> 00:12:19,240 Speaker 8: a lot of traction. 241 00:12:20,000 --> 00:12:23,240 Speaker 7: So I was just like, oh, okay, I'll keep it going. 242 00:12:24,120 --> 00:12:26,520 Speaker 8: And then over time people would ask questions about my 243 00:12:26,559 --> 00:12:29,640 Speaker 8: science and my experiments, and that led me to like, 244 00:12:29,679 --> 00:12:30,559 Speaker 8: you know, respond to. 245 00:12:30,520 --> 00:12:32,200 Speaker 7: Them, think of other things to talk about. 246 00:12:31,960 --> 00:12:35,920 Speaker 8: And eventually building this pretty big picon platform. 247 00:12:36,480 --> 00:12:40,520 Speaker 3: Like many of us, the pandemic changed a lot of things. 248 00:12:41,000 --> 00:12:43,040 Speaker 3: And I'll be honest, I had Instagram. 249 00:12:43,120 --> 00:12:46,240 Speaker 4: I didn't have TikTok at an Instagram. I had a Twitter. 250 00:12:46,320 --> 00:12:50,400 Speaker 3: I probably had a combined eleven hundred followers on all plastics. 251 00:12:51,400 --> 00:12:52,480 Speaker 4: I just didn't really. 252 00:12:52,280 --> 00:12:55,600 Speaker 3: Pulse like that, right, But the pandemic came and you know, 253 00:12:55,760 --> 00:12:58,600 Speaker 3: the college was like, hey, faculty, you have a week 254 00:12:58,640 --> 00:13:01,520 Speaker 3: to transition your courses to line learning. Go use this 255 00:13:01,559 --> 00:13:03,360 Speaker 3: thing called zoom. We've never heard of it, but we 256 00:13:03,440 --> 00:13:07,319 Speaker 3: hear it's good. So there I am a zoom and 257 00:13:07,440 --> 00:13:10,520 Speaker 3: I went extroverts. So, you know, once you were teaching online, 258 00:13:10,559 --> 00:13:15,160 Speaker 3: I got extremely bored and you know, I needed to 259 00:13:15,160 --> 00:13:17,200 Speaker 3: get out. I needed to socialize. You know, my friends 260 00:13:17,200 --> 00:13:19,200 Speaker 3: are sending me videos and they're like, oh, here's this video. 261 00:13:19,200 --> 00:13:20,719 Speaker 3: I'm like, I don't have this app called TikTok. What 262 00:13:20,760 --> 00:13:22,959 Speaker 3: am I supposed to do with this? And so I 263 00:13:23,000 --> 00:13:25,199 Speaker 3: downloaded it and let me tell you, the rabbit hole 264 00:13:25,480 --> 00:13:28,160 Speaker 3: was there. But what was really awesome for me was 265 00:13:28,200 --> 00:13:30,960 Speaker 3: as a kid growing up in Jamaica, we have an 266 00:13:30,960 --> 00:13:34,360 Speaker 3: affinity for dancing, right, and you all might be familiar 267 00:13:34,400 --> 00:13:36,400 Speaker 3: with how it comes about. You know, some DJ creates 268 00:13:36,400 --> 00:13:40,120 Speaker 3: a riddim and then the artists sing a song on it, 269 00:13:40,160 --> 00:13:43,520 Speaker 3: and then someone creates a dance and pretty soon everyone 270 00:13:43,559 --> 00:13:45,720 Speaker 3: in the island is doing the Willy Bones soor or whatever. 271 00:13:47,280 --> 00:13:50,200 Speaker 3: And so for me, you know, you go to a 272 00:13:50,200 --> 00:13:52,320 Speaker 3: party in Jamaica as a kid, everyone knew the dance 273 00:13:52,360 --> 00:13:53,800 Speaker 3: moves and then I go on TikTok. 274 00:13:53,440 --> 00:13:54,240 Speaker 4: And it's the same thing. 275 00:13:54,760 --> 00:13:54,960 Speaker 6: Yes. 276 00:13:55,440 --> 00:13:58,920 Speaker 3: So I was like immediately drawn back to my past 277 00:13:58,960 --> 00:14:00,960 Speaker 3: as a kid growing up in jam and seeing the 278 00:14:01,000 --> 00:14:04,080 Speaker 3: community that's built her own dance, shared experience of dance 279 00:14:04,120 --> 00:14:06,120 Speaker 3: and the knowledge of the moves and all that stuff, 280 00:14:06,120 --> 00:14:06,439 Speaker 3: and so. 281 00:14:06,960 --> 00:14:07,920 Speaker 4: I was drawn into it. 282 00:14:07,960 --> 00:14:10,400 Speaker 3: So I started making videos at home by myself, learning 283 00:14:10,480 --> 00:14:11,760 Speaker 3: choreography to the Renegade. 284 00:14:11,760 --> 00:14:14,840 Speaker 4: That one was hard. I didn't finish that one. And 285 00:14:15,120 --> 00:14:15,640 Speaker 4: you know, one of. 286 00:14:15,640 --> 00:14:18,559 Speaker 3: My students saw a video I posted on our for 287 00:14:18,640 --> 00:14:20,920 Speaker 3: you page, and when we went back to campus, when 288 00:14:20,920 --> 00:14:23,040 Speaker 3: we were allowed to go back to campus in person, 289 00:14:23,640 --> 00:14:25,240 Speaker 3: she's like, Hey, we need to collaborate. 290 00:14:25,400 --> 00:14:27,720 Speaker 4: You can dance. I didn't know you could dance. I'm like, 291 00:14:27,760 --> 00:14:28,840 Speaker 4: I didn't know you could dance. 292 00:14:30,080 --> 00:14:35,760 Speaker 3: And what that created was really this community of scientists 293 00:14:35,840 --> 00:14:41,120 Speaker 3: who have interests outside of science, including dance, music, theater. 294 00:14:41,800 --> 00:14:44,600 Speaker 3: And we built a little community in the lab and 295 00:14:44,640 --> 00:14:47,840 Speaker 3: in my classes in the chemistry department, you know, where 296 00:14:47,880 --> 00:14:51,920 Speaker 3: we all like learned dances and choreography and showed that 297 00:14:51,920 --> 00:14:53,800 Speaker 3: as a scientist you can be multi facetating. 298 00:14:53,880 --> 00:14:56,240 Speaker 4: You didn't have to just be the stereotypical. 299 00:14:56,760 --> 00:14:59,000 Speaker 3: Hey, I'm in a basement in a white lab quote 300 00:14:59,000 --> 00:15:01,440 Speaker 3: with no personality, no emotion, no skills. 