Relatively Prime Seminar: Funding의 전체 녹취록

전사 🔗

WEBVTT 00:00:00.001 --> 00:00:06.720 SH: Hello everyone, it is your host Sam Hansen and I am back with a new series in 00:00:06.720 --> 00:00:10.720 Relatively Prime that we are going to be calling seminars and it's going to be 00:00:10.720 --> 00:00:14.920 going out into the Relatively Prime feed off and on and it's going to be 00:00:14.920 --> 00:00:19.320 tackling the big questions about mathematics, so not from mathematics. 00:00:19.320 --> 00:00:23.880 We're not going to be digging deep into specific mathematical concepts here, but 00:00:23.880 --> 00:00:29.280 we're going to be doing more of a meta conversation about what goes on in 00:00:29.280 --> 00:00:34.640 mathematics and our first conversation is going to be about funding in 00:00:34.640 --> 00:00:38.960 mathematics and if you find that you have a question that you want to hear a 00:00:38.960 --> 00:00:45.360 seminar about please just email seminar@acmescience.com that's seminar at A C M E 00:00:45.360 --> 00:00:51.040 science.com and it will be up for a potential seminar in the future. So 00:00:51.040 --> 00:00:56.240 without further ado to join me and discuss funding in mathematics I have 00:00:56.240 --> 00:01:01.360 Carrie Diaz-Eaton, a mathematician and the associate professor of digital and 00:01:01.360 --> 00:01:05.320 computational studies at Bates College as well as the executive director of the 00:01:05.320 --> 00:01:10.080 Rios Institute, Drew Lewis, a mathematician and independent consultant and Jude 00:01:10.080 --> 00:01:14.400 Higdon, the chief operation officers of the Institute for Quantitative Study of 00:01:14.400 --> 00:01:18.920 Inclusion, Diversity and Equity or QSide. Hello everyone, thank you so much for 00:01:18.920 --> 00:01:23.800 joining me. 00:01:18.920 --> 00:01:23.800 CDZ: Hello, thanks for having us. 00:01:18.920 --> 00:01:23.800 JH: Good to be here. 00:01:18.920 --> 00:01:23.800 SH: And so first off let's 00:01:23.800 --> 00:01:31.000 talk just about where funding for math has traditionally come from and I can 00:01:31.000 --> 00:01:36.520 give a short little rundown about 64% of the funding in math comes from the NSF, 00:01:36.520 --> 00:01:42.720 18% comes from the Department of Defense and these are the federal funders, not 00:01:42.720 --> 00:01:48.120 including the private funders, and the reason 18% is from DOD is that that is 00:01:48.120 --> 00:01:53.680 where the NSA or national security agency's money sits and 12% is from HHS 00:01:53.680 --> 00:02:00.000 which is where the NIH money sits. So has anyone here you know dealt with 00:02:00.000 --> 00:02:04.640 getting federal funding? What was it like? 00:02:00.000 --> 00:02:04.640 CDZ: I guess I can talk a little bit 00:02:04.640 --> 00:02:10.760 about the process. I'll start. There are many divisions within National 00:02:10.760 --> 00:02:16.920 Science Foundation that give federal funding for mathematics so one of them 00:02:16.920 --> 00:02:22.640 that I think folks are most familiar with is the DMS, Division of Mathematical 00:02:22.640 --> 00:02:29.160 Sciences, but I don't actually usually get funding from them at all. So in my 00:02:29.160 --> 00:02:32.920 world as a mathematician I work very interdisciplinary, I do a lot of education 00:02:32.920 --> 00:02:39.320 research, I also do some in math biology so I have been funded by programs in the 00:02:39.320 --> 00:02:44.360 education side of the house and some programs that are joint between 00:02:44.360 --> 00:02:50.680 education and biology. So each of those programs has like a flavor I think you 00:02:50.680 --> 00:02:55.080 know like you try to figure out you know what what are you doing? What kind of 00:02:55.080 --> 00:02:59.720 project do you have in mind? Is it going to be something that is focused on a 00:02:59.720 --> 00:03:04.880 particular research area? Is it going to be about bringing new trainees into your 00:03:04.880 --> 00:03:08.760 lab? Is it going to be about something you're doing for your institutional to 00:03:08.760 --> 00:03:12.720 create, institution to create capacity for something more? There are like 00:03:12.720 --> 00:03:17.200 all sorts of different ways that you can get or reasons why you might look to get 00:03:17.200 --> 00:03:22.720 funding for mathematics. My sort of experience of that is like sometimes 00:03:22.720 --> 00:03:27.440 putting in proposals that get shot down and then eventually getting proposals in 00:03:27.440 --> 00:03:31.520 after coming back to the drawing board and revising them and listening to feedback 00:03:31.520 --> 00:03:36.000 and getting funded, but it can be a very long process. It's a very lengthy, very 00:03:36.000 --> 00:03:41.720 intensive process. There are way more grants than can possibly get funded. It's 00:03:41.720 --> 00:03:45.760 very competitive. I've also served on the other side of things reviewing 00:03:45.760 --> 00:03:52.280 proposals and many proposals are great and we can't certainly fund them all and 00:03:52.280 --> 00:03:59.720 so it's overall a very difficult, rigorous, intensive project that gets 00:03:59.720 --> 00:04:07.560 measured all the way down to your margin size and point size and with some 00:04:07.560 --> 00:04:12.160 percentage chance of getting funded. But when it does it really can open the 00:04:12.160 --> 00:04:17.560 doors not just for mathematicians and for innovation but also for students and 00:04:17.560 --> 00:04:21.840 trainees that are also employed on projects as well. 00:04:17.560 --> 00:04:21.840 JH: I'm happy to jump in 00:04:21.840 --> 00:04:26.440 and talk about my experience there. I've been part of, similar to 00:04:26.440 --> 00:04:30.640 Carrie, I've been part of more application processes than funded 00:04:30.640 --> 00:04:34.960 processes. I think that's just sort of how it goes. Again, not being a 00:04:34.960 --> 00:04:40.720 mathematician myself, I sort of rep mathematicians. The role that I 00:04:40.720 --> 00:04:46.040 generally play in the proposal

Load full transcript

process is sort of narrative story building and 00:04:46.040 --> 00:04:53.560 trying to think about the why of the questions around this. My experience 00:04:53.560 --> 00:04:58.520 of federally funded grants as one of the, at least historically, we'll 00:04:58.520 --> 00:05:04.840 see where that goes, is that Federal grants particularly are incredibly 00:05:04.840 --> 00:05:10.160 onerous in terms of the strictures required. The hurdles you have to 00:05:10.160 --> 00:05:17.120 jump through both organizationally and as coming from a nonprofit, a 501c3, 00:05:17.120 --> 00:05:21.320 not from an academic institution that has that sort of baked into the sauce 00:05:21.320 --> 00:05:26.040 that's particularly onerous for my organization to sort of overcome those 00:05:26.040 --> 00:05:31.560 hurdles. So we have, and especially in the current political climate, largely 00:05:31.560 --> 00:05:36.440 walked away from even seeking federal grants. I've been part of several 00:05:36.440 --> 00:05:42.200 successful NSF grants, one successful NIH grants and more proposals than I can 00:05:42.200 --> 00:05:47.920 probably count or remember at this point. But they are, in my experience, 00:05:47.920 --> 00:05:52.760 federally funded grants are from federal institutions like the NSF, the NIH, 00:05:52.760 --> 00:05:57.280 the Department of Education, the Department of Defense. We don't tend to 00:05:57.280 --> 00:06:01.240 apply through the Department of Defense. I've never been part of that process. 