1 00:00:01,720 --> 00:00:04,880 Speaker 1: Call Zon Media. 2 00:00:05,080 --> 00:00:07,520 Speaker 2: Welcome to Dick It app Here, a podcast where the 3 00:00:07,560 --> 00:00:11,720 Speaker 2: singular it is seemingly irrelevant now because everything is happening 4 00:00:11,840 --> 00:00:15,080 Speaker 2: all of the time. I'm your host, Miya Wong, And 5 00:00:15,800 --> 00:00:19,800 Speaker 2: one of the many, many, many chaotic things that has 6 00:00:19,880 --> 00:00:22,480 Speaker 2: been going on over the last two weeks since Trump's 7 00:00:22,520 --> 00:00:26,439 Speaker 2: power has been a bunch of funding freezes to the 8 00:00:26,760 --> 00:00:29,920 Speaker 2: US federal government grant system. And I think to a 9 00:00:29,960 --> 00:00:32,920 Speaker 2: lot of people that doesn't sound like an enormously big deal, 10 00:00:33,400 --> 00:00:38,239 Speaker 2: but that is unbelievably catastrophic for like I would go 11 00:00:38,280 --> 00:00:39,960 Speaker 2: so far to say, is like the survival of the 12 00:00:40,040 --> 00:00:42,440 Speaker 2: human species for reasons they will get to in a second, 13 00:00:42,800 --> 00:00:46,080 Speaker 2: but unbelievably bad for the quality of life of everyone 14 00:00:46,440 --> 00:00:49,040 Speaker 2: on Earth. And to get to kind of a sense 15 00:00:49,200 --> 00:00:52,559 Speaker 2: of exactly what this kind of stuff does, what these 16 00:00:52,560 --> 00:00:55,840 Speaker 2: funding freezes do, and what the sort of threat, particularly 17 00:00:55,920 --> 00:00:59,520 Speaker 2: to the future of American science is, I have brought 18 00:00:59,520 --> 00:01:02,720 Speaker 2: in two people who are intimately familiar with this Arguvon Salis, 19 00:01:02,720 --> 00:01:06,440 Speaker 2: who's a surgeon and professor of medicine and friend of 20 00:01:06,480 --> 00:01:07,200 Speaker 2: the show. 21 00:01:07,600 --> 00:01:08,840 Speaker 3: Yeah, come on. 22 00:01:08,959 --> 00:01:11,160 Speaker 2: Yeah, definitely. I I don't know why I had such 23 00:01:11,160 --> 00:01:13,520 Speaker 2: a hesitant friend of the show, because it wasn't in 24 00:01:13,560 --> 00:01:16,240 Speaker 2: my notes that was that was ad living it. But yeah, 25 00:01:16,240 --> 00:01:18,080 Speaker 2: friend of the show, Kami Hoda, who is a Gas 26 00:01:18,080 --> 00:01:21,319 Speaker 2: show entrologist and the host of the podcast House of Pods, 27 00:01:21,360 --> 00:01:22,920 Speaker 2: and both of you two, welcome to the show. 28 00:01:23,440 --> 00:01:24,760 Speaker 3: Thank you so much for having us. 29 00:01:24,959 --> 00:01:25,640 Speaker 4: Yeah, thank you. 30 00:01:25,959 --> 00:01:28,880 Speaker 3: I'm excited to be here for your most Persian episode ever. 31 00:01:32,680 --> 00:01:33,240 Speaker 3: For sure. 32 00:01:34,000 --> 00:01:37,280 Speaker 2: We may have done episodes of like that were like 33 00:01:37,640 --> 00:01:38,520 Speaker 2: about a row. 34 00:01:38,600 --> 00:01:42,440 Speaker 1: Yeah, this is a Persians a bit too Persian doctors 35 00:01:42,520 --> 00:01:45,959 Speaker 1: talking about Trump is about as Persian as a good 36 00:01:46,000 --> 00:01:48,560 Speaker 1: and you're not You're not overselling it. This is a 37 00:01:48,880 --> 00:01:52,680 Speaker 1: large scale attack on the healthcare infrastructure of the United 38 00:01:52,720 --> 00:01:56,480 Speaker 1: States on a massive level, So you're not lying. It 39 00:01:56,680 --> 00:01:59,040 Speaker 1: is a serious, serious issue, not just for us but 40 00:01:59,040 --> 00:01:59,800 Speaker 1: for the whole world. 41 00:02:00,280 --> 00:02:00,480 Speaker 3: Yeah. 42 00:02:00,560 --> 00:02:01,800 Speaker 2: And one of the I mean the places I want 43 00:02:01,840 --> 00:02:04,000 Speaker 2: to start, I think is with because it was happening 44 00:02:04,040 --> 00:02:07,480 Speaker 2: I think in n s FNIH a bit before this happened. 45 00:02:07,760 --> 00:02:10,919 Speaker 2: But the OPM, the Office of Personnel Management, sent out 46 00:02:10,919 --> 00:02:15,040 Speaker 2: this memo last week that was a it was nominally 47 00:02:15,040 --> 00:02:19,799 Speaker 2: a response to this very weird Trump executive order. That's 48 00:02:20,560 --> 00:02:23,440 Speaker 2: him being like every single program that has to do 49 00:02:23,480 --> 00:02:25,520 Speaker 2: with civil rights, which is like, so, my my description 50 00:02:25,680 --> 00:02:27,120 Speaker 2: was anything it has to do with civil rights at all, 51 00:02:27,160 --> 00:02:30,400 Speaker 2: like gone. His description of it is like dei and woke, 52 00:02:30,760 --> 00:02:33,359 Speaker 2: so like anything it has to do with queer people, 53 00:02:33,440 --> 00:02:36,280 Speaker 2: anything that has to do with like racial inequality. And 54 00:02:36,320 --> 00:02:39,000 Speaker 2: they were supposed to like go through and review every 55 00:02:39,080 --> 00:02:42,720 Speaker 2: single government grant program for anything. 56 00:02:42,960 --> 00:02:47,480 Speaker 4: But don't forget he also included the gender ideology, which 57 00:02:47,520 --> 00:02:51,040 Speaker 4: is a meaningless praise and the Green New Deal is 58 00:02:51,040 --> 00:02:51,560 Speaker 4: all part of. 59 00:02:51,480 --> 00:02:54,440 Speaker 2: It, yep, yep, yep, you know, and this is part 60 00:02:54,480 --> 00:02:57,480 Speaker 2: of the raft of executive voters, particularly the anti trans 61 00:02:57,480 --> 00:03:00,840 Speaker 2: executive voters. But OPM's response to this an awful Personnel 62 00:03:00,840 --> 00:03:03,720 Speaker 2: Management's response was to just freeze literally every single grant 63 00:03:03,720 --> 00:03:07,280 Speaker 2: program in the country. And this was everything from pell 64 00:03:07,360 --> 00:03:10,360 Speaker 2: grants and like work study for college students, to like 65 00:03:10,480 --> 00:03:13,480 Speaker 2: food aid for single mothers to my personal favorite and 66 00:03:13,520 --> 00:03:15,480 Speaker 2: I don't know why this never made it into the press, 67 00:03:15,480 --> 00:03:17,160 Speaker 2: because I'm apparently the only one who went through and 68 00:03:17,200 --> 00:03:19,400 Speaker 2: read the list, but one of the things that he 69 00:03:19,480 --> 00:03:23,720 Speaker 2: froze funding for was security patrols for nuclear weapons manufacturing sites. 70 00:03:24,400 --> 00:03:30,040 Speaker 2: So like we almost like, why, yeah, why is that included? 71 00:03:30,200 --> 00:03:32,440 Speaker 2: It was because literally what happened was they found a 72 00:03:32,480 --> 00:03:36,440 Speaker 2: list of every single grant that like anyone does like 73 00:03:36,440 --> 00:03:38,640 Speaker 2: and any like program that gives out grants, and they 74 00:03:38,680 --> 00:03:40,240 Speaker 2: froze all of them, and so like another one of 75 00:03:40,280 --> 00:03:42,360 Speaker 2: them that when I said this is like, this is 76 00:03:42,360 --> 00:03:43,920 Speaker 2: a threat to all life on Earth, I was not 77 00:03:43,960 --> 00:03:45,760 Speaker 2: I was not joking here. One of the other ones 78 00:03:45,800 --> 00:03:49,040 Speaker 2: was defunding one of the very important like international nuclear 79 00:03:49,080 --> 00:03:51,800 Speaker 2: non proliferation organizations, like specifically the one that's there to 80 00:03:51,800 --> 00:03:55,040 Speaker 2: make sure that like random people don't get like enriched 81 00:03:55,160 --> 00:03:59,000 Speaker 2: uranium or like obtain nuclear weapons. So like we we 82 00:03:59,480 --> 00:04:02,400 Speaker 2: dodged a like giant nuke sized bullet. When when like 83 00:04:02,880 --> 00:04:05,520 Speaker 2: most of these programs got their money back after a 84 00:04:05,600 --> 00:04:07,880 Speaker 2: judge was like, well, you obviously can't do this. This 85 00:04:08,000 --> 00:04:13,520 Speaker 2: is so unbelievably illegal that it's astounding, Like the Constitution 86 00:04:13,760 --> 00:04:16,520 Speaker 2: like very blatantly says that the power of the purse 87 00:04:16,640 --> 00:04:17,960 Speaker 2: is Congress, not the president. 88 00:04:17,960 --> 00:04:20,840 Speaker 4: Eight like stop, yeah, but I would just want to 89 00:04:20,880 --> 00:04:24,320 Speaker 4: clarify for the people listening here that it wasn't just 90 00:04:24,520 --> 00:04:29,440 Speaker 4: grant specifically, it was like all federal assistance. So one 91 00:04:29,520 --> 00:04:32,400 Speaker 4: of the things that was very confusing and chaotic was 92 00:04:32,839 --> 00:04:35,400 Speaker 4: this question of does this mean Snap is gone? Does 93 00:04:35,400 --> 00:04:38,040 Speaker 4: this mean Wick is gone? What about headst what about 94 00:04:38,120 --> 00:04:41,320 Speaker 4: meals on wheels? I mean, there are tons of federal 95 00:04:41,360 --> 00:04:44,320 Speaker 4: assistance programs out there, and they had only made an 96 00:04:44,320 --> 00:04:48,280 Speaker 4: exception for Social Security and medic care in the memo, 97 00:04:48,360 --> 00:04:51,200 Speaker 4: but not Medicaid. And what happened the next day, but 98 00:04:51,240 --> 00:04:53,000 Speaker 4: the Medicaid portal went down? 99 00:04:53,200 --> 00:04:55,919 Speaker 2: Right, Yeah, And it's chaotic too because like all of 100 00:04:55,920 --> 00:04:58,240 Speaker 2: the programs you just named were on the list of 101 00:04:58,440 --> 00:05:00,359 Speaker 2: like programs that they were putting a freeze on, but 102 00:05:00,360 --> 00:05:03,000 Speaker 2: then it wasn't clear what was going to happen with them, end. 103 00:05:03,279 --> 00:05:06,039 Speaker 3: Right, And it's still not right, right. 104 00:05:06,120 --> 00:05:07,520 Speaker 2: Yeah, we just have a judge. 105 00:05:07,560 --> 00:05:09,599 Speaker 4: We have We found one judge with a backbone in 106 00:05:09,640 --> 00:05:13,200 Speaker 4: the entire country so far, and he said, no, you cannot. 107 00:05:13,400 --> 00:05:13,640 Speaker 2: Yeah. 108 00:05:13,880 --> 00:05:16,440 Speaker 1: Yeah, I am surprised actually that Trump hasn't gone out 109 00:05:16,480 --> 00:05:19,200 Speaker 1: on the attack. Maybe I just missed it, like attacking 110 00:05:19,240 --> 00:05:20,800 Speaker 1: that judge, you know. 111 00:05:21,200 --> 00:05:22,040 Speaker 3: But it is. 112 00:05:22,440 --> 00:05:24,560 Speaker 1: I mean, what's so confusing to me is, you know, 113 00:05:24,600 --> 00:05:26,200 Speaker 1: I get it, at least in some part of their 114 00:05:26,200 --> 00:05:32,719 Speaker 1: weird internal terrible logic, transphobic logic. I get why they're 115 00:05:32,760 --> 00:05:35,160 Speaker 1: doing some of the things they're doing. But then some 116 00:05:35,200 --> 00:05:38,839 Speaker 1: of them don't even make sense within their own whack 117 00:05:39,279 --> 00:05:43,800 Speaker 1: internal logic, like when they scrub, for example, the CDC 118 00:05:44,040 --> 00:05:47,440 Speaker 1: for all the terms that they didn't like, gender terms, 119 00:05:47,560 --> 00:05:51,080 Speaker 1: transgender terms, things like that. They also scrub things like 120 00:05:51,360 --> 00:05:56,839 Speaker 1: following maternal morbidity or opioid use, things that don't, at 121 00:05:56,920 --> 00:06:01,479 Speaker 1: least on the surface, even fit with their attacks on 122 00:06:01,839 --> 00:06:05,320 Speaker 1: woke ideology. So it seems like it's a complete mess 123 00:06:05,320 --> 00:06:08,440 Speaker 1: to me what's happening. And it's what's terrifying about it 124 00:06:08,480 --> 00:06:10,560 Speaker 1: is not just that it's a mess, but it is happening. 125 00:06:10,680 --> 00:06:12,840 Speaker 1: I mean, they are doing it, they are pushing it, 126 00:06:12,880 --> 00:06:15,320 Speaker 1: even though they clearly don't even seem to really know 127 00:06:15,360 --> 00:06:18,320 Speaker 1: what they're doing or even have a great sense internally 128 00:06:18,360 --> 00:06:19,039 Speaker 1: of what they're doing. 