301 00:15:01,480 --> 00:15:18,400 Speaker 2: You know, dancing and science is not my ministry. It 302 00:15:18,520 --> 00:15:20,520 Speaker 2: is also not mine. 303 00:15:20,720 --> 00:15:24,840 Speaker 1: Okay, y'all don't need to see that, but doctor Isaac's 304 00:15:24,960 --> 00:15:28,240 Speaker 1: I'm telling you, if you don't follow him on TikTok, 305 00:15:28,360 --> 00:15:30,640 Speaker 1: get to it. You gotta get to it because he's 306 00:15:30,680 --> 00:15:32,119 Speaker 1: got the moves, he's. 307 00:15:32,120 --> 00:15:36,760 Speaker 2: Funny, smart, it's perfect. We me and my friends. You know, 308 00:15:36,840 --> 00:15:40,920 Speaker 2: we are more of calckulers and science. That's true. That's true. 309 00:15:41,200 --> 00:15:41,760 Speaker 2: That's true. 310 00:15:42,040 --> 00:15:45,120 Speaker 1: And showing up as ourselves has been really really important 311 00:15:45,120 --> 00:15:47,560 Speaker 1: to us. I don't know if we've told this story 312 00:15:48,200 --> 00:15:51,640 Speaker 1: on the show, but Zaki, tell these folks about what 313 00:15:51,800 --> 00:15:54,240 Speaker 1: happened after our first episode. We got a lot of love, 314 00:15:54,840 --> 00:15:57,040 Speaker 1: but we did get a lot of a lot of love, 315 00:15:57,080 --> 00:15:59,400 Speaker 1: but we got a little bit of hate. 316 00:15:59,840 --> 00:16:02,400 Speaker 2: I know people say just ignore those things, but I 317 00:16:02,440 --> 00:16:05,000 Speaker 2: also think those things are indicator when you get hate. 318 00:16:05,240 --> 00:16:08,000 Speaker 2: That kind of hate is an indicator of where people 319 00:16:08,080 --> 00:16:10,680 Speaker 2: have closed minds or where change needs to happen. When 320 00:16:10,720 --> 00:16:13,400 Speaker 2: we first started Dope Labs, people like you said, I 321 00:16:13,400 --> 00:16:15,160 Speaker 2: showed us a lot of love, but we diget an 322 00:16:15,200 --> 00:16:17,960 Speaker 2: email and I will never forget this. The guy was like, 323 00:16:18,840 --> 00:16:22,320 Speaker 2: you're using language like this, You're not sounding professional. Does 324 00:16:22,440 --> 00:16:24,600 Speaker 2: it makes you less credible when you talk like this? 325 00:16:24,720 --> 00:16:28,960 Speaker 2: I said, baby, this country grammar. You're gonna get it God, 326 00:16:29,160 --> 00:16:34,520 Speaker 2: turning to Nelly. Yes, I'm going now, damn Dawn, baby Okay, 327 00:16:34,640 --> 00:16:37,000 Speaker 2: I turned to Nelly in here all right? And so 328 00:16:37,120 --> 00:16:41,120 Speaker 2: I think you know that also challenges what people think 329 00:16:41,280 --> 00:16:43,880 Speaker 2: a scientist sounds like. And so showing up like this 330 00:16:44,400 --> 00:16:47,400 Speaker 2: tells you exactly, But I am a scientist. So this 331 00:16:47,520 --> 00:16:50,400 Speaker 2: is now what a scientist sounds like. I remember when 332 00:16:50,440 --> 00:16:52,800 Speaker 2: you graduated. I'm not gonna point any fingers and name 333 00:16:52,840 --> 00:16:55,640 Speaker 2: any names, but somebody said, a scientist doesn't dress like this. 334 00:16:56,000 --> 00:17:00,720 Speaker 1: Oh yes, I always got a lot of well you, 335 00:17:00,760 --> 00:17:04,199 Speaker 1: and I say a lot people have commented on the 336 00:17:04,240 --> 00:17:06,439 Speaker 1: way that I dress and the way that I you know, 337 00:17:06,520 --> 00:17:10,159 Speaker 1: the way that I do things for what feels like forever, 338 00:17:10,240 --> 00:17:12,120 Speaker 1: because they just don't feel like it falls in line 339 00:17:12,160 --> 00:17:14,359 Speaker 1: with what they feel like someone who's accomplished in this 340 00:17:14,400 --> 00:17:15,080 Speaker 1: field looks like. 341 00:17:15,359 --> 00:17:18,960 Speaker 2: And I'm like, well, here, I am right here, I 342 00:17:19,000 --> 00:17:22,400 Speaker 2: am existing outside of what you imaginally look at that 343 00:17:22,680 --> 00:17:24,200 Speaker 2: open your mind, open your mind. 344 00:17:24,440 --> 00:17:27,760 Speaker 1: It really isn't that much of a stretch. It's just closed, 345 00:17:27,800 --> 00:17:30,239 Speaker 1: it's just makeup, it's just hair like. 346 00:17:32,200 --> 00:17:34,720 Speaker 2: These are just the accessories. But the brain is where 347 00:17:34,720 --> 00:17:38,199 Speaker 2: it's at. No, that's that's the gym. Okay. 348 00:17:38,480 --> 00:17:42,760 Speaker 1: Well, we hear similar stories from Raven and Andre too 349 00:17:42,800 --> 00:17:46,560 Speaker 1: about how they had some negative reactions to them before 350 00:17:46,600 --> 00:17:49,720 Speaker 1: they even started their science communication and during I. 351 00:17:49,640 --> 00:17:54,119 Speaker 6: Had an incident at one of my former places of 352 00:17:54,160 --> 00:17:58,840 Speaker 6: employment where I had a coworker tell me that she 353 00:17:58,880 --> 00:18:01,639 Speaker 6: didn't believe that I worked there, and it was my 354 00:18:01,720 --> 00:18:05,600 Speaker 6: first day and she threatened to call the police on 355 00:18:05,720 --> 00:18:08,520 Speaker 6: me because I was in the faculty mail room. 356 00:18:09,160 --> 00:18:11,840 Speaker 5: And I left that. 357 00:18:12,440 --> 00:18:18,360 Speaker 6: Incident really feeling just charged with this mission to disrupt 358 00:18:18,880 --> 00:18:21,320 Speaker 6: the notion of what a scientist looks like, and I 359 00:18:21,359 --> 00:18:24,360 Speaker 6: wanted to do it in such an extreme way that 360 00:18:25,200 --> 00:18:27,680 Speaker 6: just made the message very clear. 361 00:18:28,119 --> 00:18:29,320 Speaker 4: I do get some pushback, you know. 362 00:18:29,320 --> 00:18:31,320 Speaker 3: There are some folks who think that what I'm doing 363 00:18:31,400 --> 00:18:35,320 Speaker 3: is not productive, and what they measure success on right, 364 00:18:35,400 --> 00:18:38,639 Speaker 3: is really the number of publications you have instead of 365 00:18:38,720 --> 00:18:41,080 Speaker 3: really the number of folks that you've brought into the field. 