00:06:01.240 --> 00:06:06.560 But it is, it's just a tough process, right? It's really hard to check all 00:06:06.560 --> 00:06:11.280 the boxes and to get everything in the exact right ways. There is a lot of 00:06:11.280 --> 00:06:15.960 bureaucratic structure to it. The payoff can be quite good, right? 00:06:15.960 --> 00:06:19.920 Because if you are successful, the numbers, you know, the amount of funding 00:06:19.920 --> 00:06:25.000 available there is quite good. And historically, it has also been incredibly 00:06:25.000 --> 00:06:30.880 stable once you're funded. I think the gravity, the sort of physics of that 00:06:30.880 --> 00:06:34.680 world are changing pretty quickly right now in ways that I think folks did not 00:06:34.680 --> 00:06:38.840 think they could be. But that's been sort of part of my experience with the 00:06:38.840 --> 00:06:43.720 funding landscape at that level. 00:06:38.840 --> 00:06:43.720 SH: Drew, is it possible for you to talk at all about 00:06:43.720 --> 00:06:47.880 sort of like what the impact of these grants means? Like what are some of the 00:06:47.880 --> 00:06:52.320 things that are actually happening when mathematicians are getting funding? 00:06:52.320 --> 00:06:56.920 CDZ: And I'll tell Drew to also talk about the institutes because I feel like that's a 00:06:56.920 --> 00:07:02.640 different kind of beast. Like we're getting federal funding by proxy, right? 00:07:02.640 --> 00:07:10.000 DL: Yeah, so the NSF funds all kinds of different things in math. So one thing 00:07:10.000 --> 00:07:13.400 that most mathematicians are maybe most familiar with there is the standard 00:07:13.400 --> 00:07:17.600 grants through DMS, the Division of Mathematical Sciences, which will 00:07:17.600 --> 00:07:22.800 directly fund mathematics research. So salary support and travel support for 00:07:22.800 --> 00:07:27.880 collaborations, right? For mathematicians to do math research, proving theorems, 00:07:27.880 --> 00:07:32.760 collaborating with others. Another big thing they fund is conference grants, 00:07:32.760 --> 00:07:37.440 right? This is across divisions and directorates, but they will fund directly 00:07:37.440 --> 00:07:43.040 conferences around different topics. So for instance, the Southern Regional 00:07:43.040 --> 00:07:46.760 Algebra Conference that helped organize one year, we got a DMS conference grant, 00:07:46.760 --> 00:07:52.400 helped support that and pay for particularly early career faculty to be 00:07:52.400 --> 00:07:59.080 able to attend the conference. Yeah, to Carrie's point, one of the big things 00:07:59.080 --> 00:08:03.520 that DMS funds is the, let me see if I can get the acronym right, is the 00:08:03.520 --> 00:08:08.640 Mathematical Sciences Infrastructure Program or something similar, which funds 00:08:08.640 --> 00:08:14.480 these big math institutes. So IMSI is one of them, right? And then there's AIM in 00:08:14.480 --> 00:08:21.400 Pasadena and ICERM at Brown University. And I think they also fund IAS at 00:08:21.400 --> 00:08:27.640 Princeton and one more, no, two more. 00:08:21.400 --> 00:08:27.640 CDZ: Ipam UCLA. 00:08:21.400 --> 00:08:27.640 DL: Yeah, and then the one in 00:08:27.640 --> 00:08:34.400 Minnesota, Minneapolis. 00:08:27.640 --> 00:08:34.400 JH: No, they don't fund that anymore. 00:08:27.640 --> 00:08:34.400 CDZ: SL Math is the one you're missing, I think. 00:08:34.400 --> 00:08:39.840 DL: There we go. 00:08:34.400 --> 00:08:39.840 SH: Yes, SL Math is the other main one, but they do still partially fund 00:08:39.840 --> 00:08:44.920 the Minnesota one. It's just not one of the big six Mathematical Sciences 00:08:44.920 --> 00:08:50.480 Research Institutes. Not to be confused with the Mathematical Science Research 00:08:50.480 --> 00:08:56.520 Institute, which is now SL Math. 00:08:50.480 --> 00:08:56.520 DL: Yeah, so these institutes are great because 00:08:56.520 --> 00:09:00.480 they host, in addition to shorter conferences and things, they also have 00:09:00.480 --> 00:09:06.040 longer programs and collaborations. So for instance, all three of us were 00:09:06.040 --> 00:09:10.760 part of one of those at IMSI a few years ago, where we all got to go to IMSI for a 00:09:10.760 --> 00:09:15.760 month and collaborate together in person. But they also do semester long or even 00:09:15.760 --> 00:09:20.000 year-long kind of collaborative programs where folks who are on sabbaticals can 00:09:20.000 --> 00:09:24.880 come and

really intensively work on these projects for an extended period of time. 00:09:24.880 --> 00:09:29.000 And this serves as a great kind of, I want to say incubator. That's not quite 00:09:29.000 --> 00:09:32.760 the right word, but maybe catalyst is the right word to really make significant 00:09:32.760 --> 00:09:36.600 progress on these hard problems and provide that time and space for people 00:09:36.600 --> 00:09:41.720 to think really deeply about these kinds of things. 00:09:36.600 --> 00:09:41.720 SH: And Jude, you mentioned Q-side, 00:09:41.720 --> 00:09:46.840 probably moving a little bit away from from federal funding right now. So could 00:09:46.840 --> 00:09:51.240 you talk a little bit about what the other options are? Because there are 00:09:51.240 --> 00:09:56.840 private funders. The Simons is the big one that pops into my head, but I mean 00:09:56.840 --> 00:10:01.080 Kavli and some of the others also do provide funding. So what's sort of 00:10:01.080 --> 00:10:07.680 different when you exit the federal and go to the private funders? 00:10:07.680 --> 00:10:11.960 JH: Well, there's also a missing link in there, which is state funding. And there's a 00:10:11.960 --> 00:10:16.160 huge amount of opportunity there. And I think sometimes folks forget that there 00:10:16.160 --> 00:10:22.200 are state and local grants. And so we've actually been wrapped into a lot of work 00:10:22.200 --> 00:10:26.480 around state-level grants. We're doing a ton of proposal work with the 00:10:26.480 --> 00:10:30.960 collaborative in the state of California around the Racial Justice Act and 00:10:30.960 --> 00:10:34.440 around some of that work that's coming out of the state. And then we've also got 00:10:34.440 --> 00:10:38.760 a proposal in with the state of Pennsylvania. So that's something that I 00:10:38.760 --> 00:10:43.080 do think a lot of folks don't even think about, right, is the state-level 00:10:43.080 --> 00:10:47.200 grants and those hurdles that I mentioned earlier being so onerous are 00:10:47.200 --> 00:10:51.480 much lower in those spaces. So that's something to think about. You know, 00:10:51.480 --> 00:10:55.760 primarily where we have looked for funding is to private foundations 00:10:55.760 --> 00:11:00.640 historically. And I think for nonprofits, that tends to be the place that they tend 00:11:00.640 --> 00:11:04.920 to look for state grants and for foundation grants. And so yeah, you've 00:11:04.920 --> 00:11:09.920 got, I mean, there's a ton of them for the kind of work that we do at QSide, 00:11:09.920 --> 00:11:13.960 even some of the traditional large funding foundations aren't really 00:11:13.960 --> 00:11:19.600 appropriate. So the places we tend to look are to mission-aligned foundations, 00:11:19.600 --> 00:11:24.960 right? So the big ones that do work related to like criminal illegal 00:11:24.960 --> 00:11:29.400 system reform, like the Arnold Foundation or Arnold Ventures, we've been 00:11:29.400 --> 00:11:33.680 funded pretty significantly historically from the Walmart Foundation. We've had 00:11:33.680 --> 00:11:38.760 funding from the Bloomberg Foundation. And I would say the difference, in my 00:11:38.760 --> 