129 00:06:19,760 --> 00:06:21,560 Speaker 2: I think that's the danger of this right now, is 130 00:06:21,560 --> 00:06:25,159 Speaker 2: that this is revenge. Right They're lashing out in sort 131 00:06:25,160 --> 00:06:28,359 Speaker 2: of in pure anger and pure hatred, and they have 132 00:06:28,480 --> 00:06:31,400 Speaker 2: been given control of an apparatus that they don't understand 133 00:06:31,440 --> 00:06:33,520 Speaker 2: at all, Right Like that, that's how you get defunding 134 00:06:33,520 --> 00:06:35,960 Speaker 2: a nuclear police. That's how you get them defunding like 135 00:06:36,240 --> 00:06:39,800 Speaker 2: the very Goldwater Memorial grant thing that gives money to 136 00:06:39,880 --> 00:06:44,719 Speaker 2: kids who're writing essays about Bury Goldwater. They don't understand 137 00:06:44,760 --> 00:06:46,520 Speaker 2: what the state is and what it does, and they're 138 00:06:46,520 --> 00:06:48,120 Speaker 2: just trying to take the whole thing apart, and they're 139 00:06:48,160 --> 00:06:50,080 Speaker 2: just trying to sort of rampage their way through it. 140 00:06:50,120 --> 00:06:51,920 Speaker 2: And it means that we're in this situation now where 141 00:06:51,920 --> 00:06:54,320 Speaker 2: like for a long time, the line on like trans 142 00:06:54,400 --> 00:06:57,039 Speaker 2: Rice was like, well, you should defend trans Rice because 143 00:06:57,040 --> 00:06:59,040 Speaker 2: they're going to come for you next, And that's no 144 00:06:59,080 --> 00:07:01,920 Speaker 2: longer true. This is actually happening here is in order 145 00:07:01,960 --> 00:07:04,720 Speaker 2: to kill us. They are willing to kill every sit 146 00:07:04,800 --> 00:07:07,680 Speaker 2: They're willing to let all of you die in nuclear fire. 147 00:07:08,760 --> 00:07:11,360 Speaker 2: It's like specifically in order to hurt us. Right, that's 148 00:07:11,360 --> 00:07:13,840 Speaker 2: the sort of line we're at where you know, all 149 00:07:13,880 --> 00:07:16,320 Speaker 2: of these all of these sort of complicated systems and 150 00:07:16,360 --> 00:07:18,640 Speaker 2: all of these sort of complicated funding mechanisms are just 151 00:07:18,760 --> 00:07:22,160 Speaker 2: getting lit on fire by people who don't understand what 152 00:07:22,160 --> 00:07:23,440 Speaker 2: they're doing and don't care. 153 00:07:24,000 --> 00:07:26,840 Speaker 3: Right, just out of spider or something, for sure, out. 154 00:07:26,720 --> 00:07:29,040 Speaker 4: Of fight and hate. But I want to just take 155 00:07:29,080 --> 00:07:31,120 Speaker 4: a step back and think about the fact that all 156 00:07:31,120 --> 00:07:34,320 Speaker 4: of this is happening because of two versus three executive orders, 157 00:07:34,320 --> 00:07:37,040 Speaker 4: depending how you think about it. But they're literally executive orders. 158 00:07:37,040 --> 00:07:39,240 Speaker 4: They are not laws in the books. In Congress did 159 00:07:39,320 --> 00:07:43,400 Speaker 4: not pass anything. It's like this elderly man woke up 160 00:07:43,440 --> 00:07:47,400 Speaker 4: and said, hey, let's get rid of DEI and d 161 00:07:47,600 --> 00:07:49,680 Speaker 4: I A for example, those are the terms they use 162 00:07:49,760 --> 00:07:54,800 Speaker 4: exactly without saying what DEI is or what DEI A is, 163 00:07:54,880 --> 00:07:56,920 Speaker 4: And just I feel that we need to pause for 164 00:07:56,920 --> 00:07:59,440 Speaker 4: a moment on the A de I A and they 165 00:07:59,520 --> 00:08:03,040 Speaker 4: spell out, you know, as we're accessible. Wiping out everything 166 00:08:03,080 --> 00:08:07,120 Speaker 4: related to accessibility is directly in violation of the ADA 167 00:08:07,440 --> 00:08:09,680 Speaker 4: and makes no sense and is cool and all of that, 168 00:08:09,760 --> 00:08:12,720 Speaker 4: but also just like legally, it makes no kind of 169 00:08:12,760 --> 00:08:14,800 Speaker 4: sense unless they are going to go after the ADA, 170 00:08:14,880 --> 00:08:17,440 Speaker 4: which I'm guessing is part of their plan to the 171 00:08:17,480 --> 00:08:20,200 Speaker 4: extent that there is a plan. But the two key 172 00:08:20,240 --> 00:08:22,960 Speaker 4: executive orders here are the sex and gender. One that's 173 00:08:23,120 --> 00:08:28,160 Speaker 4: defending quote unquote defending women, that basically dictates that sex 174 00:08:28,400 --> 00:08:33,599 Speaker 4: must be only male and female, thereby erasing intersex people completely, 175 00:08:34,080 --> 00:08:37,400 Speaker 4: and that there's really either essentially saying there's no such 176 00:08:37,440 --> 00:08:40,640 Speaker 4: thing as gender and that the only genders that they 177 00:08:41,000 --> 00:08:43,960 Speaker 4: see are willing to recognize are male and female, there 178 00:08:43,960 --> 00:08:47,640 Speaker 4: by erasing trans folks, intersect people, non binary folks, cutter 179 00:08:47,640 --> 00:08:50,480 Speaker 4: a gender, queer, gender whood, all of those people. So 180 00:08:50,559 --> 00:08:53,520 Speaker 4: for them to go into like the CDC data sets, 181 00:08:53,720 --> 00:08:56,920 Speaker 4: take them offline so that they can binarize whatever is 182 00:08:56,960 --> 00:08:59,280 Speaker 4: there eliminate I'm assuming I don't I mean, I don't 183 00:08:59,320 --> 00:09:01,199 Speaker 4: know that this is not I'm assuming that that's what 184 00:09:01,240 --> 00:09:04,000 Speaker 4: they're doing, taking any sex that thought male or female 185 00:09:04,080 --> 00:09:06,920 Speaker 4: out of there, and then removing gender as a varia 186 00:09:06,960 --> 00:09:09,240 Speaker 4: will because they've said that no grant funding should go 187 00:09:09,240 --> 00:09:13,480 Speaker 4: to any assessment of gender period. So that's when you're 188 00:09:13,520 --> 00:09:15,720 Speaker 4: talking to me about like how they're willing to throw 189 00:09:15,760 --> 00:09:20,000 Speaker 4: everyone under the bus just to pursue this transphobic agenda. 190 00:09:20,080 --> 00:09:22,320 Speaker 4: That's what you're talking about. They're willing to take huge 191 00:09:22,360 --> 00:09:25,959 Speaker 4: lots of information off of the Internet so people can 192 00:09:26,000 --> 00:09:29,320 Speaker 4: no longer research or position. Anyone else can no longer 193 00:09:29,360 --> 00:09:32,240 Speaker 4: access this information, just to make sure that there is 194 00:09:32,320 --> 00:09:36,040 Speaker 4: no hint or reference to anyone who is transgender. That 195 00:09:36,120 --> 00:09:39,320 Speaker 4: seems to be like the key thing that they're trying 196 00:09:39,320 --> 00:09:40,800 Speaker 4: to do with all of this. So they have thrown 197 00:09:40,800 --> 00:09:43,720 Speaker 4: the entire government and take chaos and the lives of 198 00:09:43,760 --> 00:09:47,360 Speaker 4: millions of people into chaos all to remove the t 199 00:09:48,280 --> 00:09:49,079 Speaker 4: in LGBP. 200 00:09:49,480 --> 00:09:52,000 Speaker 2: Yeah, and the stuff that they're doing, like the destruction 201 00:09:52,080 --> 00:09:54,320 Speaker 2: of this research data, the way that it's been just 202 00:09:54,400 --> 00:09:57,920 Speaker 2: like taken down and destroyed. Little parts of it have 203 00:09:58,000 --> 00:10:00,440 Speaker 2: come back up after the sort of backlash, but you 204 00:10:00,480 --> 00:10:03,160 Speaker 2: know what they're what they're doing is staging a digital 205 00:10:03,240 --> 00:10:06,080 Speaker 2: version of the nazis burning all of the books at 206 00:10:06,080 --> 00:10:08,679 Speaker 2: the Institute Sexual Research. Like that's that's exposedly what they're doing. 207 00:10:08,720 --> 00:10:11,880 Speaker 2: It's it's literally the same stuff, like it is research 208 00:10:11,960 --> 00:10:14,840 Speaker 2: on queerness and trans people that they are lighting on fire. 209 00:10:15,360 --> 00:10:15,560 Speaker 4: Yep. 210 00:10:17,400 --> 00:10:20,240 Speaker 2: And you know you know who else lights research on 211 00:10:20,360 --> 00:10:23,200 Speaker 2: queer and trans people on fire. It's it's the sponsors 212 00:10:23,280 --> 00:10:25,120 Speaker 2: of this show. It's the products of services. 213 00:10:25,679 --> 00:10:28,520 Speaker 3: Yeah, that's the way you get those big bucks. That's 214 00:10:28,520 --> 00:10:30,960 Speaker 3: how you do it. That's professional broadcasting. 215 00:10:41,480 --> 00:10:45,120 Speaker 2: And we are back. So I want to move from 216 00:10:45,240 --> 00:10:48,839 Speaker 2: that to kind of the next phase after we got 217 00:10:48,840 --> 00:10:53,400 Speaker 2: out of the sort of oh PM like suspending everything phase, 218 00:10:53,440 --> 00:10:56,520 Speaker 2: which has been this kind of this uncertainty around a 219 00:10:56,520 --> 00:11:00,480 Speaker 2: whole bunch of the other funding agencies for science, National 220 00:11:00,480 --> 00:11:03,920 Speaker 2: Science Foundation, National Institutes of Health. Can you talk a 221 00:11:03,920 --> 00:11:06,559 Speaker 2: bit about what's been going on with grants there before 222 00:11:06,559 --> 00:11:09,000 Speaker 2: we move into like how this whole process works. 223 00:11:09,720 --> 00:11:13,400 Speaker 4: Yeah, So the first sign that something was materially going 224 00:11:13,440 --> 00:11:17,319 Speaker 4: to change after these executive orders, as I recall, I'm 225 00:11:17,360 --> 00:11:20,000 Speaker 4: living this along with everyone else, and what is time. 226 00:11:20,280 --> 00:11:22,880 Speaker 4: But the first thing that I recall is the study 227 00:11:22,880 --> 00:11:28,120 Speaker 4: section being canceled. The study sections are meeting where scientists 228 00:11:28,120 --> 00:11:32,479 Speaker 4: come together. They each will have read various grant proposals 229 00:11:32,600 --> 00:11:35,840 Speaker 4: and scored them on a number of different dimensions, and 230 00:11:35,880 --> 00:11:38,920 Speaker 4: then they come together and discussed. They don't discuss all 231 00:11:38,960 --> 00:11:40,679 Speaker 4: of them, by the way, They only dissuess the ones 232 00:11:40,679 --> 00:11:43,120 Speaker 4: that have that seem to have the most merit, and 233 00:11:43,160 --> 00:11:46,400 Speaker 4: then out of those they make recommendations for which ones 234 00:11:46,440 --> 00:11:51,319 Speaker 4: they believe should get funded. So these are a critical 235 00:11:51,440 --> 00:11:54,280 Speaker 4: part of the process by which the government gives out 236 00:11:54,320 --> 00:11:57,800 Speaker 4: funds for research. If these meetings do not happen, people 237 00:11:57,960 --> 00:12:01,640 Speaker 4: grants are not getting evaluated us and recommended for funding. 238 00:12:01,760 --> 00:12:03,920 Speaker 4: That means they're not getting the funding. That means they're 239 00:12:03,920 --> 00:12:06,880 Speaker 4: not hiring people, or they're having to fire people they 240 00:12:06,920 --> 00:12:09,200 Speaker 4: already had in their layoff, people they already had in 241 00:12:09,240 --> 00:12:12,400 Speaker 4: their lab. They're not able to continue the important work 242 00:12:12,440 --> 00:12:15,640 Speaker 4: that they are doing they may lose their job, like 243 00:12:15,760 --> 00:12:18,480 Speaker 4: really truly people can lose their job because they were 244 00:12:18,520 --> 00:12:22,440 Speaker 4: not able to secure enough funding to support themselves and 245 00:12:22,480 --> 00:12:25,680 Speaker 4: their labs. So these are really really important meetings, and 246 00:12:25,760 --> 00:12:28,520 Speaker 4: those have been canceled for both the NSF and the 247 00:12:28,640 --> 00:12:31,600 Speaker 4: nih for at least the last couple of weeks. And 248 00:12:31,920 --> 00:12:35,800 Speaker 4: as of yesterday, I saw doctor Megan Ray said that 249 00:12:35,920 --> 00:12:38,600 Speaker 4: her or not maybe not her, but that study sections 250 00:12:38,760 --> 00:12:41,520 Speaker 4: were canceled yesterday that were due to happen today. So 251 00:12:41,559 --> 00:12:45,120 Speaker 4: there had been some communication around perhaps the free of 252 00:12:45,160 --> 00:12:48,120 Speaker 4: those activities ending on February first today that we're recording 253 00:12:48,160 --> 00:12:51,840 Speaker 4: as February third, and those study sections for today were canceled. 