366 00:18:41,600 --> 00:18:45,119 Speaker 3: And so for me, I don't mind the negative criticism, 367 00:18:45,280 --> 00:18:48,960 Speaker 3: you know, because what I know for a fact that 368 00:18:49,040 --> 00:18:52,600 Speaker 3: the work that I do has had a positive impact 369 00:18:52,600 --> 00:18:54,840 Speaker 3: on young folks who emailed me. 370 00:18:55,040 --> 00:18:56,880 Speaker 4: I've get like hundreds of emails. 371 00:18:56,600 --> 00:18:59,280 Speaker 3: From high school kids, college kids, even professors were like, 372 00:18:59,400 --> 00:19:03,240 Speaker 3: I didn't think a Korean commisary was for me until 373 00:19:03,280 --> 00:19:05,520 Speaker 3: I saw your videos. So those are the people who 374 00:19:05,560 --> 00:19:08,680 Speaker 3: I'm dotting for, and so the hitters can hit. I'm 375 00:19:08,720 --> 00:19:10,600 Speaker 3: trying to bring new folks into the game. 376 00:19:10,960 --> 00:19:15,800 Speaker 1: And with all of this, you know, with all of this, well, 377 00:19:15,880 --> 00:19:17,920 Speaker 1: let me not say all of this, because honestly, we're 378 00:19:17,960 --> 00:19:20,520 Speaker 1: all getting a lot of really positive feedback. But with 379 00:19:20,600 --> 00:19:23,400 Speaker 1: the negative feedback, you know that those kind of thing. 380 00:19:23,680 --> 00:19:26,640 Speaker 1: But we still continue to turn our microphones on because 381 00:19:26,680 --> 00:19:30,600 Speaker 1: this space needs us, It needs more voices. 382 00:19:30,880 --> 00:19:34,199 Speaker 5: Absolutely, we have such a long way to go. Where 383 00:19:34,280 --> 00:19:35,879 Speaker 5: are my colleagues? 384 00:19:36,080 --> 00:19:41,160 Speaker 6: You and I are both degreed scientists, experts. There are 385 00:19:42,040 --> 00:19:45,920 Speaker 6: so many of us out there, but yet so many 386 00:19:45,920 --> 00:19:48,720 Speaker 6: of us don't have platforms to stand on to demonstrate 387 00:19:48,720 --> 00:19:54,159 Speaker 6: that expertise, to bring people into scientific conversations in a 388 00:19:54,240 --> 00:19:55,200 Speaker 6: constructive way. 389 00:19:55,920 --> 00:20:00,000 Speaker 5: And it's just annoying that. 390 00:20:00,040 --> 00:20:03,200 Speaker 6: That Bill Kny, the science guy, is still the archetype 391 00:20:03,280 --> 00:20:07,639 Speaker 6: of science communication in twenty twenty five. There are just 392 00:20:07,720 --> 00:20:12,080 Speaker 6: so many opportunities for not only like current scientists, but 393 00:20:12,200 --> 00:20:16,680 Speaker 6: aspiring science communicators to fill in that space. 394 00:20:16,359 --> 00:20:20,480 Speaker 5: And carry us forward. So where are we right now? 395 00:20:20,840 --> 00:20:25,320 Speaker 6: People are panicking, I think, especially now with the government, 396 00:20:25,600 --> 00:20:29,720 Speaker 6: you know, US government administrations cuts to science and clear 397 00:20:29,840 --> 00:20:35,240 Speaker 6: actions against the scientific community at large. We're really facing 398 00:20:35,320 --> 00:20:37,879 Speaker 6: a text on science and people are panicking because they 399 00:20:37,920 --> 00:20:41,360 Speaker 6: didn't I don't think that many of us could gauge 400 00:20:41,720 --> 00:20:46,800 Speaker 6: how severe this would be, and now everyone's trying to 401 00:20:46,800 --> 00:20:49,320 Speaker 6: scream into the void on no platform. 402 00:20:50,440 --> 00:20:55,560 Speaker 5: So it is just like, oh. 403 00:20:55,280 --> 00:20:57,920 Speaker 6: My gosh, we have a lot of work to do. 404 00:20:58,280 --> 00:21:03,360 Speaker 6: But I'm optimistic, but it's just a daunting It's very daunting. 405 00:21:03,880 --> 00:21:07,160 Speaker 8: I think that it seems like science feels so far 406 00:21:07,240 --> 00:21:11,199 Speaker 8: away from so many people right now, especially when it 407 00:21:11,240 --> 00:21:14,720 Speaker 8: comes to the cutting edge work that's being done, the 408 00:21:14,840 --> 00:21:18,520 Speaker 8: new data that's coming out as we speak and continues 409 00:21:18,560 --> 00:21:21,760 Speaker 8: to come out, and what the actual process going through 410 00:21:21,800 --> 00:21:25,320 Speaker 8: a research project to get that data really is and 411 00:21:25,359 --> 00:21:28,119 Speaker 8: the fact that this is so opaque definitely does not 412 00:21:28,240 --> 00:21:32,880 Speaker 8: help the growing mistrust in scientists and the divestment from science. 413 00:21:33,520 --> 00:21:35,679 Speaker 8: And it's so frustrating. But I think a lot of 414 00:21:35,720 --> 00:21:41,679 Speaker 8: scientists just feel that frustration and just say, oh, this sucks, 415 00:21:42,040 --> 00:21:48,000 Speaker 8: let's get back to work. But what if we instead said, Okay, 416 00:21:48,800 --> 00:21:51,399 Speaker 8: how about we meet people where they are, share with 417 00:21:51,440 --> 00:21:54,120 Speaker 8: them what we're doing and what strides we're making. It's 418 00:21:54,200 --> 00:21:56,680 Speaker 8: easy to think that science is a waste of money 419 00:21:56,720 --> 00:21:58,320 Speaker 8: when you don't know what's coming out of it. 420 00:21:58,760 --> 00:22:01,720 Speaker 7: Right, it's not right in your face outside of like. 421 00:22:02,080 --> 00:22:08,760 Speaker 8: Pharma, big pharma commercials exactly exactly. So, I think social 422 00:22:08,800 --> 00:22:10,720 Speaker 8: media has its flaws, for sure, but it's a really 423 00:22:10,760 --> 00:22:15,280 Speaker 8: effective way to show up in the spaces that unbiased, 424 00:22:15,960 --> 00:22:19,520 Speaker 8: balanced science usually doesn't reach and spread that message. 