00:11:44.400 experience, between those kinds of funding is that my experience is that the 00:11:44.400 --> 00:11:51.320 foundation grants tend to be a lot more relationship driven. Like I sort of was 00:11:51.320 --> 00:11:57.200 invited into the Walmart Foundation criminal justice reform network where I 00:11:57.200 --> 00:12:01.280 participated and sort of got brought in to do some consulting and QSide for 00:12:01.280 --> 00:12:06.480 smaller scale things for two years before that we were sort of considered 00:12:06.480 --> 00:12:10.720 ready to be eligible to sort of be actually an independently funded 00:12:10.720 --> 00:12:15.680 organization from the foundation. That's not everyone's experience, but I do 00:12:15.680 --> 00:12:20.000 think that it is very relationship driven and sort of understanding the 00:12:20.000 --> 00:12:25.280 portfolio of the foundation and their theory of change. Like they tend to 00:12:25.280 --> 00:12:30.040 have a kind of a philosophy around the kind of work that they want to see done. 00:12:30.040 --> 00:12:34.880 And that can be scientific in nature or it can be supported in our case by data 00:12:34.880 --> 00:12:40.400 science tools and techniques. But it's just a different mission, right? 00:12:40.400 --> 00:12:45.400 And it's a different way of thinking about funding, thinking about 00:12:45.400 --> 00:12:49.720 cultivating relationships around that in those spaces. So that's been my 00:12:49.720 --> 00:12:54.520 experience. And I know Carrie also has a lot of experience in the foundation space. 00:12:54.520 --> 00:12:57.040 So I'd love to hear if anything I said rings true with her. 00:12:57.040 --> 00:13:01.760 CDZ: Yeah, no, 100%. I think you kind of get engaged in a process. And instead of the 00:13:01.760 --> 00:13:04.520 whole time you being like, I'm putting in all this work and I'm not sure if it's 00:13:04.520 --> 00:13:10.400 going anywhere, that certainty increases as the relationship builds. So at some 00:13:10.400 --> 00:13:15.080 point you decide, hey, like, I think we should keep in each other's circles, but 00:13:15.080 --> 00:13:19.360 I don't think we're quite aligned at this moment. Or you just continue building 00:13:19.360 --> 00:13:23.080 that relationship and that funding and then you have a pretty good relationship 00:13:23.080 --> 00:13:28.560 and that can get leveraged long term. But there are some foundations that 00:13:28.560 --> 00:13:34.480 still operate in a more like NSF-y kind of way. Like there are some that do 00:13:34.480 --> 00:13:38.720 have just open calls and lots of proposals and panel reviews as well and 00:13:38.720 --> 00:13:43.720 are highly competitive. But I think the ones I have really actually very much 00:13:43.720 --> 00:13:47.400 enjoyed sort of making a

relationship with my program officer at the Hewlett 00:13:47.400 --> 00:13:53.200 Foundation. And they operate with a philosophy that's very different from 00:13:53.200 --> 00:13:59.200 accounting for federal funds, which the back end of how you get your money and 00:13:59.200 --> 00:14:03.800 how it's dispersed and accounted for is very specific with federal funding. 00:14:03.800 --> 00:14:10.520 And there are some movements within philanthropy that are more relational 00:14:10.520 --> 00:14:15.000 and trust based that say we will give you some money for general operating costs 00:14:15.000 --> 00:14:19.960 and we know that you're going to use this money the way you need to use it when 00:14:19.960 --> 00:14:26.600 the time is called. So from my perspective in this moment it helps me to 00:14:26.600 --> 00:14:31.880 be able to quickly pivot my organization's actions based on what's going 00:14:31.880 --> 00:14:36.760 on in the world in a way that might be very difficult under another funding 00:14:36.760 --> 00:14:40.680 source. 00:14:36.760 --> 00:14:40.680 SH: Well if any foundation program officers are listening and you think 00:14:40.680 --> 00:14:44.840 that it's mission aligned for you to help spread mathematical stories, I am 00:14:44.840 --> 00:14:50.120 always looking for money. So one thing I do want to talk a little bit about is 00:14:50.120 --> 00:14:54.520 I mean there's this perception of mathematics, specifically theoretical 00:14:54.520 --> 00:15:00.520 mathematics, that it is one of those areas that's really nice because all you 00:15:00.520 --> 00:15:05.320 need is a writing utensil and something to write on and probably some books to 00:15:05.320 --> 00:15:10.520 read. And while I'm enough of a mathematician to know that that is not 00:15:10.520 --> 00:15:15.000 true, it is fundamentally different than some of the physical 00:15:15.000 --> 00:15:18.440 sciences or things like that where you say you are in physics, you're in 00:15:18.440 --> 00:15:23.960 high energy physics, you need a collider and that is not something that 00:15:23.960 --> 00:15:29.880 you can do easily and math can be a little bit easier to do without 00:15:29.880 --> 00:15:34.920 all those extra things. So I was digging into how different 00:15:34.920 --> 00:15:38.840 areas are funded federally. I chose federally because it's just a lot easier 00:15:38.840 --> 00:15:43.640 to get the numbers than to look at foundations. And so as I said before, 00:15:43.640 --> 00:15:49.720 math gets 64% from the National Science Foundation whereas across all of the 00:15:49.720 --> 00:15:54.280 science and engineering, medical, technology, the STEM fields, the average is 00:15:54.280 --> 00:15:58.520 27% from the NSF. So you can already see that math is getting 00:15:58.520 --> 00:16:02.760 more from the NSF than a lot of other fields. There are social sciences and 00:16:02.760 --> 00:16:08.280 psychology get about 68%. Biology but only basic biological research, so not 00:16:08.280 --> 00:16:11.000 applied biological research, so we're not including say 00:16:11.000 --> 00:16:16.360 medical fields in this, get 69% and computer science, again just basic 00:16:16.360 --> 00:16:20.440 computer science, so theoretical computer science gets 83%, but that's also a 00:16:20.440 --> 00:16:24.120 very small amount of the computer science research that happens. 00:16:24.120 --> 00:16:28.840 And then looking at the total like dollar amounts, and I found this 00:16:28.840 --> 00:16:32.680 wonderful breakdown that the NSF published and this is across the 00:16:32.680 --> 00:16:35.880 across the whole federal government. We give about, 00:16:35.880 --> 00:16:41.400 at least last year, we get there was about 45 billion dollars worth of funding. 00:16:41.400 --> 00:16:44.600 So we're not we're not talking about a small amount of funding, but 00:16:44.600 --> 00:16:48.040 in comparison with the federal budget, we're talking about 00:16:48.040 --> 00:16:51.880 a very small amount of money because that's in the 00:16:51.880 --> 00:16:55.000 trillions of dollars, so we're talking orders of magnitude. 00:16:55.000 --> 00:16:58.200 And there computer science got 2.3 billion, 00:16:58.200 --> 00:17:04.360 geosciences got 3.4 billion, life sciences got 19 billion, physics got 00:17:04.360 --> 00:17:10.600 9.5 billion, psychology 2.29 billion, engineering 3.8 00:17:10.600 --> 00:17:16.760 billion, social sciences only 766 million, and math and stats 608 million 00:17:16.760 --> 00:17:20.200 dollars. So there is another thing for other, 00:17:20.200 --> 00:17:23.560 which was 3.7 billion, but these are going to be smaller fields, which will get 00:17:23.560 --> 00:17:30.200 less money than math. So math is of all of the large fields, 00:17:30.200 --> 00:17:33.640 the least amount of money. Is anyone surprised? 