254 00:12:51,880 --> 00:12:55,800 Speaker 4: On the other hand, NSS, which is obviously a separate organization, 255 00:12:56,760 --> 00:13:00,679 Speaker 4: has informally I've heard this that they were going to 256 00:13:00,800 --> 00:13:03,480 Speaker 4: resume some body sections, although they haven't rexamped yet. 257 00:13:03,720 --> 00:13:06,080 Speaker 1: And if I did add, just to be totally clear 258 00:13:06,120 --> 00:13:11,000 Speaker 1: with your listeners, these are incredibly important organizations for discovery 259 00:13:11,520 --> 00:13:16,400 Speaker 1: of new medical breakthroughs and for pushing science forward. For 260 00:13:16,520 --> 00:13:19,440 Speaker 1: the NAIH, for example, the nih IS is a big 261 00:13:19,440 --> 00:13:22,319 Speaker 1: part of the reason we have mRNA vaccines now. They 262 00:13:22,360 --> 00:13:25,320 Speaker 1: were the ones helping to promote that research for decades 263 00:13:25,600 --> 00:13:27,880 Speaker 1: before we were able to turn them into vaccines, and 264 00:13:28,040 --> 00:13:29,760 Speaker 1: because a lot of what they did that we're able 265 00:13:29,760 --> 00:13:33,839 Speaker 1: to do that when we're looking for new breakthroughs and 266 00:13:33,880 --> 00:13:36,440 Speaker 1: we're looking for something where patient comes to us and 267 00:13:36,480 --> 00:13:39,240 Speaker 1: they're like, isn't there anything we've tried everything, isn't there 268 00:13:39,240 --> 00:13:41,360 Speaker 1: anything that we could at least try or some trial 269 00:13:41,440 --> 00:13:44,360 Speaker 1: that we could be involved in. That's where we find 270 00:13:44,360 --> 00:13:47,400 Speaker 1: these things. These are the things that we're talking about, 271 00:13:47,480 --> 00:13:52,280 Speaker 1: these really important healthcare infrastructure that we're discussing. 272 00:13:53,160 --> 00:13:56,920 Speaker 2: Yeah, and you know between NAH and National Science Foundation 273 00:13:57,080 --> 00:13:59,439 Speaker 2: and you know, Department of Energies having a similar thing 274 00:13:59,480 --> 00:14:02,960 Speaker 2: to this, because Department of Energy funds all like high 275 00:14:03,000 --> 00:14:05,160 Speaker 2: energy physics research, so all of your sort of like 276 00:14:05,160 --> 00:14:08,360 Speaker 2: particle accelerator or stuff like that. It's not just sort 277 00:14:08,400 --> 00:14:10,959 Speaker 2: of like the National Labs for example, that they get 278 00:14:10,960 --> 00:14:13,320 Speaker 2: funding from these places, although you know National Labs are like, 279 00:14:13,480 --> 00:14:15,760 Speaker 2: you know, you get your funding from grants like everyone else. 280 00:14:16,200 --> 00:14:17,760 Speaker 2: But you know, I mean, this is this is all 281 00:14:17,800 --> 00:14:20,840 Speaker 2: the way down to the level of like undergrads and 282 00:14:20,920 --> 00:14:25,480 Speaker 2: college chemistry labs like they're they are getting paid out 283 00:14:25,480 --> 00:14:28,600 Speaker 2: of these grants from National Science Foundation from the National 284 00:14:28,600 --> 00:14:31,720 Speaker 2: Institute's for Health, Like all of these all of these 285 00:14:31,840 --> 00:14:34,520 Speaker 2: institutions pay out everything, and it's like this is the 286 00:14:34,560 --> 00:14:39,600 Speaker 2: basis of how all science almost all science. Like there's 287 00:14:39,600 --> 00:14:41,960 Speaker 2: some private sector stuff, but the thing is like the 288 00:14:42,240 --> 00:14:45,640 Speaker 2: giant private like Bell Labs, right, like you're your old 289 00:14:45,680 --> 00:14:48,960 Speaker 2: school giant private sector. Here's our giant R and D thing. 290 00:14:49,040 --> 00:14:51,160 Speaker 2: Like that's all kind of gone, so you know, like 291 00:14:51,200 --> 00:14:52,840 Speaker 2: the only people who are getting funded by this are 292 00:14:52,960 --> 00:14:56,920 Speaker 2: like weird startup guys. And it's like, Okay, look look 293 00:14:56,760 --> 00:15:00,520 Speaker 2: look what they've invented in the last like fifty years. 294 00:15:00,600 --> 00:15:04,800 Speaker 2: It's like cryptocurrency NFTs, which is cryptocurrency again. 295 00:15:04,680 --> 00:15:06,000 Speaker 3: Theranos don't forget. 296 00:15:06,080 --> 00:15:09,960 Speaker 2: Yeah, they dose the metaverse juicer row like they're they're 297 00:15:10,000 --> 00:15:12,240 Speaker 2: doing great. It's really great. And people will be like, oh, 298 00:15:12,280 --> 00:15:15,640 Speaker 2: the Veta eye. It's like no National Labs were using 299 00:15:15,680 --> 00:15:18,320 Speaker 2: those AA algorithms like a decade and a half ago. 300 00:15:18,440 --> 00:15:20,560 Speaker 2: It's like, yeah, the generative blah blah. Okay, we're not 301 00:15:20,760 --> 00:15:23,720 Speaker 2: we're not here to get into me complaining about generative AI. 302 00:15:23,840 --> 00:15:29,280 Speaker 2: Go go go go listen to Edgittern's entire like yeah, yeah. 303 00:15:29,560 --> 00:15:31,160 Speaker 4: I mean I think the bottom line of what you're 304 00:15:31,160 --> 00:15:33,920 Speaker 4: trying to communicate here is that a lot of scientific 305 00:15:33,960 --> 00:15:38,960 Speaker 4: and medical breakthroughs have come from labs and from researchers 306 00:15:39,000 --> 00:15:42,160 Speaker 4: who have been funded by the NFF and the NIH 307 00:15:42,280 --> 00:15:44,800 Speaker 4: And I will just say as an academic, these are 308 00:15:44,840 --> 00:15:49,560 Speaker 4: certainly the kind of premiere funding opportunities that we have. 309 00:15:49,800 --> 00:15:52,440 Speaker 4: Like it also was really critical in the careers of 310 00:15:53,040 --> 00:15:55,520 Speaker 4: researchers to be able to show that their work is 311 00:15:55,600 --> 00:15:57,600 Speaker 4: worthy of this kind of funding. And that's part of 312 00:15:57,640 --> 00:16:01,000 Speaker 4: why I would think people's jobs, the people we pay 313 00:16:01,040 --> 00:16:03,640 Speaker 4: off of our grants, but also people like me, our 314 00:16:03,720 --> 00:16:07,320 Speaker 4: jobs can be really dependent on whether we get this 315 00:16:07,400 --> 00:16:08,120 Speaker 4: funding or not. 316 00:16:08,640 --> 00:16:11,800 Speaker 2: And it's a generational thing too, because the students also 317 00:16:11,880 --> 00:16:14,000 Speaker 2: need this funding. And so people people who are undergrads, 318 00:16:14,040 --> 00:16:17,680 Speaker 2: particularly people who are like doctoral students, like their research, right, 319 00:16:17,800 --> 00:16:20,920 Speaker 2: Like the stuff that they're doing while they're in graduate school, 320 00:16:20,920 --> 00:16:23,400 Speaker 2: like getting PhD so they can become scientists. That's all 321 00:16:23,480 --> 00:16:26,360 Speaker 2: also like funded by these grants. And if that stuff 322 00:16:26,560 --> 00:16:29,440 Speaker 2: goes away, like, it's not just that you're obliterating this 323 00:16:29,560 --> 00:16:32,440 Speaker 2: generation of science, like you're decapping the next like three 324 00:16:32,560 --> 00:16:35,360 Speaker 2: generations of scientists, right, because each one of them down 325 00:16:35,360 --> 00:16:38,160 Speaker 2: the line suddenly doesn't have the research experience that they're 326 00:16:38,160 --> 00:16:38,960 Speaker 2: supposed to have. 327 00:16:39,000 --> 00:16:40,360 Speaker 3: Exactly, yeah, right. 328 00:16:40,400 --> 00:16:42,560 Speaker 4: And also, who would want to go into science if 329 00:16:42,600 --> 00:16:45,240 Speaker 4: it's going to be right, if there's just going to 330 00:16:45,320 --> 00:16:47,560 Speaker 4: be like some random person who goes into the White 331 00:16:47,600 --> 00:16:50,120 Speaker 4: House and never mind, we're not doing that anymore. Who 332 00:16:50,120 --> 00:16:53,080 Speaker 4: are to be exposed to those kinds of wins. 333 00:16:53,240 --> 00:16:57,400 Speaker 1: A lot of the smartest doctors and scientists I know 334 00:16:58,200 --> 00:17:00,760 Speaker 1: that tend to be risk averse people. I mean, there's 335 00:17:00,800 --> 00:17:03,840 Speaker 1: a lot of people the CDC that could try to 336 00:17:03,960 --> 00:17:07,439 Speaker 1: maybe sue for you know, for not being able to 337 00:17:07,520 --> 00:17:09,240 Speaker 1: use the terms that they want to use and study 338 00:17:09,280 --> 00:17:11,600 Speaker 1: the things they want to study, and they might even 339 00:17:11,800 --> 00:17:13,840 Speaker 1: I don't know, maybe they could win. You talk to 340 00:17:13,880 --> 00:17:16,800 Speaker 1: Laurier about that. Seems unlikely because they're not private sector. 341 00:17:16,920 --> 00:17:20,280 Speaker 1: But to them, they're not going to because they're living 342 00:17:20,320 --> 00:17:21,399 Speaker 1: paycheck to paycheck too. 343 00:17:21,480 --> 00:17:24,880 Speaker 3: Some of these people that are the lower levels, people that. 344 00:17:24,920 --> 00:17:27,159 Speaker 1: Aren't making a ton of money and they have livelihoods 345 00:17:27,160 --> 00:17:29,000 Speaker 1: that they're trying to maintain, they're not going to try 346 00:17:29,000 --> 00:17:32,359 Speaker 1: and rock the boat when it comes to these things. 347 00:17:32,480 --> 00:17:35,800 Speaker 1: It's putting them in a really tenuous position already, they're 348 00:17:35,800 --> 00:17:38,840 Speaker 1: already worried about their next grant or their next what 349 00:17:38,960 --> 00:17:40,760 Speaker 1: however they're going to fund their labs. 350 00:17:41,520 --> 00:17:43,480 Speaker 4: Yeah, and I just want to highlight that postdocs I 351 00:17:43,520 --> 00:17:48,159 Speaker 4: think are particularly vulnerable because they are often like this 352 00:17:48,440 --> 00:17:51,840 Speaker 4: NFF where you actually demonstrated this girl, they aren't as 353 00:17:51,840 --> 00:17:55,119 Speaker 4: said like, they're definitely often living paycheck paycheck. And what 354 00:17:55,160 --> 00:17:57,320 Speaker 4: the NFF freeze did was that it made it so 355 00:17:57,480 --> 00:18:00,399 Speaker 4: close could not get their next paycheck. Yeah, because we 356 00:18:00,400 --> 00:18:02,280 Speaker 4: were this was happening at the end of the month, right, 357 00:18:02,320 --> 00:18:05,439 Speaker 4: So it was delaying people getting their next paycheck. And 358 00:18:05,480 --> 00:18:08,240 Speaker 4: in particular and talking about POSTOC, yes, it can affect 359 00:18:08,280 --> 00:18:11,880 Speaker 4: graduate students as well, but a lot of postdoc funding, 360 00:18:12,040 --> 00:18:14,159 Speaker 4: like one of the grants that I have actually we 361 00:18:14,200 --> 00:18:18,800 Speaker 4: worked directly with postdoctoral and some predoctoral, but many postdoctoral 362 00:18:18,840 --> 00:18:22,800 Speaker 4: training programs that fund POSTOC. And to the extent that 363 00:18:22,880 --> 00:18:25,600 Speaker 4: any of those grants are put on hold, that is 364 00:18:26,000 --> 00:18:29,600 Speaker 4: threatening the income of people who really don't have buffer, 365 00:18:29,760 --> 00:18:31,680 Speaker 4: who cannot afford to not get paid. 366 00:18:32,000 --> 00:18:34,280 Speaker 2: And also, you know, and this is another aspect of 367 00:18:34,320 --> 00:18:38,639 Speaker 2: this too, and I really doubt they understand this, but 368 00:18:38,840 --> 00:18:41,120 Speaker 2: you know, there's also a lot of postdocs who are 369 00:18:41,119 --> 00:18:44,159 Speaker 2: not from the US right there, who are either international students, 370 00:18:44,240 --> 00:18:46,920 Speaker 2: international students who are just you know, coming in from 371 00:18:47,280 --> 00:18:51,040 Speaker 2: other countries. And those people, if you suddenly don't have 372 00:18:51,080 --> 00:18:53,840 Speaker 2: a grant, you don't have a job, and that is 373 00:18:54,280 --> 00:18:57,679 Speaker 2: really really bad for your immigration status. Like that that 374 00:18:57,800 --> 00:19:00,000 Speaker 2: is enough to get you kicked out of the US. 375 00:19:00,160 --> 00:19:03,040 Speaker 2: And this is the thing that's constantly leveraged in sort 376 00:19:03,040 --> 00:19:05,639 Speaker 2: of labor organizing, right or like one of the threats 377 00:19:05,680 --> 00:19:06,920 Speaker 2: that universities will make. 378 00:19:07,119 --> 00:19:08,480 Speaker 3: Usually they do it implicitly. 379 00:19:08,520 --> 00:19:11,040 Speaker 2: Sometimes they'll just go out and say it very legally, 380 00:19:11,080 --> 00:19:13,359 Speaker 2: will be like Okay, if if you this postoc or 381 00:19:13,400 --> 00:19:16,359 Speaker 2: like you, this grad student like tries to like join 382 00:19:16,400 --> 00:19:19,040 Speaker 2: this union, like your legal status in the US is 383 00:19:19,080 --> 00:19:23,320 Speaker 2: going to be compromised. But that's another sort of risk 384 00:19:23,480 --> 00:19:27,359 Speaker 2: from this is like those people's ability to stay in 385 00:19:27,400 --> 00:19:31,119 Speaker 2: the US and not get reported basically. 