425 00:22:19,800 --> 00:22:22,160 Speaker 3: I think the way it falls short is in how 426 00:22:22,240 --> 00:22:26,280 Speaker 3: it's communicated and the methods through which the information is related. 427 00:22:26,400 --> 00:22:28,280 Speaker 3: So there's not a lot of us. I mentioned there's 428 00:22:28,280 --> 00:22:30,560 Speaker 3: not a lot of culture in the way we communicate science, 429 00:22:30,920 --> 00:22:34,560 Speaker 3: and that's because science is being communicated the way was 430 00:22:34,560 --> 00:22:36,199 Speaker 3: communicated in the nineteen forties. 431 00:22:36,240 --> 00:22:36,400 Speaker 4: Right. 432 00:22:36,440 --> 00:22:39,280 Speaker 3: I often say, if you look at any textbook, all 433 00:22:39,359 --> 00:22:41,679 Speaker 3: the examples are like a baseball reference. 434 00:22:41,720 --> 00:22:42,720 Speaker 4: Right. We've been throwing. 435 00:22:42,480 --> 00:22:46,919 Speaker 3: Baseballs as a way to calculate wavelengths for the past 436 00:22:47,840 --> 00:22:50,879 Speaker 3: eighty years, right, since the heyday of baseball. I'm like, 437 00:22:50,880 --> 00:22:52,520 Speaker 3: we need to be able to throw something else. What 438 00:22:52,600 --> 00:22:55,280 Speaker 3: are the kids nowadays culturally thrown? Throw a chankla throw, 439 00:22:55,440 --> 00:22:59,240 Speaker 3: you know, throw something else, right, and let's let's bring 440 00:22:59,320 --> 00:23:01,680 Speaker 3: some culture. So I think one of the ways we're 441 00:23:01,680 --> 00:23:05,240 Speaker 3: falling short is people aren't seeing themselves. Their lived experiences 442 00:23:05,280 --> 00:23:07,920 Speaker 3: are not reflected in the way science is communicated to them. 443 00:23:08,480 --> 00:23:10,879 Speaker 3: And so I think something we need to really do 444 00:23:10,960 --> 00:23:12,240 Speaker 3: is start teaching. 445 00:23:11,920 --> 00:23:13,280 Speaker 4: In a more modern way. 446 00:23:13,520 --> 00:23:17,919 Speaker 3: Are more modern examples that really bridge young folks who 447 00:23:17,920 --> 00:23:20,800 Speaker 3: lived experiences with science, And if we can do that, 448 00:23:20,840 --> 00:23:22,600 Speaker 3: I think we'll have better outcomes for folks. 449 00:23:36,240 --> 00:23:36,640 Speaker 2: The KEYA. 450 00:23:36,800 --> 00:23:42,000 Speaker 1: So when you think of science communication on the grand scheme, 451 00:23:42,440 --> 00:23:45,359 Speaker 1: where do you feel like there's still some gaps? Like 452 00:23:45,400 --> 00:23:47,680 Speaker 1: where do you feel like science communication is lacking? 453 00:23:48,320 --> 00:23:55,959 Speaker 2: I think science communication is lacking in the it's too uptight. 454 00:23:56,080 --> 00:23:58,679 Speaker 2: It still has a suit. I think, like, you know, 455 00:23:58,720 --> 00:24:00,600 Speaker 2: it used to have on a three piece suit and 456 00:24:00,640 --> 00:24:03,159 Speaker 2: a cumber bunch and now it just has on a 457 00:24:03,200 --> 00:24:05,320 Speaker 2: regular suit, and I'm like, you need to put on 458 00:24:05,480 --> 00:24:08,719 Speaker 2: basketball shorts and a tank top. I think some of 459 00:24:08,720 --> 00:24:12,680 Speaker 2: my favorite science communicators are here in this episode. Some 460 00:24:12,760 --> 00:24:15,080 Speaker 2: others are not and I'm going to share them, you know, 461 00:24:15,160 --> 00:24:17,680 Speaker 2: in our social media, I'll spotlight some of the people 462 00:24:17,760 --> 00:24:19,680 Speaker 2: I really like as well that are doing great work. 463 00:24:19,720 --> 00:24:23,879 Speaker 2: But I think we forget just how many combos of 464 00:24:24,000 --> 00:24:29,280 Speaker 2: identities there are and where people might find an inroad, 465 00:24:29,440 --> 00:24:31,440 Speaker 2: do you know what I mean? Like, you don't have 466 00:24:31,560 --> 00:24:35,119 Speaker 2: to make science your entire personality to enjoy it, to 467 00:24:35,200 --> 00:24:38,480 Speaker 2: be a lover of science, to be a supporter of it, right, 468 00:24:38,640 --> 00:24:42,400 Speaker 2: And I think so often science communication has been shoved 469 00:24:42,440 --> 00:24:45,600 Speaker 2: into this like upright position and that's like, okay, now 470 00:24:45,600 --> 00:24:48,240 Speaker 2: we must say this fact and this thing. And what 471 00:24:48,280 --> 00:24:50,520 Speaker 2: the evidence shows us is that that's not the only 472 00:24:50,600 --> 00:24:52,280 Speaker 2: road in. It's not a deficit model. It's not that 473 00:24:52,320 --> 00:24:54,879 Speaker 2: people don't have enough information. Is that we're not bringing 474 00:24:54,920 --> 00:24:58,119 Speaker 2: them enough narrative and connection points to make it feel 475 00:24:58,119 --> 00:25:00,719 Speaker 2: relevant to their lives, to make it feel to even 476 00:25:00,880 --> 00:25:02,760 Speaker 2: you know, hide the what do you call it, hide 477 00:25:02,800 --> 00:25:04,359 Speaker 2: the medicine and the apple sauce, or to hide it 478 00:25:04,440 --> 00:25:07,000 Speaker 2: in the candy or whatever. We don't do that enough 479 00:25:07,280 --> 00:25:10,160 Speaker 2: with science communication, Like it should be fun. Sometimes people 480 00:25:10,160 --> 00:25:11,480 Speaker 2: say to me like, oh, I listen to an episode, 481 00:25:11,560 --> 00:25:17,879 Speaker 2: y'all just laughing. Yeah, we're laughing. You think, right, you 482 00:25:17,920 --> 00:25:20,200 Speaker 2: don't want me to get a a haha, I think 483 00:25:20,280 --> 00:25:23,560 Speaker 2: my facts like that's right to me, crazy, And so 484 00:25:23,760 --> 00:25:25,760 Speaker 2: I do think that's a place where we're missing some 485 00:25:25,840 --> 00:25:28,320 Speaker 2: things in science communication. What do you think we need 486 00:25:28,320 --> 00:25:30,320 Speaker 2: more of? I think the same. 487 00:25:30,520 --> 00:25:33,439 Speaker 1: I think we need just more folks being given an 488 00:25:33,480 --> 00:25:37,119 Speaker 1: opportunity to talk. I think that we, for such a 489 00:25:37,119 --> 00:25:41,520 Speaker 1: long time, have only listened to certain scientists that look 490 00:25:41,640 --> 00:25:45,360 Speaker 1: and sound and fit this mold. And so it's just 491 00:25:45,440 --> 00:25:49,360 Speaker 1: like when folks are looking for a scientists, they are 492 00:25:49,400 --> 00:25:53,919 Speaker 1: looking for this very cookie cutter look and feel, and 493 00:25:53,960 --> 00:25:56,880 Speaker 1: I'm like, but there's so many smart dope people out 494 00:25:56,880 --> 00:25:59,320 Speaker 1: there that are doing such amazing work, and y'all are 495 00:25:59,359 --> 00:26:02,440 Speaker 1: missing out on that amazing work just because they don't 496 00:26:02,480 --> 00:26:05,359 Speaker 1: fit into your cookie cutter mold. Like they are people 497 00:26:05,400 --> 00:26:09,560 Speaker 1: that are a part of the LGBTQ plus community. They 498 00:26:09,560 --> 00:26:13,360 Speaker 1: are people that are differently abled, people who are coming from. 499 00:26:13,520 --> 00:26:14,560 Speaker 2: All walks of life. 500 00:26:14,560 --> 00:26:17,480 Speaker 1: There are deaf scientists, there are blind scientists, and we're 501 00:26:17,520 --> 00:26:20,680 Speaker 1: missing out on those experiences because we're like, no, I 502 00:26:20,880 --> 00:26:26,120 Speaker 1: want to see someone that looks like that guy that 503 00:26:26,200 --> 00:26:28,040 Speaker 1: has been talking for the last thirty years. 504 00:26:28,080 --> 00:26:33,000 Speaker 2: No shade but a little bit I heard it. We 505 00:26:33,240 --> 00:26:37,960 Speaker 2: asked Raven, Andre and lindsay what they thought was missing 506 00:26:37,960 --> 00:26:39,080 Speaker 2: from science communication. 507 00:26:40,000 --> 00:26:46,080 Speaker 6: A healthy science communication ecosystem involves teaching science communication at 508 00:26:46,119 --> 00:26:49,560 Speaker 6: the K twol level for sure, not only science communication 509 00:26:49,640 --> 00:26:53,719 Speaker 6: but also science literacy, but focusing in on science communication, 510 00:26:54,440 --> 00:26:58,359 Speaker 6: teaching these kids, Okay, well you learn science and you 511 00:26:58,440 --> 00:27:00,480 Speaker 6: may not be able to become a science and tist 512 00:27:00,640 --> 00:27:03,359 Speaker 6: right now, but you can talk about the things that 513 00:27:03,400 --> 00:27:06,040 Speaker 6: you learned. And we have so many kids who want 514 00:27:06,040 --> 00:27:10,320 Speaker 6: to become YouTubers, twitch streamers, all of that make money 515 00:27:10,440 --> 00:27:12,120 Speaker 6: on social media, which is amazing. 516 00:27:12,240 --> 00:27:13,800 Speaker 5: That could be a very great career. 517 00:27:14,400 --> 00:27:19,159 Speaker 6: But science communication is a proven avenue to pursue that, 518 00:27:19,280 --> 00:27:22,000 Speaker 6: so why not integrate that into a K twelve curriculum? 519 00:27:22,560 --> 00:27:25,720 Speaker 6: And then, of course, as an educator, I'm always thinking 520 00:27:25,880 --> 00:27:29,000 Speaker 6: education in front of mine. That needs to carry over 521 00:27:29,160 --> 00:27:33,840 Speaker 6: into colleges and universities. We need science communication majors. We 522 00:27:33,880 --> 00:27:39,320 Speaker 6: need like formal degree programs around building a science communication career, 523 00:27:39,359 --> 00:27:45,520 Speaker 6: whether it's written art, fine arts, or like actual communications 524 00:27:46,440 --> 00:27:50,719 Speaker 6: journal you know, like formal science writing, technical science writing, 525 00:27:51,400 --> 00:27:54,600 Speaker 6: creative science writing, like science illustrating. 526 00:27:55,720 --> 00:28:00,119 Speaker 5: It's an ecosystem. And then going out from that. 527 00:28:00,240 --> 00:28:04,840 Speaker 6: We do now have professional science communication organizations, which is great, 528 00:28:05,400 --> 00:28:09,600 Speaker 6: but I think that that ecosystem could be much more robust. 529 00:28:10,440 --> 00:28:12,280 Speaker 5: I think that we can build out that. 530 00:28:12,240 --> 00:28:17,359 Speaker 6: Network a lot more, and I think that's what it 531 00:28:17,520 --> 00:28:21,720 Speaker 6: would look like. Probably the offshoots of this ecosystem would 532 00:28:21,760 --> 00:28:25,480 Speaker 6: look like we have more presence virtually, we have more 533 00:28:25,520 --> 00:28:30,560 Speaker 6: in person opportunities for science communicators. Also, all the currently 534 00:28:30,680 --> 00:28:35,840 Speaker 6: established professional science professional organizations should have a strong science 535 00:28:35,880 --> 00:28:39,760 Speaker 6: communication arm to their initiatives. 536 00:28:40,120 --> 00:28:42,160 Speaker 3: I think one of the things I really hope to 537 00:28:42,160 --> 00:28:43,960 Speaker 3: do is to really change the picture of a scientist. 538 00:28:44,400 --> 00:28:46,800 Speaker 3: I think if you look at the data, we haven't 539 00:28:46,880 --> 00:28:50,080 Speaker 3: increased the participation rates of people of color and folks 540 00:28:50,080 --> 00:28:53,600 Speaker 3: with minoritized identities. And that's because science doesn't have a 541 00:28:53,640 --> 00:28:56,960 Speaker 3: culture that's inviting to those folks, right. And so for me, 542 00:28:57,040 --> 00:28:58,560 Speaker 3: I want to change a picture of a scientist. And 543 00:28:58,720 --> 00:29:03,320 Speaker 3: if you want to engage on participation among folks in minoritized. 