00:17:33.640 --> 00:17:38.920 DL:No 00:17:33.640 --> 00:17:38.920 CDZ: No, I mean, and I think I think part of the reason is exactly what you said. 00:17:38.920 --> 00:17:43.080 Historically, hasn't required a lot of large equipment and costs and purchases. 00:17:43.080 --> 00:17:48.040 And so the vast majority of of math funding is about like 00:17:48.040 --> 00:17:52.120 conferences and collaborations and travel, and 00:17:52.120 --> 00:17:56.040 and that's why the math institutes are this overly large disproportionate 00:17:56.040 --> 00:18:00.120 amount of money that sort of acts as these mini hubs for a lot of that. 00:18:00.120 --> 00:18:03.880 And otherwise, equipment costs have been traditionally a lot lower. 00:18:03.880 --> 00:18:08.280 So I'm not surprised, but I think it is for the audience, it may be an 00:18:08.280 --> 00:18:12.200 interesting observation that we are maybe the lowest funding, 00:18:12.200 --> 00:18:15.720 but we also have a high dependence on federal funds. 00:18:15.720 --> 00:18:20.120 I think with the exception of folks who are actually, or 00:18:20.120 --> 00:18:23.800 mathematicians, getting

funded under biology like me, 00:18:23.800 --> 00:18:27.800 or something like that, a lot of this is really 00:18:27.800 --> 00:18:32.680 made possible just with federal monies, and there are fewer foundations out 00:18:32.680 --> 00:18:36.360 there and fewer different kinds of federal agencies that 00:18:36.360 --> 00:18:40.040 are supporting this work. Unlike, biology might also be supported 00:18:40.040 --> 00:18:44.280 by EPA or something. The landscape is shifting across all 00:18:44.280 --> 00:18:51.160 of those granting agencies, which is I think what we're getting to. 00:18:51.160 --> 00:18:55.800 JH: I think the only thing I would add is that 00:18:55.800 --> 00:19:01.000 one of the reasons why we as a mission-driven and applied, 00:19:01.000 --> 00:19:04.920 we're really a data science nonprofit, right? With the 00:19:04.920 --> 00:19:08.440 like the shorthand for QSide is data science plus social justice, right? 00:19:08.440 --> 00:19:12.680 That's like social justice problems examined and tried 00:19:12.680 --> 00:19:17.400 to solve social justice challenges through innovative uses and partnerships 00:19:17.400 --> 00:19:21.720 of using data science in that space. We have never found a home 00:19:21.720 --> 00:19:26.840 anywhere in the federal ecosystem for anything related to that, 00:19:26.840 --> 00:19:30.840 but my husband and I who co-founded QSide are, we are both scientists at our core. 00:19:30.840 --> 00:19:34.680 I'm a psychologist, my doctorate is in psychology, his is in applied math. 00:19:34.680 --> 00:19:38.920 Even in the applied math field, the true mathematicians in the group, 00:19:38.920 --> 00:19:43.800 correct me if I'm wrong, it can be even for sort of like more traditional 00:19:43.800 --> 00:19:47.640 applied math work. It's a heavier hill to climb in some 00:19:47.640 --> 00:19:54.280 ways in the federal ecosystem. Hyper-applied mission-driven work 00:19:54.280 --> 00:19:58.440 of using tools and using innovative tools or developing 00:19:58.440 --> 00:20:02.840 innovative mathematical tools that can sort of be used in social science 00:20:02.840 --> 00:20:07.400 contexts. We have yet to find a home or a kind of 00:20:07.400 --> 00:20:11.480 sympathetic landing spot for that within the federal ecosystem. 00:20:11.480 --> 00:20:15.080 We tried and sometimes we get subsumed in 00:20:15.080 --> 00:20:20.040 other types of grants like social science grants or something as 00:20:20.040 --> 00:20:24.520 kind of the resident quat nerds and to kind of bolster that, 00:20:24.520 --> 00:20:28.680 but it hasn't, we haven't really found a spot for this work 00:20:28.680 --> 00:20:32.520 within that landscape. 00:20:28.680 --> 00:20:32.520 SH: One thing that really strikes me 00:20:32.520 --> 00:20:37.800 when I'm thinking about all of this is that 00:20:37.800 --> 00:20:43.320 math, no and I don't want to get on, I don't want to get all soap boaxy, I also 00:20:43.320 --> 00:20:46.920 don't want to say things that are 00:20:46.920 --> 00:20:53.720 truthy and not truthful, but it really isn't that big of a stretch to say 00:20:53.720 --> 00:20:58.280 that mathematics is the thing that underpins most of this 00:20:58.280 --> 00:21:01.000 science at some level. Sometimes you have to dig 00:21:01.000 --> 00:21:05.240 really, really far down to get to it, but at some point there needs to be 00:21:05.240 --> 00:21:09.000 some math involved in most of this as long as there's any 00:21:09.000 --> 00:21:17.240 you know quantifiable research going on. And yet I've always felt a certain 00:21:17.240 --> 00:21:22.040 idea that a lot of people have that math is just sort of done, 00:21:22.040 --> 00:21:26.520 that it's this thing that exists and we have the math. 00:21:26.520 --> 00:21:31.000 And I worry about that some when we're thinking about 00:21:31.000 --> 00:21:37.160 funding in particular because as our university systems continue to move 00:21:37.160 --> 00:21:40.440 more and more in the corporatized direction that they 00:21:40.440 --> 00:21:45.000 have continually done under neoliberal leadership, 00:21:45.000 --> 00:21:51.080 I worry that without the funding with you know just being viewed as this 00:21:51.080 --> 00:21:56.760 thing that's sort of complete that math will atrophy a little bit. 00:21:56.760 --> 00:22:00.280 CDZ: So let me let me put a slightly different thing on it. 00:22:00.280 --> 00:22:04.040 I mean I think that's certainly something the students are taught in the 00:22:04.040 --> 00:22:07.800 classroom is like here are the rules apply the rules like math 00:22:07.800 --> 00:22:11.000 this has always been for 200 years in calculus. I mean I 00:22:11.000 --> 00:22:14.360 you know that is certainly a thing where we're teaching students actively 00:22:14.360 --> 00:22:17.240 whether or not we should do that is maybe a different podcast. 00:22:17.240 --> 00:22:24.920 But I think one of the things that I have been 00:22:24.920 --> 00:22:29.400 I wouldn't say struggling with but reprocessing I mean I think is the word 00:22:29.400 --> 00:22:34.120 to use is that traditionally DMS funding, mathematical funding 00:22:34.120 --> 00:22:39.400 direct from like the federal agencies has focused on 00:22:39.400 --> 00:22:44.280 mathematical innovation and not application. And when you go to 00:22:44.280 --> 00:22:48.200 application then you seek you know funding from the other divisions from 00:22:48.200 --> 00:22:53.000 the other places. While this is great for mathematical 00:22:53.000 --> 00:23:00.680 development I think it is part of the how we have 00:23:00.680 --> 00:23:05.000 not cultivated the relationship we need to have with our ultimate program 00:23:05.000 --> 00:23:11.960 officers which are the public. And I think that this is a huge problem 00:23:11.960 --> 00:23:16.520 how much are mathematicians the folks who are spotlighted 00:23:16.520 --> 00:23:20.600 when breakthroughs are made in all of these other areas right. 00:23:20.600 -->