386 00:19:31,400 --> 00:19:33,000 Speaker 3: Exactly, yeah, exactly. 387 00:19:33,040 --> 00:19:35,359 Speaker 1: And then then we talk about bringing in you know, 388 00:19:35,440 --> 00:19:37,119 Speaker 1: I know there's a lot of internal debate right now 389 00:19:37,160 --> 00:19:40,040 Speaker 1: between the publican party on you know, bringing in people 390 00:19:40,080 --> 00:19:43,399 Speaker 1: to work these jobs and bringing in these minds. But 391 00:19:43,840 --> 00:19:46,879 Speaker 1: this is a clear example of where the United States 392 00:19:46,880 --> 00:19:49,439 Speaker 1: has excelled in the past. We've been able to bring 393 00:19:49,480 --> 00:19:52,000 Speaker 1: in great minds from all over the world to help 394 00:19:52,080 --> 00:19:55,359 Speaker 1: us work on research and to help us come to 395 00:19:55,440 --> 00:19:57,399 Speaker 1: work in these labs. I mean you go to like 396 00:19:57,560 --> 00:19:59,960 Speaker 1: USA Staff and Stanford and you see these people work 397 00:20:00,000 --> 00:20:03,800 Speaker 1: making these labs on important stuff. And that's another like, 398 00:20:04,119 --> 00:20:05,240 Speaker 1: that's that's that's something. 399 00:20:05,080 --> 00:20:05,840 Speaker 3: We're gonna lose. 400 00:20:05,880 --> 00:20:08,360 Speaker 1: And I hope we don't lose it permanently. I hope 401 00:20:08,359 --> 00:20:11,240 Speaker 1: it's not, you know something like you say, well last 402 00:20:11,320 --> 00:20:14,280 Speaker 1: generations worth of damage. But it's hard to see how 403 00:20:14,280 --> 00:20:15,240 Speaker 1: it won't at this point. 404 00:20:16,000 --> 00:20:18,800 Speaker 4: Yeah, I was just looking up one hundred percent agree 405 00:20:18,800 --> 00:20:21,280 Speaker 4: and to your point about how much of the science 406 00:20:21,720 --> 00:20:23,800 Speaker 4: and even other amazing things that are done in the 407 00:20:23,840 --> 00:20:27,520 Speaker 4: country are are done by immigrants. I think it's over 408 00:20:27,760 --> 00:20:30,600 Speaker 4: just over a third of Nobel laureates from the United 409 00:20:30,680 --> 00:20:33,960 Speaker 4: States have been immigrants to the United States. 410 00:20:33,640 --> 00:20:35,680 Speaker 2: You know, And it's sort it's sort of a nationalist thing, right, 411 00:20:35,720 --> 00:20:39,119 Speaker 2: but like for ninety nine percent of the time for 412 00:20:39,200 --> 00:20:42,080 Speaker 2: better like, the US has been very very good at 413 00:20:42,240 --> 00:20:45,120 Speaker 2: absorbing other country scientists. When you know this, like we 414 00:20:45,119 --> 00:20:47,840 Speaker 2: we got to you know, okay, so like it's hard 415 00:20:47,840 --> 00:20:49,440 Speaker 2: to take too much credit for it because we also 416 00:20:49,520 --> 00:20:51,440 Speaker 2: took a bunch of scientists from the Nazi like from 417 00:20:51,520 --> 00:20:54,440 Speaker 2: the actual Nazis, but we also like a bunch of 418 00:20:54,520 --> 00:20:57,120 Speaker 2: very famous US scientists, Like we're in the US because 419 00:20:57,119 --> 00:20:59,840 Speaker 2: they were fleeing the rise of the Nazis. And you know, 420 00:21:00,160 --> 00:21:01,920 Speaker 2: we are looking at a situation where we are going 421 00:21:01,920 --> 00:21:03,800 Speaker 2: to be the opposite of this, where like our scientists 422 00:21:03,800 --> 00:21:07,800 Speaker 2: are going to be fleeing everywhere else because our government 423 00:21:07,880 --> 00:21:09,719 Speaker 2: is being run by these people. 424 00:21:10,480 --> 00:21:13,080 Speaker 4: Yeah, and I wanted to highlight, I think that's literal 425 00:21:13,080 --> 00:21:15,399 Speaker 4: all really great points about the effect of not getting 426 00:21:15,400 --> 00:21:18,159 Speaker 4: the funding and who it trickles down to. But I 427 00:21:18,200 --> 00:21:21,040 Speaker 4: also wanted to highlight that there's two different kind of 428 00:21:21,400 --> 00:21:25,160 Speaker 4: ways that the funding can be withheld. The one is 429 00:21:25,640 --> 00:21:29,000 Speaker 4: just that review process and not actually reviewing grants. Right, So, 430 00:21:29,119 --> 00:21:32,080 Speaker 4: like I personally submitted a proposal in the fall, who 431 00:21:32,119 --> 00:21:35,119 Speaker 4: knows if when that will get discussed. There are people 432 00:21:35,119 --> 00:21:37,320 Speaker 4: in that kind of position where they maybe were dependent 433 00:21:37,480 --> 00:21:40,399 Speaker 4: on or really hoping to get funding this round, and 434 00:21:40,440 --> 00:21:43,240 Speaker 4: now they don't know if or when that proposal will 435 00:21:43,240 --> 00:21:45,320 Speaker 4: get reviewed. Of course, you never know if you're going 436 00:21:45,359 --> 00:21:47,200 Speaker 4: to get funded, but to not even have a chance 437 00:21:47,240 --> 00:21:51,879 Speaker 4: at review is an unanticipated barrier. Then On the other side, 438 00:21:52,200 --> 00:21:56,320 Speaker 4: there's people who have been funded and are in the 439 00:21:56,320 --> 00:21:58,480 Speaker 4: position that I'm in, which is not knowing whether I'm 440 00:21:58,480 --> 00:22:02,960 Speaker 4: going to receive the next payment. Because the NIH, so 441 00:22:03,040 --> 00:22:05,679 Speaker 4: I have a five year grant and we are currently 442 00:22:05,720 --> 00:22:09,040 Speaker 4: in year three. Every year you have to submit a 443 00:22:09,119 --> 00:22:13,000 Speaker 4: status update on your project, and then they determine, based 444 00:22:13,040 --> 00:22:15,520 Speaker 4: on lots of different things, including what budget they are 445 00:22:15,560 --> 00:22:18,760 Speaker 4: given from Congress, how much of the funds that they 446 00:22:18,760 --> 00:22:21,080 Speaker 4: had originally projected they'll be able to give to you. 447 00:22:21,560 --> 00:22:24,439 Speaker 4: And there are, as you can imagine, a lot of 448 00:22:24,480 --> 00:22:28,000 Speaker 4: people who are doing work that's related to health disparities, 449 00:22:28,119 --> 00:22:32,920 Speaker 4: help equity, women's health, LGBTQ health, et cetera, who now 450 00:22:32,960 --> 00:22:36,439 Speaker 4: do not know if our work falls under quote unquote 451 00:22:36,440 --> 00:22:40,359 Speaker 4: DEI or deia or gender ideology or all these vague 452 00:22:40,440 --> 00:22:43,720 Speaker 4: terms that the administration is using, and so we actually 453 00:22:43,720 --> 00:22:46,639 Speaker 4: don't know whether, like for me, I don't know if 454 00:22:46,640 --> 00:22:48,640 Speaker 4: I'm going to get my next set of funds. In July, 455 00:22:48,840 --> 00:22:50,920 Speaker 4: so I was in the process of interviewing to hire 456 00:22:50,960 --> 00:22:54,800 Speaker 4: someone to join my lab, and I genuinely don't know 457 00:22:54,840 --> 00:22:58,400 Speaker 4: whether I should hire someone at knowing that I may 458 00:22:58,440 --> 00:23:01,959 Speaker 4: lose funds, and you know, five months or do I 459 00:23:02,040 --> 00:23:04,280 Speaker 4: just try to make do without? And then that's a 460 00:23:04,359 --> 00:23:06,199 Speaker 4: job that no one gets. And if you play that 461 00:23:06,280 --> 00:23:09,159 Speaker 4: out over the three hundred thousand people who are funded 462 00:23:09,160 --> 00:23:12,040 Speaker 4: in various ways by the NIH, you start to understand 463 00:23:12,080 --> 00:23:14,760 Speaker 4: the scope of damage that's being done here. 464 00:23:15,440 --> 00:23:21,120 Speaker 1: Can you tell people what your current grant is? And 465 00:23:21,240 --> 00:23:25,960 Speaker 1: because I think that is pertin into this conversation, yes, yes, yes. 466 00:23:25,760 --> 00:23:29,960 Speaker 4: You're right. Okay, So my grant is called ending sexual 467 00:23:30,000 --> 00:23:34,520 Speaker 4: Harassment Teaching of Principal Investigators as a q acronym E STOPS. 468 00:23:34,600 --> 00:23:37,879 Speaker 4: So our goal is to try to help people intervene 469 00:23:37,960 --> 00:23:41,600 Speaker 4: when there is sexual harassment, with the ultimate goal decreasing 470 00:23:41,640 --> 00:23:45,440 Speaker 4: the amount of sexual harassment that's happening in biomedical research. 471 00:23:45,600 --> 00:23:47,760 Speaker 2: Oh they don't, they don't what you do with that? 472 00:23:48,040 --> 00:23:48,119 Speaker 4: Like? 473 00:23:48,920 --> 00:23:54,280 Speaker 1: Oh no, right, because one of the great terrible ironies 474 00:23:54,280 --> 00:23:56,919 Speaker 1: of this whole thing is that their argument is that 475 00:23:56,920 --> 00:23:59,639 Speaker 1: they're doing a lot of this to protect women, the 476 00:24:00,600 --> 00:24:04,440 Speaker 1: sanctity of women or whatever this is. You know, I'm 477 00:24:04,600 --> 00:24:08,040 Speaker 1: hopeful that I'm wrong for you. I hope that this 478 00:24:08,119 --> 00:24:10,320 Speaker 1: is not the case, but I could see them very 479 00:24:10,359 --> 00:24:14,880 Speaker 1: easily saying that this somehow fits underwoke ideology and even 480 00:24:14,920 --> 00:24:19,400 Speaker 1: though it's something clearly that is designed to help not 481 00:24:19,440 --> 00:24:22,200 Speaker 1: just women, but a lot of women could benefit from this, 482 00:24:22,720 --> 00:24:22,919 Speaker 1: you know. 483 00:24:23,960 --> 00:24:27,480 Speaker 4: Yeah, and to your point, like everyone is at risk 484 00:24:27,560 --> 00:24:30,679 Speaker 4: for hearingcing sexual harassment, it's just that the majority of 485 00:24:30,720 --> 00:24:34,280 Speaker 4: folks who experience that are women or sexual engender minorities. 486 00:24:34,440 --> 00:24:37,719 Speaker 4: And so yeah, I've really, obviously, as you can imagine, 487 00:24:37,840 --> 00:24:41,720 Speaker 4: been thinking a lot about how they are interpreting these 488 00:24:41,760 --> 00:24:44,919 Speaker 4: words that they're using and whether sexual harassment, which by 489 00:24:44,960 --> 00:24:47,040 Speaker 4: the way, is a form of discrimination, Like is that 490 00:24:47,240 --> 00:24:49,160 Speaker 4: DEI is stopping discrimination? 491 00:24:49,520 --> 00:24:55,159 Speaker 3: DEI? Who? Well, you know, quickly, if I may, I 492 00:24:55,160 --> 00:24:56,080 Speaker 3: can go over this. 493 00:24:56,840 --> 00:25:00,359 Speaker 1: There was this email that was dispersed from the the 494 00:25:00,400 --> 00:25:03,000 Speaker 1: CDC about terms that were no longer going to be used, 495 00:25:03,000 --> 00:25:06,200 Speaker 1: that were going to be scrubbed from the CDC's databases. 496 00:25:06,200 --> 00:25:13,000 Speaker 1: And they include words like gender, transgender, pregnant person, pregnant people, LGBT, transsexual, 497 00:25:13,040 --> 00:25:14,679 Speaker 1: non binary, non binary. 498 00:25:15,480 --> 00:25:17,960 Speaker 2: They use both to one with a hyphen and without 499 00:25:17,960 --> 00:25:18,639 Speaker 2: the hyphen. 500 00:25:18,720 --> 00:25:21,480 Speaker 1: Signed male at birth, assign female at birth, biologically male, 501 00:25:21,560 --> 00:25:24,880 Speaker 1: or biologically female. So anything that terms like that they're 502 00:25:24,920 --> 00:25:27,280 Speaker 1: gonna scrub Wait, let me, can I. 503 00:25:27,320 --> 00:25:30,360 Speaker 4: Just clarify that, because actually it's even worse, I think, 504 00:25:30,400 --> 00:25:33,399 Speaker 4: than what you just described, because what they actually said 505 00:25:33,440 --> 00:25:35,960 Speaker 4: in that email, as I understand it, is that there's 506 00:25:36,040 --> 00:25:38,280 Speaker 4: all these researchers who work at the CDC. So they said, 507 00:25:38,720 --> 00:25:42,520 Speaker 4: if you have submitted a manuscript for publication to any 508 00:25:42,560 --> 00:25:45,920 Speaker 4: scientific or medical journal that has any of these words 509 00:25:45,960 --> 00:25:51,399 Speaker 4: in it, you must retract that manuscript. So it's even 510 00:25:51,520 --> 00:25:54,760 Speaker 4: much much broader than just what's on the CDC's website. 