544 00:29:02,840 --> 00:29:04,800 Speaker 4: Identities, we have to do things differently. 545 00:29:04,800 --> 00:29:06,320 Speaker 3: We have to do it in a way that invites 546 00:29:06,360 --> 00:29:08,120 Speaker 3: people in, right, So we have to make sure the 547 00:29:08,160 --> 00:29:11,840 Speaker 3: culture of our academic spaces or labs or classrooms are 548 00:29:11,880 --> 00:29:14,960 Speaker 3: inviting and one that ones that like allow folks to 549 00:29:14,960 --> 00:29:17,000 Speaker 3: be their full cells. And so what I'm trying to 550 00:29:17,040 --> 00:29:20,280 Speaker 3: do is really to say, hey, here's a different way 551 00:29:20,360 --> 00:29:23,960 Speaker 3: of existing in the lab space that both student and faculty, 552 00:29:24,440 --> 00:29:26,880 Speaker 3: and here's how you can bring your full authentic self 553 00:29:26,960 --> 00:29:28,720 Speaker 3: to the lab and to the classroom. 554 00:29:28,760 --> 00:29:29,440 Speaker 4: And there's data. 555 00:29:29,440 --> 00:29:32,200 Speaker 3: Scientists believe in data, there's data to backness up. I 556 00:29:32,240 --> 00:29:35,560 Speaker 3: love this beautiful references paper all the time in the 557 00:29:35,640 --> 00:29:39,800 Speaker 3: Journal of Flavor Economics that really talked about the statistics 558 00:29:39,800 --> 00:29:43,400 Speaker 3: around papers that are published by diverse co authors. 559 00:29:43,520 --> 00:29:45,240 Speaker 4: So if you look at the citation. 560 00:29:45,000 --> 00:29:48,040 Speaker 3: Numbers, right, papers that have a more diverse co authorship 561 00:29:48,080 --> 00:29:51,719 Speaker 3: have more citations than those that are ethnically homogenous. And 562 00:29:51,800 --> 00:29:56,160 Speaker 3: so diversity is important. But if we're not inviting people 563 00:29:56,160 --> 00:29:59,160 Speaker 3: in who with different perspectives, who might need a different 564 00:29:59,200 --> 00:30:02,800 Speaker 3: way of learning and understanding science, then we're not doing 565 00:30:02,840 --> 00:30:06,120 Speaker 3: our collective selves any benefits. So so I'm trying my 566 00:30:06,160 --> 00:30:09,600 Speaker 3: best to get folks into science any way I can. 567 00:30:09,960 --> 00:30:13,080 Speaker 2: No matter what your background is, you can be involved 568 00:30:13,120 --> 00:30:17,040 Speaker 2: in science communication. We need lots of perspectives, like we 569 00:30:17,040 --> 00:30:18,840 Speaker 2: were just talking about, and so. 570 00:30:18,880 --> 00:30:21,320 Speaker 1: You might be thinking, well, you know, what should I do. 571 00:30:21,440 --> 00:30:23,320 Speaker 1: What are some of the steps I should take? What 572 00:30:23,440 --> 00:30:25,880 Speaker 1: are some things that I should be thinking about if 573 00:30:25,880 --> 00:30:29,200 Speaker 1: I do want to dip my toe into science communication. 574 00:30:30,000 --> 00:30:32,600 Speaker 1: Lindsey and Andre gave us some advice. 575 00:30:33,280 --> 00:30:35,920 Speaker 8: I would say, well, I would say just do it, 576 00:30:35,960 --> 00:30:40,680 Speaker 8: but it's not that easy, right, I would say, like, really, 577 00:30:40,720 --> 00:30:44,560 Speaker 8: brainthorn for yourself, what aspects of the research you're doing 578 00:30:44,680 --> 00:30:48,200 Speaker 8: are most exciting? What things do you think are most relevant? 579 00:30:48,240 --> 00:30:51,080 Speaker 8: And what would you want the public to know If 580 00:30:51,440 --> 00:30:54,080 Speaker 8: you could make sure everybody in the world knew one 581 00:30:54,120 --> 00:30:56,959 Speaker 8: part of your research, what would that be? Pick that 582 00:30:57,080 --> 00:30:59,680 Speaker 8: topic and workshop how you talk about that? If you 583 00:30:59,680 --> 00:31:03,000 Speaker 8: want to do it Instagram in three minutes max, right, 584 00:31:03,080 --> 00:31:06,479 Speaker 8: And then this is the party is important. Draft it 585 00:31:06,560 --> 00:31:10,000 Speaker 8: and then share it with a non scientist because we 586 00:31:10,040 --> 00:31:12,560 Speaker 8: spend so little time training in how to communicate it 587 00:31:12,560 --> 00:31:15,240 Speaker 8: on scientists. This is important because you can share with 588 00:31:15,280 --> 00:31:17,959 Speaker 8: a friend, the family member, ask them like, what are 589 00:31:17,960 --> 00:31:20,000 Speaker 8: you getting out of this? Are you getting enough from it? 590 00:31:20,120 --> 00:31:21,600 Speaker 8: Or what do you think I should change that this 591 00:31:21,760 --> 00:31:24,160 Speaker 8: can be accessible to you. 592 00:31:23,920 --> 00:31:24,560 Speaker 2: Right right? 593 00:31:25,120 --> 00:31:28,160 Speaker 3: You know, scientists can have talents too, you know, as 594 00:31:28,200 --> 00:31:30,040 Speaker 3: a matter of fact, I read a paper recently that 595 00:31:30,360 --> 00:31:32,720 Speaker 3: said some of the most successful scientists are ones that 596 00:31:32,760 --> 00:31:34,520 Speaker 3: have artistic skills. And if you look at a number 597 00:31:34,520 --> 00:31:37,959 Speaker 3: of scientists who have Nobel prizes, they disproportionately have more 598 00:31:38,040 --> 00:31:40,840 Speaker 3: artistic skills than the average scientists. So yeah, if you 599 00:31:40,880 --> 00:31:43,080 Speaker 3: want to do great science, they got to learn some choreography, 600 00:31:44,360 --> 00:31:46,720 Speaker 3: play some music or something. So that's kind of how 601 00:31:46,720 --> 00:31:49,120 Speaker 3: it started, and it blossomed from there. We just get 602 00:31:49,160 --> 00:31:50,760 Speaker 3: more and more students. Majors