00:23:24.360 You know if you're not supporting the applied work the work that's in the 00:23:24.360 --> 00:23:29.080 community because it's not innovation in 00:23:29.080 --> 00:23:35.400 in a traditional sense and is more about synthesis and border crossing 00:23:35.400 --> 00:23:39.400 from from the ivory tower to the public and to the community 00:23:39.400 --> 00:23:42.840 all of a sudden now you've missed this whole opportunity 00:23:42.840 --> 00:23:49.720 to tell people or engage people like with the joy of and the the excitement 00:23:49.720 --> 00:23:53.320 and the innovations and the insights and the power that you get from these 00:23:53.320 --> 00:23:57.160 techniques right. You've lost the right to claim it 00:23:57.160 --> 00:24:01.000 now you know that you're relevant and important to society. 00:24:01.000 --> 00:24:06.920 So I want to really appreciate how DMS funding has been used to really make 00:24:06.920 --> 00:24:11.240 sure that we are ahead on the innovation side that we're contributing to like 00:24:11.240 --> 00:24:14.600 thinking about like new complex problems before there are 00:24:14.600 --> 00:24:18.040 problem right. Just like the underpinnings of 00:24:18.040 --> 00:24:23.480 theory mathematical theory but I want to say at the same time I 00:24:23.480 --> 00:24:29.640 think we have created our own problem with who we're seen as and 00:24:29.640 --> 00:24:33.960 who we're seen for by the rest of the public. 00:24:29.640 --> 00:24:33.960 SH: Yes 00:24:33.960 --> 00:24:38.200 100 percent I mean that's that is part of why I do the work I do right like I 00:24:38.200 --> 00:24:42.440 want to tell these mathematical stories. It's one of my favorite things to do 00:24:42.440 --> 00:24:46.520 even though I do prefer telling theoretical stories that applied stories 00:24:46.520 --> 00:24:50.120 but that's just because that's the area of math that I always 00:24:50.120 --> 00:24:53.720 gravitated towards myself. The applied stories are tend to be much more 00:24:53.720 --> 00:24:57.640 enjoyable for everyone listening though. 00:24:57.640 --> 00:25:01.880 So now now as as Jude previously indicated let's 00:25:01.880 --> 00:25:05.960 let's move to today. Well actually I'm going to send us back to about October 00:25:05.960 --> 00:25:09.400 2024. Like I mean there's a long history that we 00:25:09.400 --> 00:25:15.240 could be talking about around different political parties views on 00:25:15.240 --> 00:25:18.920 scientific funding but we're not going to dig all the way into that because 00:25:18.920 --> 00:25:23.960 this podcast would be 45 hours long. So instead Drew 00:25:23.960 --> 00:25:30.280 can you tell me about the October 2024 commerce report from Senator 00:25:30.280 --> 00:25:37.000 Cruz? 00:25:30.280 --> 00:25:37.000 DL: Yeah so in October the the Senate 00:25:37.000 --> 00:25:41.640 Commerce Committee headed by Ted Cruz released a report. 00:25:41.640 --> 00:25:44.840 I forget the the title off the top of my head but 00:25:44.840 --> 00:25:49.080 essentially they went through the portfolio of NSF 00:25:49.080 --> 00:25:54.440 funding looking for keywords in a list. So any grant that used words like 00:25:54.440 --> 00:25:58.520 diversity, equity, inclusion, belonging, 00:25:58.520 --> 00:26:03.800 identity characteristics like black or latine and 00:26:03.800 --> 00:26:07.080 cooked up this database of all these grants that use these words. They did 00:26:07.080 --> 00:26:10.520 into some manual checking. They thought that black holes were 00:26:10.520 --> 00:26:14.200 important right so they took those off of the list right but 00:26:14.200 --> 00:26:16.520 you know if you're talking about supporting black people then that went 00:26:16.520 --> 00:26:20.040 on their list. And so they released this database of 00:26:20.040 --> 00:26:23.720 grants to target. I guess I should say they only very 00:26:23.720 --> 00:26:28.120 recently released a full database. They put out a report in October 00:26:28.120 --> 00:26:31.960 and where they kind of cherry picked some particular grants on there 00:26:31.960 --> 00:26:35.000 and lambasted them in their usual kind of 00:26:35.000 --> 00:26:39.160 rhetoric about how terrible it is to actually include and support 00:26:39.160 --> 00:26:43.640 people of various identities. 00:26:39.160 --> 00:26:43.640 SH: Yes so and that that report 00:26:43.640 --> 00:26:50.520 highlighted about two billion dollars of quote unquote woke NSF grants 00:26:50.520 --> 00:26:53.560 and just just know whenever we're talking about 00:26:53.560 --> 00:26:57.560 woke today there's likely scare quotes around it 00:26:57.560 --> 00:27:02.200 because it is very very scary. And so that's 00:27:02.200 --> 00:27:06.840 I mean two billion that's about a quarter a little bit under a quarter of 00:27:06.840 --> 00:27:13.640 of the NSF's annual outlay. So that happens in October and then 00:27:13.640 --> 00:27:18.600 there's an election in November and in late January 00:27:18.600 --> 00:27:25.160 our current president jumps into office and on the first day does any well 00:27:25.160 --> 00:27:28.840 first first day and then some days after is anyone want to 00:27:28.840 --> 00:27:33.800 you know give a colorful description of some of the executive orders that came 00:27:33.800 --> 00:27:38.040 through. 00:27:33.800 --> 00:27:38.040 CDZ: Sorry I was just flipping to another 00:27:38.040 --> 00:27:41.640 page I had with this like gorgeous timeline I wish you could see 00:27:41.640 --> 00:27:47.880 like how beautiful it is. So the it had this timeline of events 00:27:47.880 --> 00:27:52.360 and January 20th to 24th executive orders targeting federal spending 00:27:52.360 --> 00:27:58.200 workforce DEI etc are issued and and so I it's nice because it has a whole 00:27:58.200 --> 00:28:03.000 layout of all well nice tragic whichever the 00:28:03.000 --> 00:28:10.840 correct word is to use and January 27th was the memo 00:28:10.840 --> 00:28:15.800

directing federal funding pauses. So there were kind of these waves 00:28:15.800 --> 00:28:19.080 either were the executive orders that were like you got to stop 00:28:19.080 --> 00:28:23.080 spending we're gonna we're gonna start cutting people and we're going to like 00:28:23.080 --> 00:28:28.200 do the Ted Cruz like like anti DEI on everything 00:28:28.200 --> 00:28:33.960 contractors spending on DEI etc and then separately from that but only 00:28:33.960 --> 00:28:37.800 put only a little bit later it we were they were going to 00:28:37.800 --> 00:28:42.120 operationalize all of this through these like reviews of every single grant 00:28:42.120 --> 00:28:46.520 they've given of every funding the federal funding agency etc 00:28:46.520 --> 00:28:50.200 and in order to do that they were saying don't spend any 00:28:50.200 --> 00:28:53.560 money at all and I think folks probably have heard 00:28:53.560 --> 00:28:57.320 you know a lot like USAID was like one of the 00:28:57.320 --> 00:29:01.240 agencies that got a lot of play in in our academic world the 00:29:01.240 --> 00:29:07.000 pauses of NSF and of NIH and all of these others 00:29:07.000 --> 00:29:10.120 then almost immediately there were legal challenges 00:29:10.120 --> 00:29:16.440 and within two days the memo was rescinded but at the same time 00:29:16.440 --> 00:29:23.480 that that memo was rescinded they were still freezing the funding 00:29:23.480 --> 00:29:26.840 so there was even more 00:29:23.480 --> 00:29:26.840 SH: And the press secretary 00:29:26.840 --> 00:29:31.080 literally said no we're still we're still freezing the funding like 00:29:31.080 --> 00:29:35.640 at a press conference 00:29:31.080 --> 00:29:35.640 CDZ: Exactly exactly and so they were like yeah we're not 00:29:35.640 --> 00:29:39.160 going to pay attention to this which you know so they were more judges being 00:29:39.160 --> 00:29:43.080 like no no you can't like you cannot freeze and and we're 00:29:43.080 --> 00:29:48.760 talking about folks who just you know different institutions and 00:29:48.760 --> 00:29:51.960 funding agencies also like interpreted