511 00:25:54,760 --> 00:25:58,520 Speaker 4: It's any work that anyone employed by the CDC has done, 512 00:25:58,560 --> 00:26:00,840 Speaker 4: any researcher to say that they've done that they're in 513 00:26:00,880 --> 00:26:04,120 Speaker 4: the process of publishing, they have been asked to rescind 514 00:26:04,680 --> 00:26:09,520 Speaker 4: that work so that they can remove these god awful words, right, 515 00:26:10,080 --> 00:26:13,280 Speaker 4: that are actually words that are used routinely in science, 516 00:26:13,680 --> 00:26:15,879 Speaker 4: but they can no longer have them in their manuscripts. 517 00:26:15,880 --> 00:26:19,399 Speaker 4: And how nonsensical would their manuscript be without these words? 518 00:26:19,440 --> 00:26:21,639 Speaker 4: I mean, it's yeah, it's terrible. 519 00:26:21,920 --> 00:26:24,480 Speaker 1: The other thing that blows my mind about this is 520 00:26:24,560 --> 00:26:29,000 Speaker 1: how incredibly inefficient. Maybe that's the point, is how ridiculous 521 00:26:29,040 --> 00:26:31,199 Speaker 1: it's going to be. Who's going to be doing this, 522 00:26:31,320 --> 00:26:33,320 Speaker 1: who's going to be looking over this. To my knowledge, 523 00:26:33,359 --> 00:26:36,199 Speaker 1: there's only been one political point in regards to this, 524 00:26:36,240 --> 00:26:39,359 Speaker 1: and that's that the CDC. It's Susan Monerrez is the 525 00:26:39,440 --> 00:26:43,720 Speaker 1: acting director there at the CDC, and it's all going 526 00:26:43,800 --> 00:26:47,080 Speaker 1: to go through that one person. All every study is 527 00:26:47,080 --> 00:26:49,840 Speaker 1: going to go through that one person. It makes no sense. 528 00:26:49,920 --> 00:26:52,480 Speaker 1: I don't even understand how it's going to be enforced. 529 00:26:52,600 --> 00:26:56,320 Speaker 1: It's a ridiculous thing. I'm sure they're going to try 530 00:26:56,359 --> 00:26:58,840 Speaker 1: to make some examples out of people, but how are 531 00:26:58,880 --> 00:27:01,520 Speaker 1: they even enforced this. We're gonna find out what your grant, 532 00:27:01,560 --> 00:27:01,960 Speaker 1: I guess. 533 00:27:02,880 --> 00:27:06,480 Speaker 2: Yeah. I think the bleak thing about specifically the fact 534 00:27:06,480 --> 00:27:08,439 Speaker 2: that the study retractions and it's just you know, this 535 00:27:08,480 --> 00:27:11,040 Speaker 2: attempt to ban anyone from doing any research, right, is 536 00:27:11,040 --> 00:27:14,359 Speaker 2: that like the problem for them with medical research about 537 00:27:14,359 --> 00:27:16,840 Speaker 2: trans people is that everyone who's doing this who isn't 538 00:27:17,040 --> 00:27:21,840 Speaker 2: a like unbelievably rabid anti trans person from the beginning, 539 00:27:22,560 --> 00:27:24,840 Speaker 2: you know, looks at everything that they want to you 540 00:27:24,880 --> 00:27:26,760 Speaker 2: to trans people and goes, this is going to kill 541 00:27:26,920 --> 00:27:30,960 Speaker 2: unbelievable numbers of us. And I think like part of 542 00:27:31,000 --> 00:27:34,520 Speaker 2: what they're doing here is they're trying to before any 543 00:27:34,520 --> 00:27:36,199 Speaker 2: of this stuff come out, they're trying to stop the 544 00:27:36,240 --> 00:27:40,440 Speaker 2: scientific apparatus from revealing the fact that they are trying 545 00:27:40,440 --> 00:27:46,159 Speaker 2: to wipe us out. And that's yeah, an unbelievably bleak 546 00:27:46,359 --> 00:27:48,000 Speaker 2: thing to live through. 547 00:27:48,080 --> 00:27:55,680 Speaker 1: I guess, like, yeah, so sorry. I mean, honestly, I 548 00:27:55,720 --> 00:27:58,440 Speaker 1: wish I could say something more. It's really terrible. 549 00:27:58,840 --> 00:28:03,480 Speaker 2: I will say this like Jenny Wineley, because it never happens. Obviously, 550 00:28:03,520 --> 00:28:05,040 Speaker 2: the best the best thing you can do for trans 551 00:28:05,320 --> 00:28:08,359 Speaker 2: people is like something that involves the follow of the regime. 552 00:28:08,800 --> 00:28:11,399 Speaker 2: Like the second best thing is like hire us, because 553 00:28:11,440 --> 00:28:13,239 Speaker 2: no one does it and we can't no one can 554 00:28:13,280 --> 00:28:16,360 Speaker 2: get jobs, right and but like like that, the third 555 00:28:16,440 --> 00:28:20,159 Speaker 2: minimum thing after like money or like housing, is like 556 00:28:20,359 --> 00:28:22,400 Speaker 2: like check in on the trans people in your life 557 00:28:22,400 --> 00:28:25,200 Speaker 2: because nobody actually ever does it, and it means a 558 00:28:25,240 --> 00:28:27,680 Speaker 2: lot and it's not going to like stop the wrath 559 00:28:27,720 --> 00:28:29,520 Speaker 2: of the state. But like, I don't know, a lot 560 00:28:29,520 --> 00:28:31,280 Speaker 2: of people feel us alone. This This has been to 561 00:28:31,320 --> 00:28:34,119 Speaker 2: be a trans public service announcement. It's now over. 562 00:28:35,680 --> 00:28:39,360 Speaker 1: I think that's great advice. In other friend of the show, 563 00:28:39,480 --> 00:28:43,000 Speaker 1: Margaret Kiljoy that she also said, you know when you 564 00:28:43,080 --> 00:28:47,440 Speaker 1: hire people, you hire trans people, put them front of house, 565 00:28:47,920 --> 00:28:50,800 Speaker 1: make it visible, and then when you go and you 566 00:28:50,840 --> 00:28:53,880 Speaker 1: frequent these places, let them know that's part of why 567 00:28:53,920 --> 00:28:56,360 Speaker 1: you do it. Like, I like that you guys are 568 00:28:56,400 --> 00:28:59,000 Speaker 1: doing this. I'm here to support that. I mean, because 569 00:28:59,080 --> 00:29:01,720 Speaker 1: we're talking about money, talking with people's livelihoods or at stake, 570 00:29:02,280 --> 00:29:05,240 Speaker 1: and we have to show that these are people that 571 00:29:05,480 --> 00:29:08,680 Speaker 1: are not only employable but could benefit your business. 572 00:29:08,840 --> 00:29:11,440 Speaker 4: Yeah, honestly, I don't know what to say about it either, 573 00:29:11,640 --> 00:29:15,840 Speaker 4: aside from everything that they're doing is atrocious. It is 574 00:29:16,080 --> 00:29:22,400 Speaker 4: a scientific it is inhumane. It will it will harm people. 575 00:29:22,640 --> 00:29:25,520 Speaker 2: Yeah, people are going to die. People probably have already died. 576 00:29:26,000 --> 00:29:28,840 Speaker 2: If you're transit you're listening to this, fucking don't die. 577 00:29:29,040 --> 00:29:30,800 Speaker 2: Think about how good it's going to be to get 578 00:29:30,800 --> 00:29:33,360 Speaker 2: a piss on these people's graves in like eight years. 579 00:29:33,440 --> 00:29:38,840 Speaker 3: It's gonna but it is. 580 00:29:38,920 --> 00:29:39,160 Speaker 4: It is. 581 00:29:39,200 --> 00:29:42,920 Speaker 1: I agree, it is in dad to Argawan's point, it 582 00:29:43,040 --> 00:29:46,720 Speaker 1: is dumb on every metric. I can't think of a 583 00:29:46,720 --> 00:29:50,240 Speaker 1: single metric and that these actions are not hurtful and 584 00:29:50,400 --> 00:29:51,800 Speaker 1: going to harm us in the long run. 585 00:30:02,040 --> 00:30:04,000 Speaker 2: To close this out, this is a thing that I 586 00:30:04,040 --> 00:30:05,880 Speaker 2: think is very important because no one in the US 587 00:30:05,920 --> 00:30:08,960 Speaker 2: apparently seems to understand this at all. How does the 588 00:30:08,960 --> 00:30:12,200 Speaker 2: grant process actually work and what is it? Because you know, 589 00:30:12,480 --> 00:30:15,720 Speaker 2: this process is the difference between you, like having clean 590 00:30:15,800 --> 00:30:18,840 Speaker 2: water to drink and like that study that was going 591 00:30:18,840 --> 00:30:21,680 Speaker 2: to determine if your water is clean or not not happening. 592 00:30:21,760 --> 00:30:25,280 Speaker 4: Yeah, yeah, exactly. So you know, first thing I will 593 00:30:25,280 --> 00:30:27,640 Speaker 4: say is that the word grant applies to lots and 594 00:30:27,720 --> 00:30:30,760 Speaker 4: lots of different opportunities, and there are grants as small 595 00:30:30,800 --> 00:30:33,719 Speaker 4: as like one thousand or five thousand dollars in grants 596 00:30:33,760 --> 00:30:38,040 Speaker 4: as large as multimillion dollars, and the processes actually are 597 00:30:38,520 --> 00:30:40,840 Speaker 4: I mean, they're analogous, but they can be pretty different because, 598 00:30:40,880 --> 00:30:42,880 Speaker 4: as you can imagine, for a smaller grant, the amount 599 00:30:42,880 --> 00:30:44,400 Speaker 4: of work that you have to do to earn that 600 00:30:44,440 --> 00:30:47,320 Speaker 4: grant generally is a little bit less. But I can 601 00:30:47,360 --> 00:30:50,840 Speaker 4: speak in the most detail to the NIH review process 602 00:30:50,840 --> 00:30:53,800 Speaker 4: and specifically to these grants that they call R one 603 00:30:53,920 --> 00:30:56,640 Speaker 4: because are like kind of their fanciest grants that go 604 00:30:56,720 --> 00:30:59,560 Speaker 4: to individual researchers with their team, but it's led by 605 00:30:59,600 --> 00:31:02,320 Speaker 4: an individ researcher often. And the way this works is, 606 00:31:02,680 --> 00:31:04,400 Speaker 4: first of all, I want folks to understand it takes 607 00:31:04,400 --> 00:31:07,480 Speaker 4: a year from the time that you apply until the 608 00:31:07,520 --> 00:31:10,560 Speaker 4: time that you get money. Can take up to a 609 00:31:10,600 --> 00:31:14,320 Speaker 4: full calendar year, and so you put in an immense 610 00:31:14,320 --> 00:31:17,160 Speaker 4: amount of effort. So I'll use myself as an example. 611 00:31:17,160 --> 00:31:19,800 Speaker 4: I apply for a grant in October, huge amount of 612 00:31:19,840 --> 00:31:22,400 Speaker 4: effort I don't know how many hours leading up to 613 00:31:22,480 --> 00:31:25,720 Speaker 4: that brand submission, and then I just sit and wait 614 00:31:26,400 --> 00:31:31,600 Speaker 4: for months, months and months before there's even a study section. 615 00:31:31,680 --> 00:31:34,800 Speaker 4: If study section happens, and then after that, it's still 616 00:31:35,360 --> 00:31:38,880 Speaker 4: a couple more months before I might get information. It depends. 617 00:31:38,920 --> 00:31:41,120 Speaker 4: Of course, there's some variability there, but it's a long, 618 00:31:41,280 --> 00:31:43,480 Speaker 4: long process, is what I'm trying to say. And the 619 00:31:43,520 --> 00:31:46,480 Speaker 4: way the process starts is often you will send with 620 00:31:46,600 --> 00:31:49,360 Speaker 4: called the letter of interest to the agency that you're 621 00:31:49,360 --> 00:31:51,280 Speaker 4: applying to. So, as you said earlier, it's the National 622 00:31:51,320 --> 00:31:55,480 Speaker 4: Institutes of Health. So every institute has its own notice 623 00:31:55,480 --> 00:31:58,160 Speaker 4: of funding opportunities or no fos that are like, here's 624 00:31:58,200 --> 00:32:01,080 Speaker 4: what we're actually asking people to submit for at this 625 00:32:01,160 --> 00:32:04,360 Speaker 4: point in time, and then people will send a letter 626 00:32:04,400 --> 00:32:08,160 Speaker 4: of interest to the program officer. Each grant mechanism will 627 00:32:08,160 --> 00:32:10,760 Speaker 4: have its own grant off the program officer, and you 628 00:32:10,760 --> 00:32:13,240 Speaker 4: will send a letter of interest, maybe you get some feedback, 629 00:32:13,520 --> 00:32:16,040 Speaker 4: and then you move forward to the actual grant itself. 