are like. 603 00:31:50,840 --> 00:31:53,160 Speaker 4: Listen, we want to dance too. We got dance mods. 604 00:31:52,920 --> 00:31:56,160 Speaker 3: And was a really powerful way to connect with students, 605 00:31:56,160 --> 00:31:58,320 Speaker 3: but also a way to flip the script, Like I've 606 00:31:58,360 --> 00:32:00,480 Speaker 3: always been the one teaching them things, they were the 607 00:32:00,480 --> 00:32:03,640 Speaker 3: ones teaching me. Moved so the teacher became the student 608 00:32:03,680 --> 00:32:05,479 Speaker 3: and the student became the teacher, and I think what 609 00:32:05,600 --> 00:32:09,360 Speaker 3: that made for was really better relationships across the board 610 00:32:09,400 --> 00:32:12,600 Speaker 3: for all of us. 611 00:32:14,520 --> 00:32:18,280 Speaker 2: I think what we're hearing from our friends here and 612 00:32:18,400 --> 00:32:20,760 Speaker 2: what we know from our own lived experience, is that 613 00:32:21,200 --> 00:32:24,160 Speaker 2: scientists want to be seen as multi dimensional. We want 614 00:32:24,200 --> 00:32:25,480 Speaker 2: to be able to have some depth. 615 00:32:25,840 --> 00:32:29,720 Speaker 1: Absolutely, yeah, because I mean, who would we be without 616 00:32:29,760 --> 00:32:32,840 Speaker 1: our many layers, right, We didn't just pop up out 617 00:32:32,840 --> 00:32:36,480 Speaker 1: of nowhere, and we're like here I am as a scientist. 618 00:32:36,520 --> 00:32:41,160 Speaker 1: Like we lived, honey, We have lived, and we have 619 00:32:41,240 --> 00:32:43,400 Speaker 1: a lot of life experiences that we bring to the table, 620 00:32:43,440 --> 00:32:46,800 Speaker 1: which makes us stronger scientists and it helps with our 621 00:32:46,880 --> 00:32:50,320 Speaker 1: science communication because you know, I know how to communicate 622 00:32:50,680 --> 00:32:53,560 Speaker 1: to folks from lots of walks of life. And it's 623 00:32:53,560 --> 00:32:56,720 Speaker 1: not because oh I'm from that walk of life. Part 624 00:32:56,720 --> 00:32:59,040 Speaker 1: of it is, you know, But then the other part 625 00:32:59,120 --> 00:33:02,600 Speaker 1: is that I've lived, I've traveled, We've traveled, we've traveled together, 626 00:33:02,680 --> 00:33:04,680 Speaker 1: We've talked to strangers. We've done a lot of things, 627 00:33:04,720 --> 00:33:06,760 Speaker 1: and so I love to talk to stranger. My friend 628 00:33:07,160 --> 00:33:12,760 Speaker 1: doesn't know a stranger. Okay, sometimes I'm like, hey, danger, danger, danger, 629 00:33:12,800 --> 00:33:13,600 Speaker 1: stranger danger. 630 00:33:13,840 --> 00:33:14,680 Speaker 2: She don't believe in it. 631 00:33:15,080 --> 00:33:18,680 Speaker 1: But yeah, I mean having all of these layers, like 632 00:33:18,760 --> 00:33:23,400 Speaker 1: my friend, she's a wonderful artist, she's a beautiful piano player. 633 00:33:23,680 --> 00:33:26,840 Speaker 1: She does all of these amazing things that you know, 634 00:33:27,000 --> 00:33:30,280 Speaker 1: you stop it, that make her who she is. And 635 00:33:30,360 --> 00:33:32,960 Speaker 1: I mean she wouldn't have been able to be the professor. 636 00:33:33,000 --> 00:33:35,280 Speaker 1: She is, the friend, she is the scientist, she is 637 00:33:35,840 --> 00:33:38,400 Speaker 1: the daughter that she is without all these experiences. 638 00:33:39,480 --> 00:33:41,600 Speaker 2: When I think about what we try to do with dope, labs. 639 00:33:41,640 --> 00:33:46,840 Speaker 2: I think there are people that gravitate to you, and 640 00:33:46,920 --> 00:33:49,040 Speaker 2: I think that's just an example. This wouldn't be the 641 00:33:49,040 --> 00:33:50,840 Speaker 2: same if it was just a Zakiah show or if 642 00:33:50,840 --> 00:33:51,400 Speaker 2: it was just a T. 643 00:33:51,520 --> 00:33:52,000 Speaker 4: T show. 644 00:33:52,240 --> 00:33:54,400 Speaker 2: And I think what we see is that we reach 645 00:33:54,520 --> 00:33:58,160 Speaker 2: different audiences and our friendship together is a thing to 646 00:33:58,240 --> 00:34:01,480 Speaker 2: showcase because I also think so much of science gets painted, 647 00:34:01,560 --> 00:34:03,920 Speaker 2: especially in the media, it's like a one person operation, 648 00:34:04,040 --> 00:34:04,960 Speaker 2: one person in charge. 649 00:34:05,600 --> 00:34:07,880 Speaker 1: That's not how it works. I mean, it's just so wild. 650 00:34:07,920 --> 00:34:09,760 Speaker 1: People are like, oh, this is such and such scientist. 651 00:34:09,800 --> 00:34:12,160 Speaker 1: I'm like, do you know the team that is behind 652 00:34:12,320 --> 00:34:14,239 Speaker 1: you know, there are thirty people on that group, right 653 00:34:14,480 --> 00:34:18,560 Speaker 1: down to undergrads lab tech. Yes, Like you have no 654 00:34:18,760 --> 00:34:22,960 Speaker 1: idea people win in like Nobel Prizes and things like that. 655 00:34:23,000 --> 00:34:25,759 Speaker 1: They are coming from massive labs with a lot of 656 00:34:25,800 --> 00:34:28,120 Speaker 1: people doing a lot of work. And I think that 657 00:34:28,200 --> 00:34:30,360 Speaker 1: also just highlights something we've talked about a couple of 658 00:34:30,400 --> 00:34:34,640 Speaker 1: episodes ago about the entire enterprise of science, what it 659 00:34:34,800 --> 00:34:37,080 Speaker 1: takes to do this kind of research, what it takes 660 00:34:37,080 --> 00:34:39,640 Speaker 1: to keep driving this kind of innovation, and the money 661 00:34:39,920 --> 00:34:42,440 Speaker 1: it takes, you know, to do that. Because if the 662 00:34:42,520 --> 00:34:44,960 Speaker 1: lab tech is invisible to you, and the postdoc and 663 00:34:45,000 --> 00:34:48,840 Speaker 1: the grad student and the senior