these memos very very 00:29:51.960 --> 00:29:54.600 differently and had different ways of operating 00:29:54.600 --> 00:29:58.280 there was a variety of responses some were like business as usual 00:29:58.280 --> 00:30:01.640 let's play it out in the court some were like freaking out and they were like 00:30:01.640 --> 00:30:05.720 stop using all your grants and and some of those institutions had real on the 00:30:05.720 --> 00:30:08.840 ground impacts immediately like folks were 00:30:08.840 --> 00:30:12.600 fired folks were like you got you lost your job today because we don't 00:30:12.600 --> 00:30:16.120 we're getting reviewed we were on the Ted Cruz list or 00:30:16.120 --> 00:30:21.400 whatever and some grants for example DOE grants have been 00:30:21.400 --> 00:30:25.640 straight out canceled so let's say you had a grant that was supposed to last 00:30:25.640 --> 00:30:31.160 three more years too bad it's done like there have been ones like that 00:30:31.160 --> 00:30:35.320 NSF has been differently impacted so as far as I'm aware 00:30:35.320 --> 00:30:39.400 so far folks have not been able to renew grants 00:30:39.400 --> 00:30:44.920 and grants that were going to end have been denied the ability to ask for a no 00:30:44.920 --> 00:30:48.200 cost extension but grants that have been 00:30:48.200 --> 00:30:52.680 promised up to a particular point have not yet been canceled I'm saying yet 00:30:52.680 --> 00:30:56.680 then canceled because I feel like it was they were trying 00:30:56.680 --> 00:31:02.920 but yeah it has been kind of halted so this is kind of spanned 00:31:02.920 --> 00:31:06.680 everything and I think one of the difficult parts is 00:31:06.680 --> 00:31:10.120 the DEI attack was maybe one of the first waves 00:31:10.120 --> 00:31:14.040 and then there was the the freezing on grants and then there was the firing of 00:31:14.040 --> 00:31:18.120 staff and and now more staff firing and budget cut 00:31:18.120 --> 00:31:21.720 allotments so I worry a little bit that by 00:31:21.720 --> 00:31:25.960 focusing on the the funding and the freezes that were also like we forget to 00:31:25.960 --> 00:31:30.360 talk about the DEI part as well like is there a list of words that you're not 00:31:30.360 --> 00:31:32.840 allowed to say and also you know question the 00:31:32.840 --> 00:31:38.040 legality of that core because at least for NSF where math is 00:31:38.040 --> 00:31:41.320 highly where we've established math is highly dependent on 00:31:41.320 --> 00:31:46.920 for anybody who's reviewed it's two criteria intellectual merit and 00:31:46.920 --> 00:31:50.440 broadening participation that are legislated by congress 00:31:50.440 --> 00:31:54.600 so when you throw out DEI when you throw out 00:31:54.600 --> 00:31:58.920 specific actions that are meant to make sure that we 00:31:58.920 --> 00:32:03.800 are competitive because everyone who wants to have a STEM career can have a 00:32:03.800 --> 00:32:07.640 STEM career and that's done through DEI 00:32:07.640 --> 00:32:12.120 actions right if you have removed that ability then 00:32:12.120 --> 00:32:17.640 you're not actually you know executing the instructions of congress 00:32:17.640 --> 00:32:21.880 SH: Yeah that that is a really important and good point 00:32:21.880 --> 00:32:25.080 like this has been legislated broad broader impacts 00:32:25.080 --> 00:32:29.880 is in the actual law but the executive borders are 00:32:29.880 --> 00:32:33.320 apparently trying to limit how you how you do it and 00:32:33.320 --> 00:32:38.680 as people on blue sky because we're not going to talk about the hell site 00:32:38.680 --> 00:32:42.840 have been pointing out specifically as say Chanda Prescod-Weinstein like this 00:32:42.840 --> 00:32:49.640 is effectively a resegregation effort in in many ways trying to limit 00:32:49.640 --> 00:32:53.640

higher education and the other groups that need this sort of funding to 00:32:53.640 --> 00:32:58.280 include people who have historically had the power and privilege to take part 00:32:58.280 --> 00:33:01.640 in those groups and not trying to keep the door open 00:33:01.640 --> 00:33:04.920 I do want to talk a little bit about that list of words so 00:33:04.920 --> 00:33:08.760 the list of words that were being searched for was 00:33:08.760 --> 00:33:12.520 actually gathered and shared by Michael Harris who is a 00:33:12.520 --> 00:33:16.920 mathematician who has a newsletter called the silicon reckoner talking about 00:33:16.920 --> 00:33:21.000 mathematics and artificial intelligence and machine learning but also 00:33:21.000 --> 00:33:24.360 has been covering some of this topic as well 00:33:24.360 --> 00:33:29.080 and the other mathematicians here I I would love to hear from y'all 00:33:29.080 --> 00:33:33.960 what it what it means if mathematicians are not allowed to use 00:33:33.960 --> 00:33:40.600 words like inclusion inequalities some things like polarization are those 00:33:40.600 --> 00:33:44.440 words that might trigger math grants to be looked at 00:33:44.440 --> 00:33:48.200 weird but yet have nothing to do with quote unquote 00:33:48.200 --> 00:33:52.840 wokeness 00:33:48.200 --> 00:33:52.840 DL: I mean I think if you just do the the naive search through the grants 00:33:52.840 --> 00:33:56.440 you're gonna find a lot of math grants with those words but 00:33:56.440 --> 00:33:59.320 at some point I think it's a little bit of a distraction to think about that 00:33:59.320 --> 00:34:02.520 because we already saw with the Ted Cruz report right he went through black was 00:34:02.520 --> 00:34:06.280 one of the words in there right and specifically in this report he said oh 00:34:06.280 --> 00:34:09.800 if they're just talking about black holes that's okay so they want to support 00:34:09.800 --> 00:34:12.920 black holes they don't want to support black people so I think the same thing 00:34:12.920 --> 00:34:15.480 with the math grants they're gonna look and if you're talking about inclusions 00:34:15.480 --> 00:34:18.440 of sets right they're gonna say okay this is fine 00:34:18.440 --> 00:34:22.600 if you're talking about including students from underrepresented groups in 00:34:22.600 --> 00:34:28.680 your work that's gonna get flagged 00:34:22.600 --> 00:34:28.680 SH: So I uh I hope that you are right I think 00:34:28.680 --> 00:34:34.920 that you are right right now but something that I worry about here is 00:34:34.920 --> 00:34:39.240 this push that seems to be coming from our unelected 00:34:39.240 --> 00:34:42.840 apartheid Clyde with the black hat and the 00:34:42.840 --> 00:34:49.960 fun adult boy jumps Elon Musk and of this this push to 00:34:49.960 --> 00:34:55.240 fire everyone and I think start using LLMs for everything so large language 00:34:55.240 --> 00:34:59.240 models for pretty much everything and I I I do think that as long as there's 00:34:59.240 --> 00:35:03.000 humans looking at these things we don't have much to worry about what 00:35:03.000 --> 00:35:06.520 happens if there aren't humans to looking to look at them because 00:35:06.520 --> 00:35:11.720 they've already fired 168 people from NSF 00:35:12.200 --> 00:35:20.200 so that was a what about 20% of the workforce and there's talk of cutting 00:35:20.200 --> 00:35:26.680 hundreds more people of like up to a 50 to 60 percent total cut of of workforce 00:35:26.680 --> 00:35:32.360 staff not to mention the fact that the house budget proposal probably will 00:35:32.360 --> 00:35:37.560 cut 50% to 75% percent of the funding that NSF gives out in 00:35:37.560 --> 00:35:41.480 grants so what if humans no longer