630 00:32:16,080 --> 00:32:18,280 Speaker 4: And I just want to say that it is more 631 00:32:18,320 --> 00:32:20,760 Speaker 4: work than probably anything else I've ever done, except maybe 632 00:32:20,760 --> 00:32:24,120 Speaker 4: my dissertation, and so it's a huge amount of work. 633 00:32:24,200 --> 00:32:28,560 Speaker 4: The R one includes, for example, a one page specific 634 00:32:28,600 --> 00:32:31,320 Speaker 4: aims page, which is you have the entirety of the 635 00:32:31,320 --> 00:32:34,800 Speaker 4: study somehow magically summarized in one page with your three aims. 636 00:32:34,800 --> 00:32:37,360 Speaker 4: And if that doesn't get the reviewer's attention, and if 637 00:32:37,360 --> 00:32:40,960 Speaker 4: they don't think it's compelling and interesting and important, that 638 00:32:41,040 --> 00:32:42,960 Speaker 4: may be the end. You may have done all the 639 00:32:42,960 --> 00:32:45,240 Speaker 4: rest of the work and they may only read that, 640 00:32:45,800 --> 00:32:48,600 Speaker 4: and then you have a twelve page These are single 641 00:32:48,640 --> 00:32:52,080 Speaker 4: space pages. Single space page is happing toward twelve page 642 00:32:52,360 --> 00:32:55,360 Speaker 4: research strategy. I don't know how many thousand words, thousands 643 00:32:55,360 --> 00:32:57,560 Speaker 4: of words that it's been, so I'm just telling you 644 00:32:57,600 --> 00:33:00,600 Speaker 4: twelve single space pages. There's a lot of effect about 645 00:33:00,600 --> 00:33:05,440 Speaker 4: your research. And it's like one of these puzzles where 646 00:33:05,440 --> 00:33:07,480 Speaker 4: it has to be exactly right and you have like 647 00:33:07,520 --> 00:33:09,400 Speaker 4: these figures and you have to get them exactly the 648 00:33:09,480 --> 00:33:11,480 Speaker 4: right size in the exact right place on the page 649 00:33:11,520 --> 00:33:13,920 Speaker 4: with the legend and everything, so that all magically sits 650 00:33:13,960 --> 00:33:16,360 Speaker 4: in these tall pages. Because if you don't do it right, 651 00:33:16,400 --> 00:33:19,920 Speaker 4: they will literally reject your grant for formatting problems, and 652 00:33:19,960 --> 00:33:22,520 Speaker 4: so you may have spent months writing this grant and 653 00:33:22,560 --> 00:33:26,240 Speaker 4: because you had the wrong size or the wrong margins 654 00:33:26,560 --> 00:33:28,959 Speaker 4: that they can literally choose not to even read it, 655 00:33:29,160 --> 00:33:32,000 Speaker 4: and then you're then having to wait till either six 656 00:33:32,040 --> 00:33:34,280 Speaker 4: months later if there's another opportunity, or sometimes a full 657 00:33:34,360 --> 00:33:35,920 Speaker 4: year later before you can try again. 658 00:33:36,560 --> 00:33:38,200 Speaker 2: Also, it's worth noting you also have to like do 659 00:33:38,320 --> 00:33:41,120 Speaker 2: a bunch of science. Like if it was just you 660 00:33:41,240 --> 00:33:44,920 Speaker 2: must do twelve you must write twelve pages of stuff 661 00:33:44,920 --> 00:33:47,320 Speaker 2: at formatta, it would probably be okay, But like you 662 00:33:47,360 --> 00:33:49,920 Speaker 2: also have to do science, like both for it and 663 00:33:50,080 --> 00:33:53,440 Speaker 2: also while you're doing it. 664 00:33:52,840 --> 00:33:57,000 Speaker 1: It's incredibly hard to get these. When someone gets a grant, 665 00:33:57,080 --> 00:33:59,719 Speaker 1: we all celebrate it for them because they're also excited 666 00:33:59,720 --> 00:34:02,400 Speaker 1: because you know, it's not easy. So what's funny about 667 00:34:02,400 --> 00:34:05,000 Speaker 1: that is the Republicans make it seem like all you 668 00:34:05,040 --> 00:34:06,959 Speaker 1: have to do is put in a couple of terms, 669 00:34:07,080 --> 00:34:10,720 Speaker 1: like you know, non binary, and you automatically get a grant. 670 00:34:10,800 --> 00:34:13,359 Speaker 1: They're like, no, idea, how like challenging it is? 671 00:34:13,440 --> 00:34:16,239 Speaker 2: No, It's like the only thing that could even potentially 672 00:34:16,280 --> 00:34:18,319 Speaker 2: work like that is to say, say whatever, you're doing 673 00:34:18,440 --> 00:34:21,239 Speaker 2: is cancer research, Like that's the actual thing, right, Like 674 00:34:21,280 --> 00:34:24,520 Speaker 2: so sometimes you could like defraud the DoD by telling 675 00:34:24,560 --> 00:34:27,719 Speaker 2: them like whatever research you're doing is camouflaged, like it's not. 676 00:34:28,040 --> 00:34:31,600 Speaker 2: It's even that is like it makes it like one 677 00:34:31,719 --> 00:34:35,440 Speaker 2: percent more likely that you're endless hours of work. 678 00:34:35,600 --> 00:34:37,719 Speaker 5: Yeah, I wish I could just by woke Ideology the 679 00:34:38,000 --> 00:34:41,439 Speaker 5: Future bulk pages and they're like ghetagras us. But yeah, 680 00:34:41,520 --> 00:34:43,319 Speaker 5: to your point, you have to part of what's in 681 00:34:43,360 --> 00:34:45,600 Speaker 5: those twelve pages is what is the work that you've 682 00:34:45,640 --> 00:34:48,799 Speaker 5: done that builds up to the work that you're proposing 683 00:34:48,880 --> 00:34:51,880 Speaker 5: to do, And that's stuff whole section called preliminary studies. 684 00:34:52,040 --> 00:34:54,600 Speaker 4: And what's in there very is depending on like what 685 00:34:54,680 --> 00:34:56,480 Speaker 4: kind of research you're doing. If you're doing animal research, 686 00:34:56,560 --> 00:34:59,240 Speaker 4: it might be various animal models that you've tested different 687 00:34:59,239 --> 00:35:01,680 Speaker 4: things on that straight for example, that you are able 688 00:35:01,719 --> 00:35:03,960 Speaker 4: to work with the specific animal model that you're proposing 689 00:35:04,000 --> 00:35:06,520 Speaker 4: to use in this study, and that you have the 690 00:35:07,080 --> 00:35:11,640 Speaker 4: specific methodological skills for whichever type of sace cellular analysis 691 00:35:11,719 --> 00:35:13,560 Speaker 4: or whatever it is that you're doing, that you have 692 00:35:13,640 --> 00:35:16,120 Speaker 4: those skills, that you have the equipment that you're able 693 00:35:16,160 --> 00:35:19,000 Speaker 4: to actually carry out that research because part of what 694 00:35:19,040 --> 00:35:22,239 Speaker 4: they're evaluating is can the person who's proposing to do 695 00:35:22,280 --> 00:35:24,640 Speaker 4: this work actually do the work. Last thing they want 696 00:35:24,640 --> 00:35:26,239 Speaker 4: to do is give you millions of dollars and have 697 00:35:26,239 --> 00:35:27,960 Speaker 4: you fall flat on your face because you don't have 698 00:35:28,040 --> 00:35:31,080 Speaker 4: the skills that are needed. So you have these pages. 699 00:35:31,160 --> 00:35:33,440 Speaker 4: Part of those cull pages like often a page two 700 00:35:33,600 --> 00:35:37,319 Speaker 4: three pages about what you have done to prepare for 701 00:35:37,480 --> 00:35:39,680 Speaker 4: the work that you're proposing, and a lot of times 702 00:35:39,719 --> 00:35:42,520 Speaker 4: to your point that work may or may not be funded. 703 00:35:42,560 --> 00:35:44,760 Speaker 4: You may have to if you're like at an academic institution, 704 00:35:45,080 --> 00:35:46,880 Speaker 4: you might be using your startup funds, you might be 705 00:35:46,880 --> 00:35:49,880 Speaker 4: trying to get smaller foundation grants or something to be 706 00:35:49,920 --> 00:35:51,959 Speaker 4: able to do that work, so that you can prove 707 00:35:52,080 --> 00:35:54,319 Speaker 4: to the funding agency that you're able to do it. 708 00:35:54,640 --> 00:35:57,000 Speaker 4: And then in addition to this culltation thing, there are 709 00:35:58,120 --> 00:36:00,880 Speaker 4: a bunch of additional documents that are are required, Like 710 00:36:00,920 --> 00:36:03,759 Speaker 4: there's currently this will probably change, but currently there's like 711 00:36:03,800 --> 00:36:07,120 Speaker 4: a diversity plan, there is a how are you going 712 00:36:07,200 --> 00:36:09,960 Speaker 4: to treat participants to our women and minorities. There's like 713 00:36:10,000 --> 00:36:13,680 Speaker 4: an age document, there's a page about resources and facilities. 714 00:36:13,719 --> 00:36:16,080 Speaker 4: There's all these additional documents which again all have their 715 00:36:16,120 --> 00:36:19,760 Speaker 4: own specific formatting requirements. There's a project narrative which is shorter, 716 00:36:19,840 --> 00:36:21,480 Speaker 4: and then a project summary, which is longer. I think 717 00:36:21,520 --> 00:36:23,359 Speaker 4: I could have those backward way way way. It's all 718 00:36:23,400 --> 00:36:26,000 Speaker 4: these additional pages. It's not just the specific games and 719 00:36:26,200 --> 00:36:28,240 Speaker 4: just the reach of strategy. It's all of this plus 720 00:36:28,280 --> 00:36:30,839 Speaker 4: the budget and the budget justification, and like you could 721 00:36:30,880 --> 00:36:32,719 Speaker 4: just go on, but I think you start to understand 722 00:36:32,719 --> 00:36:35,799 Speaker 4: that there are many many files that go into a 723 00:36:35,840 --> 00:36:40,160 Speaker 4: single grant application, and it represents often months of work 724 00:36:40,360 --> 00:36:43,759 Speaker 4: for an individual and their collaborators. And if you have, 725 00:36:43,920 --> 00:36:47,360 Speaker 4: for example, another institution you're collaborating with, they all have 726 00:36:47,480 --> 00:36:49,640 Speaker 4: to do a bunch of this paperwork as well, and 727 00:36:49,680 --> 00:36:51,520 Speaker 4: there's a contract between the two and all this is 728 00:36:51,560 --> 00:36:54,320 Speaker 4: done just to have a chance of getting conded. 729 00:36:54,920 --> 00:36:57,680 Speaker 2: Yeah, and you know, the disruptions to the funding system, 730 00:36:58,000 --> 00:37:02,120 Speaker 2: the disruptions to the studies, the disruption to just the 731 00:37:02,160 --> 00:37:05,360 Speaker 2: payout means that like all of this work that you're doing, 732 00:37:06,080 --> 00:37:09,160 Speaker 2: you know, you have no idea whether whether like again, 733 00:37:09,200 --> 00:37:11,400 Speaker 2: all of this in some cases unpaid labor that you 734 00:37:11,440 --> 00:37:13,040 Speaker 2: have been doing for months and months and months like 735 00:37:13,560 --> 00:37:16,040 Speaker 2: could just not happen. Yes, And also like it's worth 736 00:37:16,080 --> 00:37:17,960 Speaker 2: noting too, Like you also have to like when you're 737 00:37:18,000 --> 00:37:21,400 Speaker 2: figuring out what you're going to be doing next, like 738 00:37:21,960 --> 00:37:23,960 Speaker 2: working out whether or not your grant even has a 739 00:37:24,040 --> 00:37:26,480 Speaker 2: chance of getting approved. Like that like is something that 740 00:37:26,560 --> 00:37:28,400 Speaker 2: is that is that is a long term decision that 741 00:37:28,400 --> 00:37:31,080 Speaker 2: determines like what like you know, what colleges you go to, 742 00:37:31,280 --> 00:37:33,120 Speaker 2: like what institutions you end up at, like all of 743 00:37:33,120 --> 00:37:35,080 Speaker 2: that kind of stuff, and like that thing being all 744 00:37:35,120 --> 00:37:36,120 Speaker 2: the stuffing up in the air. 745 00:37:36,400 --> 00:37:39,320 Speaker 4: And for people who run lab, yeah, trying to figure 746 00:37:39,360 --> 00:37:41,759 Speaker 4: out like can you so I don't personally work with 747 00:37:41,840 --> 00:37:44,359 Speaker 4: graduate students, but a lot of people do, So can 748 00:37:44,400 --> 00:37:48,120 Speaker 4: you afford to bring in and sponsor another support another 749 00:37:48,160 --> 00:37:51,480 Speaker 4: graduate student? Can you afford the support of another postdoc? 750 00:37:51,840 --> 00:37:55,400 Speaker 4: These are all long term decisions. These aren't just like oh, Okay, 751 00:37:55,320 --> 00:37:57,080 Speaker 4: I'm going to hire some for two months until I 752 00:37:57,120 --> 00:37:59,520 Speaker 4: find out the next thing. It's like you would you 753 00:37:59,560 --> 00:38:02,719 Speaker 4: want tom to people, especially trainees. So it makes it 754 00:38:02,920 --> 00:38:06,600 Speaker 4: very difficult for people who run labs to make those 755 00:38:06,640 --> 00:38:08,960 Speaker 4: decisions to bring people in because we don't want to 756 00:38:09,040 --> 00:38:11,880 Speaker 4: let people down. And so I think the kind of 757 00:38:12,000 --> 00:38:15,000 Speaker 4: intuitive and natural consequence is that people will bring in 758 00:38:15,520 --> 00:38:20,399 Speaker 4: fewer people, because that's less risky than bringing in more 759 00:38:20,400 --> 00:38:23,960 Speaker 4: people and then having to either cut their funding or 760 00:38:24,080 --> 00:38:26,160 Speaker 4: let them go or whatever later on when you don't 761 00:38:26,200 --> 00:38:28,880 Speaker 4: get the resources that you need. And I want to 762 00:38:28,880 --> 00:38:31,399 Speaker 4: just point out that institutions here have a major role 763 00:38:31,480 --> 00:38:33,800 Speaker 4: to play. And not all institutions, and by that I 764 00:38:33,840 --> 00:38:36,160 Speaker 4: mean higher education institutions, and not all of them are 765 00:38:36,440 --> 00:38:40,160 Speaker 4: equally resourced, obviously, but we all know that there are 766 00:38:40,239 --> 00:38:43,759 Speaker 4: quite a few in this country that have massive endowments, 767 00:38:44,120 --> 00:38:46,560 Speaker 4: and so are what is the plan there and what 768 00:38:46,640 --> 00:38:49,480 Speaker 4: is the support for the folks at their institutions. And 769 00:38:49,480 --> 00:38:52,040 Speaker 4: I'm not trying to be I'm not trying to oversimplify 770 00:38:52,080 --> 00:38:54,520 Speaker 4: what is in fact a very challenging issue. But it 771 00:38:54,560 --> 00:38:57,120 Speaker 4: would be nice, it would be fantastic if some of 772 00:38:57,160 --> 00:39:00,360 Speaker 4: these institutions came out and said, we understand that this 773 00:39:00,440 --> 00:39:03,400 Speaker 4: is a very challenging time, wereming committed to supporting the 774 00:39:03,440 --> 00:39:07,760 Speaker 4: work of our faculty, our graduate students, our postoc et cetera, 775 00:39:07,880 --> 00:39:11,400 Speaker 4: and we will and we will fund anyone who's funding 776 00:39:11,480 --> 00:39:13,120 Speaker 4: is withdrawn or withheld. 