scientists and the supporting 664 00:34:48,880 --> 00:34:52,200 Speaker 1: the people washing the glass, where if everybody is invisible 665 00:34:52,239 --> 00:34:54,359 Speaker 1: to you, then you think that those people don't need 666 00:34:54,400 --> 00:34:57,400 Speaker 1: to be paid and that these things just happen magically, 667 00:34:57,400 --> 00:35:00,000 Speaker 1: and they don't. And I think part of science communication 668 00:35:00,480 --> 00:35:03,000 Speaker 1: for some people that are peeling the layers back and saying, hey, 669 00:35:03,040 --> 00:35:05,480 Speaker 1: this is what the scientific enterprise looks like. Part of 670 00:35:05,480 --> 00:35:08,799 Speaker 1: it is showing those parts that get hidden right. Part 671 00:35:08,800 --> 00:35:10,440 Speaker 1: of it is showing the process, like we did in 672 00:35:10,480 --> 00:35:13,640 Speaker 1: the episode weeks ago with Roberto Bowley who talked about 673 00:35:13,680 --> 00:35:16,200 Speaker 1: the EBAR system where he was leaning on research from 674 00:35:16,200 --> 00:35:19,920 Speaker 1: the eighties to help him prepare for an aging population 675 00:35:20,160 --> 00:35:24,520 Speaker 1: right now, to help people understand that basic research has 676 00:35:24,640 --> 00:35:27,759 Speaker 1: always been key to us advancing and moving forward. All 677 00:35:27,800 --> 00:35:30,160 Speaker 1: of that's necessary for people that are in science communication 678 00:35:30,200 --> 00:35:32,240 Speaker 1: to share with the world. I think the fun science 679 00:35:32,239 --> 00:35:35,400 Speaker 1: communication is like look at this bird or this new species. 680 00:35:35,400 --> 00:35:39,200 Speaker 2: You know, like that's fun. But that's not all it is, too, 681 00:35:39,560 --> 00:35:41,120 Speaker 2: like everything that's going on, you know. 682 00:35:41,440 --> 00:35:45,200 Speaker 1: Absolutely, let my friend cook I just shut. 683 00:35:44,960 --> 00:35:46,040 Speaker 2: My mouth, you know. 684 00:35:46,120 --> 00:35:48,600 Speaker 1: And all of that makes me think about when the 685 00:35:48,600 --> 00:35:52,280 Speaker 1: pandemic first hit, and we were dying for good science 686 00:35:52,280 --> 00:35:55,920 Speaker 1: communication because there was a lot of misinformation on a 687 00:35:55,960 --> 00:36:00,799 Speaker 1: lot of people confused about what was going on, absolutely 688 00:36:00,840 --> 00:36:04,080 Speaker 1: what this is, what this virus is, how it gets 689 00:36:04,320 --> 00:36:07,080 Speaker 1: passed from person to person, how long it lives on 690 00:36:07,120 --> 00:36:10,680 Speaker 1: a surface. And then when the vaccine came out, the 691 00:36:10,800 --> 00:36:16,960 Speaker 1: vaccine mistrust, we were hungry, hungry, hungry for good science communication, 692 00:36:17,040 --> 00:36:20,719 Speaker 1: and we hoped to add positive science communication to the 693 00:36:21,160 --> 00:36:24,520 Speaker 1: ecosystem because it was such a tough time and people 694 00:36:24,560 --> 00:36:28,040 Speaker 1: were reading headlines and not reading the articles. People were 695 00:36:28,480 --> 00:36:33,319 Speaker 1: making like really sensational articles and really sensational headlines and 696 00:36:33,440 --> 00:36:36,440 Speaker 1: just misleading a lot of folks, And it was just 697 00:36:36,520 --> 00:36:39,960 Speaker 1: so unfortunate because I was just like, man, if folks 698 00:36:39,960 --> 00:36:43,480 Speaker 1: were better trained in science communication, we would not be 699 00:36:43,560 --> 00:36:46,359 Speaker 1: in the position that we are right now, where no 700 00:36:46,400 --> 00:36:48,920 Speaker 1: one knows where to turn for facts. 701 00:36:49,280 --> 00:36:51,960 Speaker 2: So true. I think all we can do is hope 702 00:36:51,960 --> 00:36:57,400 Speaker 2: to continue to nurture our audience of science interested people, 703 00:36:57,920 --> 00:37:01,359 Speaker 2: to try to bring the expert right to their front door, 704 00:37:01,560 --> 00:37:04,040 Speaker 2: right to their ear drums, and to continue to try 705 00:37:04,040 --> 00:37:06,000 Speaker 2: to find good stories and to share them in a 706 00:37:06,040 --> 00:37:10,560 Speaker 2: way that's fun and that just leaves friendship and joy 707 00:37:10,719 --> 00:37:14,000 Speaker 2: all throughout it. You know, yes, I loved this episode. 708 00:37:14,080 --> 00:37:24,160 Speaker 1: It was basically the science of Dope Labs. You can 709 00:37:24,200 --> 00:37:28,200 Speaker 1: find us on X and Instagram at Dope Labs podcast. 710 00:37:28,200 --> 00:37:31,880 Speaker 2: Tt Is on X and Instagram at dr Underscore t Sho, 711 00:37:32,160 --> 00:37:35,399 Speaker 2: and you can find Takiya at z said so. Dope 712 00:37:35,480 --> 00:37:37,440 Speaker 2: Labs is a production of Lamanada Media. 713 00:37:37,680 --> 00:37:42,319 Speaker 1: Our senior supervising producer is Kristin Lapour and our associate 714 00:37:42,360 --> 00:37:44,440 Speaker 1: producer is Issara Svez. 715 00:37:45,160 --> 00:37:48,880 Speaker 2: Dope Labs is sound designed, edited and mixed by James Farber. 716 00:37:49,560 --> 00:37:52,759 Speaker 2: Lamanada Media is Vice President of Partnerships and Production is 717 00:37:52,840 --> 00:37:57,520 Speaker 2: Jackie Danziger. Executive producer from iHeart Podcast is Katrina Norvil. 718 00:37:57,920 --> 00:37:59,600 Speaker 2: Marketing lead is Alison Kanter. 719 00:38:00,360 --> 00:38:05,640 Speaker 1: Original music composed and produced by Takayasuzawa and Alex sugi Ura, 720 00:38:05,719 --> 00:38:10,440 Speaker 1: with additional music by Elijah Harvey. Dope Lab is executive 721 00:38:10,480 --> 00:38:14,040 Speaker 1: produced by us T T Show Dia and Kia Wattlei