look at them 00:35:41.480 --> 00:35:45.000 JH: Yeah so there's well there's a really quick 00:35:45.000 --> 00:35:48.600 anecdote that I'll share that speaks to exactly what you're saying 00:35:48.600 --> 00:35:52.120 Sam from the first Trump administration where 00:35:52.120 --> 00:35:57.320 they went through and they they preferred the word homosexual to gay 00:35:57.320 --> 00:36:00.440 and so they did these massive final replacements this is something that a lot 00:36:00.440 --> 00:36:03.400 of people in the queer community remember but I think folks who are not in the 00:36:03.400 --> 00:36:07.240 queer community may not remember and so they did this like 00:36:07.240 --> 00:36:10.840 in this mass way like across all of these documents 00:36:10.840 --> 00:36:15.800 and there were people whose names were gay who were then renamed homosexual 00:36:15.800 --> 00:36:24.280 in the process and I think that we even even with the human cognitive 00:36:24.280 --> 00:36:28.520 component to it I think that's just illustrative of the 00:36:28.520 --> 00:36:32.680 problem so I I want to quibble with one thing you said that 00:36:32.680 --> 00:36:36.840 even if it is the former and not the latter it is still deeply problematic and 00:36:36.840 --> 00:36:41.160 troubling I don't think like we're safe but even if we accept that 00:36:41.160 --> 00:36:45.320 one is okay and like more okay once in a while is more okay than the other you 00:36:45.320 --> 00:36:50.120 know like we'll put it there I think that as someone who 00:36:50.120 --> 00:36:55.720 grew up on Don't Ask Don't Tell and grew up under the regime of it is 00:36:55.720 --> 00:37:00.440 not being a thing but it is being known as that 00:37:00.440 --> 00:37:04.120 thing and using those words and having the taste of those words in your mouth 00:37:04.120 --> 00:37:10.280 linguistics matter language matters and the outlying of words like diversity 00:37:10.280 --> 00:37:14.520 equity inclusion and belonging is inherently deeply problematic 00:37:14.520 --> 00:37:20.360 not just for the tactical kind of results of that but it is a problem 00:37:20.360 --> 00:37:25.720 right like we we have to resist that that impulse like it is a problem

00:37:25.720 --> 00:37:30.360 globally to have people telling us what we can say and what we can't 00:37:30.360 --> 00:37:35.640 in those kind of ways so I'll get now I'll get down off my soapbox and 00:37:35.640 --> 00:37:40.120 relinquish the floor 00:37:35.640 --> 00:37:40.120 SH: It's it's a good soapbox and it's one I'm glad that 00:37:40.120 --> 00:37:43.320 glad that you reminded me of because I was I've been thinking so much about the 00:37:43.320 --> 00:37:47.640 funding over the last couple days I forgot that on day one 00:37:47.640 --> 00:37:52.040 he signed an executive order that removed my gender from the 00:37:52.040 --> 00:37:56.280 the legal framework of the United States which I'm gonna tell you felt 00:37:56.280 --> 00:38:01.480 felt real good that was a that was a very very positive moment for me 00:38:01.480 --> 00:38:05.160 so I'd love to talk a little bit more about the importance of program 00:38:05.160 --> 00:38:08.840 officers so we have we have already discussed them a bit 00:38:08.840 --> 00:38:12.200 we've discussed them both you know we've mentioned them on the federal and the 00:38:12.200 --> 00:38:17.480 philanthropy side so for those of you who dealt with them like 00:38:17.480 --> 00:38:21.720 what like what is the importance of a of a program officer like what does it 00:38:21.720 --> 00:38:25.880 mean that we might lose a huge amount of them I think it's really gonna 00:38:25.880 --> 00:38:31.240 DL: impact the quality of the funded projects we see so 00:38:31.240 --> 00:38:35.480 Carrie was kind of describing earlier kind of how the you know NSF process 00:38:35.480 --> 00:38:38.520 works but I think something that was kind of 00:38:38.520 --> 00:38:41.480 skipped over there is that it's not just a black box you don't just like write a 00:38:41.480 --> 00:38:44.760 proposal and then you send it in and then it comes back later 00:38:44.760 --> 00:38:49.320 right so most successful proposals there are several conversations with the 00:38:49.320 --> 00:38:52.360 program officers along the way you send them a one or two page 00:38:52.360 --> 00:38:55.560 summary you have a conversation Carrie was mentioning there's all these 00:38:55.560 --> 00:38:58.200 different programs that fund different sorts of things and the program 00:38:58.200 --> 00:39:02.280 officers help you figure out what program fits what you want to do and 00:39:02.280 --> 00:39:05.720 do you align what you want to do with the goals of the program 00:39:05.720 --> 00:39:11.640 so I think that is a huge part of what program officers do in that they help 00:39:11.640 --> 00:39:15.320 make the science and the math better 00:39:11.640 --> 00:39:15.320 CDZ: yeah no I was going to say also and not 00:39:15.320 --> 00:39:18.760 just at the proposal stage but they also travel to 00:39:18.760 --> 00:39:23.960 conferences there are also where people are and they might see a really good 00:39:23.960 --> 00:39:26.920 you know talk and say like hey like have you ever thought applying to our 00:39:26.920 --> 00:39:31.000 program or could you be a reviewer and get people involved in the system and 00:39:31.000 --> 00:39:35.160 and help to understand it I was recently at the AAAS 00:39:35.160 --> 00:39:38.280 conference which is the American Association for the Advancement of 00:39:38.280 --> 00:39:42.280 Science which is a DC policy broadly STEM professional 00:39:42.280 --> 00:39:45.320 society and I mean I was like wow there are a lot 00:39:45.320 --> 00:39:48.040 of booths missing because all the federal booths are gone like 00:39:48.040 --> 00:39:51.880 there's no you know if you did happen to have some 00:39:51.880 --> 00:39:56.040 sort of affiliation with NSF like that's not the hat you were wearing like so 00:39:56.040 --> 00:40:01.800 you couldn't tell I noticed that deeply the the absence of all 00:40:01.800 --> 00:40:07.480 sorts of federal agencies missing the agencies that 00:40:07.480 --> 00:40:11.160 could be talking to students about hey like you know here are some 00:40:11.160 --> 00:40:15.320 options for funding graduate school or might be talking to faculty about 00:40:15.320 --> 00:40:19.080 hey did you know that we have this new program in 00:40:19.080 --> 00:40:23.000 I don't know teaching AI and mathematics courses I don't know but like 00:40:23.000 --> 00:40:27.640 whatever the thing is they just weren't there anymore 00:40:23.000 --> 00:40:27.640 DL I think it's interesting 00:40:27.640 --> 00:40:31.800 so the the RUME conference the research and undergraduate math education 00:40:31.800 --> 00:40:35.880 conference is happening I think right now as we speak 00:40:35.880 --> 00:40:39.400 like a quarter of a mile from the NSF headquarters 00:40:39.400 --> 00:40:43.000 and the program officers were because of the travel ban right we're not allowed 00:40:43.000 --> 00:40:47.560 to walk down the street to the conference 00:40:47.560 --> 00:40:50.360 SH: one of the one of the other things that program officers do 00:40:50.360 --> 00:40:55.480 is that they help make sure that the review process 00:40:55.480 --> 00:41:00.200 keeps going and they you know help as Carrie mentioned find people to review 00:41:00.200 --> 00:41:02.440 they also make sure that all the meetings happen and that all the 00:41:02.440 --> 00:41:05.880 decisions are meeting their deadlines and things and 00:41:05.880 --> 00:41:09.240 one of the things that I really don't want us to 00:41:09.240 --> 00:41:13.800 miss out on is the idea that the current administration could essentially 00:41:13.800 --> 00:41:18.440 stop federal funding not by not spending it not by completely 00:41:18.440 --> 00:41:21.640 shuttering the agencies or anything like that you know such as they did with 00:41:21.640 --> 00:41:25.880 USAID they could effectively stop it by just 00:41:25.880 --> 00:41:30.040 making it so that there's so few employees that nothing can actually get 00:41:30.040 --> 00:41:34.840 done so they could claim look