777 00:39:13,400 --> 00:39:15,839 Speaker 1: Let's just say it'd be nice if some of these 778 00:39:15,960 --> 00:39:20,480 Speaker 1: very important, prestigious academic institutions showed maybe at least the 779 00:39:20,520 --> 00:39:25,080 Speaker 1: same backbone as Costco. Yeah, it's all I ask. 780 00:39:25,400 --> 00:39:28,000 Speaker 4: Okay too, I want to highlight too. It's very early 781 00:39:28,120 --> 00:39:31,799 Speaker 4: yet in this game. But Brown did come out I 782 00:39:31,840 --> 00:39:35,000 Speaker 4: think it was yesterday or sometime over the weekend, stating 783 00:39:35,080 --> 00:39:40,680 Speaker 4: clearly that they remain committed to their values of academic freedom. Right. 784 00:39:40,719 --> 00:39:42,480 Speaker 4: So that's the way to say it, right, like, we 785 00:39:42,520 --> 00:39:47,360 Speaker 4: support our staff and employees and students faculty doing whatever 786 00:39:47,560 --> 00:39:51,560 Speaker 4: work they think is important. I think that that was 787 00:39:51,600 --> 00:39:55,400 Speaker 4: their roundabout way of saying, we're not abandoning the principles 788 00:39:55,440 --> 00:39:57,239 Speaker 4: of DEI. But who knows, but that's what they said. 789 00:39:57,239 --> 00:40:01,560 Speaker 4: But the Princeton Princeton actually put out their annual report 790 00:40:01,760 --> 00:40:05,200 Speaker 4: on DEI at Princeton, and I forget the exact worrying 791 00:40:05,200 --> 00:40:06,360 Speaker 4: and I don't have it in front of me, but 792 00:40:06,400 --> 00:40:10,560 Speaker 4: their president talked about how important it is to support 793 00:40:10,840 --> 00:40:14,040 Speaker 4: people from different backgrounds, et cetera, et cetera. So that 794 00:40:14,200 --> 00:40:16,280 Speaker 4: those two that are trying to do something, Yeah. 795 00:40:16,239 --> 00:40:17,880 Speaker 3: I remain hopeful. I remain hopeful. 796 00:40:17,960 --> 00:40:19,719 Speaker 2: Yeah. Also, I got I got to put in my 797 00:40:19,760 --> 00:40:22,640 Speaker 2: word at Costco hate here, which is they're currently screwing 798 00:40:22,680 --> 00:40:23,600 Speaker 2: over their unions. 799 00:40:23,719 --> 00:40:25,880 Speaker 3: So I thought they resolved it. I thought they actually 800 00:40:25,880 --> 00:40:28,600 Speaker 3: gave them. No, they didn't. They did in the page increase. 801 00:40:29,239 --> 00:40:30,560 Speaker 2: Yeah, it's not resolved yet. 802 00:40:31,160 --> 00:40:33,040 Speaker 3: I thought the hot Dog was still win fifty though, 803 00:40:33,080 --> 00:40:34,080 Speaker 3: So that's important for me. 804 00:40:35,320 --> 00:40:37,480 Speaker 2: Read Jamie Loftus's book, Raw DOGG. 805 00:40:38,080 --> 00:40:39,839 Speaker 3: I'm a doctor. I can't do that by law. 806 00:40:40,080 --> 00:40:44,319 Speaker 4: Yeah, but even the NFL came out today and said 807 00:40:44,320 --> 00:40:48,000 Speaker 4: that they're not going to end their d programs any Typetube. 808 00:40:48,120 --> 00:40:50,480 Speaker 4: NFL known for being all right. 809 00:40:51,360 --> 00:40:53,600 Speaker 2: I mean that is the thing though, right if if 810 00:40:53,600 --> 00:40:55,560 Speaker 2: if you want to understand why the NFL is doing that, 811 00:40:55,640 --> 00:40:57,399 Speaker 2: like look at who the current heads of the NFL 812 00:40:57,440 --> 00:41:00,600 Speaker 2: Players Association are and like who they're past heads for 813 00:41:00,600 --> 00:41:03,080 Speaker 2: the last like decade have been, and that will give 814 00:41:03,080 --> 00:41:05,279 Speaker 2: you an indication of like why it's like that. 815 00:41:05,800 --> 00:41:10,880 Speaker 3: So yeah, Mia follows football pretty closely. I can tell it. 816 00:41:10,920 --> 00:41:14,040 Speaker 2: Unfortunately, if you're coming from feed Also. Also, I kind 817 00:41:14,040 --> 00:41:16,880 Speaker 2: of owe the NFL Players Association because they did they 818 00:41:17,040 --> 00:41:18,799 Speaker 2: they did put out a statement in support of our 819 00:41:18,840 --> 00:41:19,759 Speaker 2: unionization drive. 820 00:41:20,000 --> 00:41:23,160 Speaker 3: So yeah, it was very sweet. 821 00:41:23,320 --> 00:41:25,839 Speaker 4: That's nice. Well, I do want to say one more 822 00:41:25,880 --> 00:41:29,560 Speaker 4: thing about the grant process, which is that often people 823 00:41:29,600 --> 00:41:33,280 Speaker 4: are submitting the same grant over and over and over 824 00:41:34,160 --> 00:41:38,000 Speaker 4: because the funding rates are so low, and so often 825 00:41:38,080 --> 00:41:42,600 Speaker 4: they will submit it the first time, get feedback, make changes, 826 00:41:42,880 --> 00:41:45,600 Speaker 4: resubmit later and again. As I pointed out, it's not 827 00:41:45,680 --> 00:41:48,359 Speaker 4: like this is a rolling submission process where any day 828 00:41:48,360 --> 00:41:51,480 Speaker 4: of the week you can submit. I think for most mechanism. Again, 829 00:41:51,520 --> 00:41:53,880 Speaker 4: there's going to be some variability from institute to institute, 830 00:41:53,880 --> 00:41:56,879 Speaker 4: but it's at most twice a year, so like if 831 00:41:56,920 --> 00:42:00,000 Speaker 4: they're if they reject it, hopefully they give you feedback. 832 00:42:00,000 --> 00:42:01,799 Speaker 4: By the way, sometimes you don't even get feed because 833 00:42:01,800 --> 00:42:04,759 Speaker 4: if you weren't one of the top grant applications, you 834 00:42:04,840 --> 00:42:07,760 Speaker 4: don't even get discussed. So you may not get feedback. 835 00:42:07,800 --> 00:42:10,320 Speaker 4: But let's say you get feedback, then you try again, 836 00:42:10,440 --> 00:42:12,239 Speaker 4: and then maybe you try again, and then maybe you 837 00:42:12,239 --> 00:42:15,400 Speaker 4: try again. So sometimes it can take many cycles of 838 00:42:15,400 --> 00:42:19,920 Speaker 4: this entire terrible process before you get funded one. And 839 00:42:20,280 --> 00:42:22,719 Speaker 4: to coveys point about efficiency or clear like, I mean, 840 00:42:23,080 --> 00:42:25,320 Speaker 4: if you think about it that way, that it's extremely 841 00:42:25,360 --> 00:42:27,359 Speaker 4: inefficient system. But the point I just wanted to make 842 00:42:27,480 --> 00:42:31,280 Speaker 4: is that people work really really hard to get these grants, 843 00:42:31,360 --> 00:42:33,160 Speaker 4: and for some of the folks right now who are 844 00:42:33,400 --> 00:42:35,880 Speaker 4: kind of in limbo waiting for study section Jerusalem. This 845 00:42:36,040 --> 00:42:40,040 Speaker 4: might be their third or fourth submission of something, and 846 00:42:40,160 --> 00:42:42,840 Speaker 4: they were really hoping this was going to be the chance. 847 00:42:42,920 --> 00:42:45,840 Speaker 4: Because at some point you can't keep pursuing unless you 848 00:42:45,880 --> 00:42:48,879 Speaker 4: have some other independent income, like often, at some point 849 00:42:48,880 --> 00:42:51,520 Speaker 4: you cannot keep pursuing a specific line of research. So 850 00:42:51,560 --> 00:42:54,640 Speaker 4: you have to think about what breakthrough is being put 851 00:42:54,680 --> 00:42:58,399 Speaker 4: on hold or will never be identified because of all 852 00:42:58,400 --> 00:43:01,440 Speaker 4: of this, Because someone might have been waiting and maybe 853 00:43:01,600 --> 00:43:04,320 Speaker 4: they can't wait for however long it takes to resolve 854 00:43:04,400 --> 00:43:07,640 Speaker 4: this freeze, and maybe they end up switching their career 855 00:43:07,719 --> 00:43:10,000 Speaker 4: path into something completely different. And I'll just say, like 856 00:43:10,040 --> 00:43:12,200 Speaker 4: even on a smaller scale, I had a grant that 857 00:43:12,600 --> 00:43:15,880 Speaker 4: a colleague and I submitted several years back that got funded. 858 00:43:16,080 --> 00:43:17,920 Speaker 4: That was a very competitive grant. It was not a 859 00:43:17,960 --> 00:43:21,040 Speaker 4: federal grant, It was a foundation, very competitive and we 860 00:43:21,040 --> 00:43:23,880 Speaker 4: were delighted. We were I mean just thrilled to get funded. 861 00:43:24,000 --> 00:43:26,120 Speaker 4: And then we could not in the end take the grant. 862 00:43:26,120 --> 00:43:28,200 Speaker 4: We did not do the work of the grant because 863 00:43:28,360 --> 00:43:31,240 Speaker 4: he ended up not being able to find an appointment 864 00:43:31,360 --> 00:43:32,840 Speaker 4: that was going to work for him in academia, and 865 00:43:32,880 --> 00:43:34,839 Speaker 4: so he went to industry, and so that work never 866 00:43:34,840 --> 00:43:37,840 Speaker 4: got done. To this day, that work has not been done. Yeah, 867 00:43:37,920 --> 00:43:40,200 Speaker 4: I would love for it to be done. But those 868 00:43:40,239 --> 00:43:43,400 Speaker 4: are the types of consequences that we're talking about when 869 00:43:43,400 --> 00:43:45,719 Speaker 4: we're looking at like what's happening with these funds and 870 00:43:45,760 --> 00:43:48,480 Speaker 4: the delay of distributing the funds and the chances that 871 00:43:48,600 --> 00:43:52,160 Speaker 4: funds will be revoked from people. They really changed the 872 00:43:52,200 --> 00:43:55,520 Speaker 4: course of not just individual lives, but of science. Yeah. 873 00:43:55,560 --> 00:43:57,560 Speaker 2: And I mean, like the most visual example I could 874 00:43:57,560 --> 00:44:01,640 Speaker 2: think about this was I knew some people who wanted 875 00:44:01,680 --> 00:44:03,920 Speaker 2: to work in a coronavirus lab in twenty nineteen and 876 00:44:03,960 --> 00:44:06,040 Speaker 2: couldn't do it because they didn't their PI didn't have 877 00:44:06,200 --> 00:44:08,080 Speaker 2: funding for We're got a coronavirus thing. It's like, oh, 878 00:44:08,120 --> 00:44:10,000 Speaker 2: it would have been useful if they if they got 879 00:44:10,080 --> 00:44:16,520 Speaker 2: that grant. So I think this is a decent enough 880 00:44:16,520 --> 00:44:18,440 Speaker 2: place to wrap up. I do have one thing that 881 00:44:18,480 --> 00:44:20,000 Speaker 2: I want to plug, which is something you were talking 882 00:44:20,040 --> 00:44:22,600 Speaker 2: about earlier, which is putting, which is these institutions like 883 00:44:22,719 --> 00:44:26,239 Speaker 2: coming out and backing their scientists right, And that's that's 884 00:44:26,239 --> 00:44:28,160 Speaker 2: the thing that you can do. You can put pressure 885 00:44:28,239 --> 00:44:31,000 Speaker 2: on these institutions to do the right thing. And so 886 00:44:31,400 --> 00:44:33,440 Speaker 2: it might be over by by by now, but like 887 00:44:33,520 --> 00:44:37,080 Speaker 2: literally as we were recording this, there was a protest 888 00:44:37,120 --> 00:44:42,359 Speaker 2: going on at NYU's hospital. Yeah, because they've cut off 889 00:44:42,680 --> 00:44:44,239 Speaker 2: care to transuse. 890 00:44:44,440 --> 00:44:45,760 Speaker 4: They cut off. 891 00:44:46,520 --> 00:44:49,440 Speaker 2: Yeah, And so you know, you can do this the 892 00:44:49,480 --> 00:44:52,000 Speaker 2: people who actually run these systems, and you know, and 893 00:44:52,160 --> 00:44:54,719 Speaker 2: the entire federal government. Right while the people running the 894 00:44:54,719 --> 00:44:57,640 Speaker 2: federal government are relying on everyone just sort of sitting 895 00:44:57,680 --> 00:45:00,000 Speaker 2: there being shocked, not knowing what to do and doing nothing, 896 00:45:00,640 --> 00:45:03,560 Speaker 2: and you know, you can go show up to the administrators, 897 00:45:03,760 --> 00:45:06,520 Speaker 2: the offices of the administrators at these places, and you 898 00:45:06,560 --> 00:45:08,680 Speaker 2: can confront them and you could be like, Okay, you're 899 00:45:09,080 --> 00:45:10,799 Speaker 2: either right here right now, you're going to be a 900 00:45:10,800 --> 00:45:12,400 Speaker 2: coward and you're going to go along with this, or 901 00:45:12,400 --> 00:45:12,960 Speaker 2: you're going to. 902 00:45:12,920 --> 00:45:14,640 Speaker 3: Go back your own people. Yeah. 903 00:45:14,760 --> 00:45:17,440 Speaker 2: Yeah, And that's something that you could do right now. 904 00:45:17,960 --> 00:45:19,839 Speaker 4: And I just want to add we didn't talk about 905 00:45:19,880 --> 00:45:22,239 Speaker 4: this earlier, but when we talked about the CDC and 906 00:45:22,280 --> 00:45:24,640 Speaker 4: everything that's been removed, one thing that's relevant to that 907 00:45:24,760 --> 00:45:26,600 Speaker 4: is that there's an Office for Research on Women's Health. 908 00:45:26,640 --> 00:45:29,360 Speaker 4: It's the only resource dedicated to women's health in the 909 00:45:29,520 --> 00:45:32,359 Speaker 4: entire National Institutes of Health. We do have a National 910 00:45:32,400 --> 00:45:34,600 Speaker 4: Institute of Children's Health. We do not have a National 911 00:45:34,600 --> 00:45:36,880 Speaker 4: Institute of Women's Health. We have an author for research 912 00:45:36,880 --> 00:45:37,520 Speaker 4: on women's health. 913 00:45:37,560 --> 00:45:40,920 Speaker 2: Right if we love the US government, Jesus. 914 00:45:41,280 --> 00:45:43,720 Speaker 4: Yeah, it gets worse. So the National Academy the Science 915 00:45:43,800 --> 00:45:46,560 Speaker 4: is Engineering in Medicine, which is, like I would say, 916 00:45:46,719 --> 00:45:50,000 Speaker 4: one of the most prestigious kind of academic organizations that existed. 917 00:45:50,600 --> 00:45:54,200 Speaker 4: A review of funding for women's health research at the NIH, 918 00:45:54,400 --> 00:45:56,720 Speaker 4: and they put out a report in December. It's pretty 919 00:45:56,760 --> 00:46:00,279 Speaker 4: scathing if you read it, and they share that from 920 00:46:00,280 --> 00:46:03,040 Speaker 4: twenty thirteen to twenty twenty three, research for women's health 921 00:46:03,160 --> 00:46:06,400 Speaker 4: was like eight point eight percent of the entire NIH 922 00:46:06,440 --> 00:46:12,640 Speaker 4: budget as a reminder, women are the population and just 923 00:46:12,840 --> 00:46:16,920 Speaker 4: a reminder, and they called for almost sixteen billion dollars 924 00:46:16,920 --> 00:46:19,360 Speaker 4: of additional funding to go to women's health research in 925 00:46:19,400 --> 00:46:21,880 Speaker 4: the coming five years and the creation of an Institute 926 00:46:21,880 --> 00:46:24,960 Speaker 4: for Women's Health. So what happened last week with almost 927 00:46:25,000 --> 00:46:27,480 Speaker 4: everything on the website for the Office of Research for 928 00:46:27,520 --> 00:46:28,680 Speaker 4: Women's Health was deleted. 929 00:46:28,800 --> 00:46:30,239 Speaker 3: Jesus Christ, it's gone. 930 00:46:30,360 --> 00:46:33,160 Speaker 4: So they're funding. An opportunities page is gone, their bios 931 00:46:33,200 --> 00:46:36,520 Speaker 4: about their staff are gone, their updates on advances in 932 00:46:36,640 --> 00:46:39,440 Speaker 4: medicine for women over the last twenty five years. Gone. 933 00:46:39,600 --> 00:46:43,640 Speaker 4: Their pages on maternal morbidity, immortality gone, the importance of 934 00:46:43,640 --> 00:46:46,919 Speaker 4: including women and minorities, and clinical trial gone, their page 935 00:46:46,920 --> 00:46:49,640 Speaker 4: on health equity gone. You get the picture. So all 936 00:46:49,760 --> 00:46:53,040 Speaker 4: of that except for just a very bare minimum landing 937 00:46:53,080 --> 00:46:56,799 Speaker 4: page and kind a link to the office of I 938 00:46:56,800 --> 00:46:58,600 Speaker 4: forget the official in the office. So that's an office 939 00:46:58,600 --> 00:47:01,800 Speaker 4: that works on autoimmune diseases. Like everything else is gone. 940 00:47:02,000 --> 00:47:04,440 Speaker 4: And so I did create a script. If anybody wants 941 00:47:04,480 --> 00:47:07,080 Speaker 4: to call their member of Congress, I have a script 942 00:47:07,160 --> 00:47:10,600 Speaker 4: for that, and the CDC pages that people can use 943 00:47:10,640 --> 00:47:12,759 Speaker 4: in terms of actions. That's something I think that is 944 00:47:13,320 --> 00:47:15,840 Speaker 4: about as real as it gets for us at this point. 945 00:47:16,040 --> 00:47:20,239 Speaker 4: And I think that the more we are emphatic in 946 00:47:20,280 --> 00:47:23,160 Speaker 4: our messaging that none of this is okay, that we 947 00:47:23,320 --> 00:47:26,800 Speaker 4: demand to have these resources back online, that we demand 948 00:47:26,840 --> 00:47:30,040 Speaker 4: to continue funding research on health disparities for all the 949 00:47:30,080 --> 00:47:33,640 Speaker 4: different groups affected, I think the better the chance is 950 00:47:33,640 --> 00:47:37,239 Speaker 4: that that actually happens. So that's out there if anybody wants. 951 00:47:36,960 --> 00:47:39,520 Speaker 2: That, Yeah, well we'll put links to that in the description. Also, 952 00:47:39,640 --> 00:47:41,399 Speaker 2: I'm going to put it a personal plug to call 953 00:47:41,440 --> 00:47:43,319 Speaker 2: your congress person to yell at them about all of 954 00:47:43,320 --> 00:47:47,200 Speaker 2: the anti trans stuff, because they are legitimately in a 955 00:47:47,200 --> 00:47:49,440 Speaker 2: flux point right now where the party is slipping back 956 00:47:49,440 --> 00:47:52,319 Speaker 2: and forward between just being like, yeah, whatever, we'll pass 957 00:47:52,360 --> 00:47:54,680 Speaker 2: a defense bill that like banchanz people from the military, 958 00:47:54,800 --> 00:47:57,160 Speaker 2: and we're going to stop things from happening, and so 959 00:47:57,480 --> 00:47:59,200 Speaker 2: this is the thing that can go either way and 960 00:47:59,200 --> 00:48:01,920 Speaker 2: getting yelled at by because situents legitimately does help with us. 961 00:48:02,320 --> 00:48:04,080 Speaker 3: So yep, absolutely, yeah, do that. 962 00:48:04,200 --> 00:48:05,880 Speaker 2: Do that too when you're called while you're calling what 963 00:48:05,920 --> 00:48:10,720 Speaker 2: the CDC, multiple things, different calls, even Yeah. 964 00:48:10,800 --> 00:48:12,480 Speaker 4: You might just want to put them on seed Dell 965 00:48:12,719 --> 00:48:14,520 Speaker 4: and make it, you know, on your drive if you 966 00:48:14,560 --> 00:48:16,480 Speaker 4: go into work, maybe every day on the drive you're 967 00:48:16,560 --> 00:48:19,520 Speaker 4: just calling, Hi, here's the issue of the day, because 968 00:48:19,640 --> 00:48:21,440 Speaker 4: there's no shortage of issues that we need to be 969 00:48:21,480 --> 00:48:22,239 Speaker 4: communicating now. 970 00:48:23,040 --> 00:48:26,160 Speaker 2: So, speaking of things in bios, where can people find 971 00:48:26,239 --> 00:48:28,600 Speaker 2: you two for stuff that you want to promote the 972 00:48:28,719 --> 00:48:30,600 Speaker 2: way you do, et cetera, et cetera. 973 00:48:30,880 --> 00:48:33,680 Speaker 4: I mean, I'm on all the things, even the terrible thing, 974 00:48:34,680 --> 00:48:38,000 Speaker 4: which is most of them are terrible, but I'm on TikTok. 975 00:48:38,320 --> 00:48:42,160 Speaker 4: If you just put my first name, usually all come up. TikTok, Instagram, Twitter, 976 00:48:42,360 --> 00:48:46,640 Speaker 4: I know, I know, and Blue Sky and I'm not 977 00:48:46,680 --> 00:48:48,840 Speaker 4: the only one I don't really do is Facebook. 978 00:48:49,880 --> 00:48:50,719 Speaker 3: You're too cool for that. 979 00:48:51,360 --> 00:48:54,440 Speaker 4: Oh I have a subset. That's where the script is 980 00:48:54,440 --> 00:48:56,880 Speaker 4: bum subset. Now not too cool for Facebook. I'm just 981 00:48:56,880 --> 00:48:58,000 Speaker 4: too lazy for Facebook. 982 00:48:58,440 --> 00:49:00,879 Speaker 1: I mean, I mean, listen, if you're on these things, 983 00:49:00,880 --> 00:49:03,759 Speaker 1: you're not too cool for anything. That's the really cool 984 00:49:03,840 --> 00:49:06,560 Speaker 1: kids are not in any of these things. You can 985 00:49:06,640 --> 00:49:09,880 Speaker 1: find me at on Blue Sky, at cave. 986 00:49:10,000 --> 00:49:11,680 Speaker 3: Ka V E H M D. 987 00:49:12,520 --> 00:49:16,319 Speaker 1: And more importantly, you can listen to my podcast, The 988 00:49:16,360 --> 00:49:20,800 Speaker 1: House of Pod. It's a relatively fun, informal look at medicine. 989 00:49:20,840 --> 00:49:23,680 Speaker 3: We tried to make healthcare more relatable, you know. 990 00:49:23,800 --> 00:49:26,720 Speaker 1: Sometimes we'll take an aim at medical quackery or griffs 991 00:49:26,719 --> 00:49:29,000 Speaker 1: and that sort of thing. I think your listeners will 992 00:49:29,040 --> 00:49:34,000 Speaker 1: like it. Our guests range from doctors like Peter Hotez 993 00:49:34,200 --> 00:49:39,160 Speaker 1: or Argavon here to musicians like Portugal the Man, or 994 00:49:39,760 --> 00:49:42,440 Speaker 1: a lot of the Cool Zone family that you all 995 00:49:42,480 --> 00:49:46,600 Speaker 1: know and love, Prop and Robert and hopefully me as soon. 996 00:49:46,800 --> 00:49:49,520 Speaker 1: So find it anywhere you get your podcasts. 997 00:49:49,520 --> 00:49:50,160 Speaker 3: The House of Pod. 998 00:49:50,280 --> 00:49:53,279 Speaker 2: Yeah, and you can find all of that. We've talked 999 00:49:53,280 --> 00:49:56,920 Speaker 2: about like a staggering number of the other shows that 1000 00:49:56,960 --> 00:49:59,840 Speaker 2: we do in this one, but yeah you can. You 1001 00:49:59,840 --> 00:50:04,640 Speaker 2: can find our other shows where there are podcasts, And yeah, 1002 00:50:04,719 --> 00:50:07,680 Speaker 2: thank you God, I'm so bad at plugging these things. 1003 00:50:07,880 --> 00:50:10,239 Speaker 2: You think it's my living but now can't do it, 1004 00:50:10,280 --> 00:50:14,560 Speaker 2: so you're out of ten. Absolute failure. But yeah, thank 1005 00:50:14,600 --> 00:50:18,040 Speaker 2: you to both for coming on. And I hope you 1006 00:50:18,080 --> 00:50:22,680 Speaker 2: get your grant arka pod because that, like Jesus Christ. 1007 00:50:23,960 --> 00:50:26,360 Speaker 4: Thank you. Well. If I if I don't get my 1008 00:50:26,520 --> 00:50:28,880 Speaker 4: funding renewed this summer, I will, I will let you know. 1009 00:50:28,920 --> 00:50:30,000 Speaker 4: I mean we can talk about it. 1010 00:50:30,200 --> 00:50:36,600 Speaker 2: Yeah, yeah, I'm dot Yeah, this is this is big. 1011 00:50:36,600 --> 00:50:41,960 Speaker 2: Could happen here? Go go harass your legislatures, your local 1012 00:50:42,400 --> 00:50:47,359 Speaker 2: administrators for universities, your local police department. I make sure 1013 00:50:47,400 --> 00:50:52,600 Speaker 2: they do not bad stuff and do good things. It 1014 00:50:52,719 --> 00:50:55,080 Speaker 2: could happen here is a production of cool Zone Media. 1015 00:50:55,239 --> 00:50:58,320 Speaker 4: For more podcasts from cool Zone Media, visit our website 1016 00:50:58,400 --> 00:51:00,960 Speaker 4: pool Zonemedia dot com, or check us out on the 1017 00:51:00,960 --> 00:51:05,040 Speaker 4: iHeartRadio app, Apple Podcasts, or wherever you listen to podcasts. 1018 00:51:05,360 --> 00:51:07,279 Speaker 4: You can now find sources for it could Happen here 1019 00:51:07,320 --> 00:51:10,280 Speaker 4: listed directly in episode descriptions. Thanks for listening,