we're trying to spend the money 00:41:34.840 --> 00:41:37.640 but if we don't have enough program officers to actually 00:41:37.640 --> 00:41:42.680 oversee all of the review processes and all of the grant applications and 00:41:42.680 --> 00:41:45.960 things it could be that some grants get given but 00:41:45.960 --> 00:41:49.960 you know it's a couple a year instead of the thousands now 00:41:49.960 --> 00:41:56.200 CDZ: yeah well even even the whole you know firing before they 00:41:56.200 --> 00:42:03.880 fired 10 of their staff they they were asked to review all I don't I 00:42:03.880 --> 00:42:07.560 can't I heard some number I think it was like 50 000 proposals that they 00:42:07.560 --> 00:42:10.760 have funded already so already they're like where are we going to 00:42:10.760 --> 00:42:15.000 find the time to do that right and then on top of that you fire 10 00:42:15.000 --> 00:42:18.840 percent of your staff right and and and many who I've talked to say 00:42:18.840 --> 00:42:24.040 that's just the first round right so you're actually creating extra work 00:42:24.040 --> 00:42:32.040 not efficient work and so you know I think I think that I have heard 00:42:32.040 --> 00:42:35.400 suggestions about using things like generative AI 00:42:35.400 --> 00:42:40.200 large language models to step in and fill these roles as if 00:42:40.200 --> 00:42:46.680 you know the quality of the mostly but not all a lot of PhDs 00:42:46.680 --> 00:42:51.640 is somehow can be replaced by a generative AI I think it shows 00:42:51.640 --> 00:42:58.440 a general disrespect for what program officers actually do right and 00:42:58.440 --> 00:43:03.320 and I think like I have heard some folks chime in with critiques about NSF 00:43:03.320 --> 00:43:07.240 and I'm like now is that like I get it there are always things that can be 00:43:07.240 --> 00:43:11.800 improved but like now's the time to like go on the other side and say like 00:43:11.800 --> 00:43:16.200 yes we're we critique because it's an important thing in our lives that we 00:43:16.200 --> 00:43:20.840 want to get better and and sometimes we need to also fight for it too 00:43:20.840 --> 00:43:24.600 right and don't forget that at the same time 00:43:20.840 --> 00:43:24.600 JH: I would 00:43:24.600 --> 00:43:28.040 totally agree with you Carrie and I think I would 00:43:28.040 --> 00:43:32.120 rather than saying I don't even know that it gets to 00:43:32.120 --> 00:43:36.360 the level of disrespect because I think to garner that 00:43:36.360 --> 00:43:41.320 type of language requires an understanding of something right and I 00:43:41.320 --> 00:43:44.920 think it's actually ignorance fueled contempt 00:43:44.920 --> 00:43:49.480 is is sort of how I would phrase it I I think it's like folks 00:43:49.480 --> 00:43:53.640 literally do not understand what is happening 00:43:53.640 --> 00:43:57.320 I think part of the disconnect Carrie 00:43:57.320 --> 00:44:02.200 sort of touched on earlier in the conversation but I do think that 00:44:02.200 --> 00:44:09.400 it is sort of a multi decades driven philosophy 00:44:09.400 --> 00:44:14.920 that government is inherently wrong, government it is inherently bad, anything 00:44:14.920 --> 00:44:18.760 funded by the government is inherently wasteful 00:44:18.760 --> 00:44:25.880 and that is the sort of like the noble truth that undergirds all of this 00:44:25.880 --> 00:44:30.200 and all the actions flow from there so it's like if that is the foundational 00:44:30.200 --> 00:44:34.840 sort of cosmological philosophical belief that you have 00:44:34.840 --> 00:44:39.240 anything is justified at that point and you know this is where we get into the 00:44:39.240 --> 00:44:42.680 scenarios that go far beyond the NSF where it's like oh yeah 00:44:42.680 --> 00:44:46.760 oh those folks were keeping our nukes safe oh yeah those folks were like helping 00:44:46.760 --> 00:44:50.840 us respond to make sure Ebola or the bubonic plague doesn't end up in 00:44:50.840 --> 00:44:53.640 the you know but you don't understand that that's 00:44:53.640 --> 00:44:56.360 actually a function of government because it is sort of 00:44:56.360 --> 00:44:59.800 ignorance, fueled contempt of everything governmental 00:44:59.800 --> 00:45:03.480 CDZ: yeah and and when it works you don't know it's there 00:45:03.480 --> 00:45:08.760 right like unfortunately 00:45:03.480 --> 00:45:08.760 JH: it's odorless and flavorless yeah yeah 00:45:03.480 --> 00:45:08.760 CDZ: yeah yeah I think 00:45:08.760 --> 00:45:11.960 we saw this we were seeing this also one of the other 00:45:11.960 --> 00:45:15.800 orders had to do with trying to cut the overhead to 15 percent and not really 00:45:15.800 --> 00:45:21.400 understanding what that actually means and and if you look at some of the DEI 00:45:21.400 --> 00:45:26.200 memorandums or memos or whatever kinds of things that have been sent 00:45:26.200 --> 00:45:30.040 they try to position DEI in particular as like 00:45:30.040 --> 00:45:35.560 taking away from low-income white people right like they see it as a taking away 00:45:35.560 --> 00:45:39.080 and and so what I think is really interesting is some folks made this 00:45:39.080 --> 00:45:43.640 really nice map of NIH funding where you can go and look to see top NIH 00:45:43.640 --> 00:45:47.320 funders in your state and it turns out that for Maine 00:45:47.320 --> 00:45:54.680 on that list of top three are two biological laboratories that are 00:45:54.680 --> 00:46:00.920 I would say economic powerhouses of our Republican Second District in a rural 00:46:00.920 --> 00:46:06.760 area that and we are talking about millions would be taken away from them 00:46:06.760 --> 00:46:12.600 by cutting the NIH overheads to 15 percent millions direct to them and 00:46:12.600 --> 00:46:16.920 multiply by at least a factor of two if not more 00:46:16.920 --> 00:46:24.200 for the impact to the local area and we're talking about jobs in 00:46:24.200 -->

00:46:28.520 what is like sometimes a touristy area that are year-round and are really hard 00:46:28.520 --> 00:46:33.800 to come by this would this would be devastating 00:46:33.800 --> 00:46:40.520 for rural low-income communities the same thing with DEI directly 00:46:40.520 --> 00:46:44.920 one of the things when I was an external visitor which is like an evaluator 00:46:44.920 --> 00:46:50.680 for a division program for IU's one of the things we recommended was to 00:46:50.680 --> 00:46:54.200 reinvest in EPSCOR states these are rural 00:46:54.200 --> 00:47:00.280 low-funded states exactly the kind of demographics that I think 00:47:00.280 --> 00:47:03.320 they are thinking are being left behind and so 00:47:03.320 --> 00:47:07.880 I think you know we need to spend a little bit of time talking about 00:47:07.880 --> 00:47:12.440 how these things are going to directly impact 00:47:12.440 --> 00:47:19.800 and take away from everyone as well 00:47:12.440 --> 00:47:19.800 SH: And so while the NSF money seems to still be 00:47:19.800 --> 00:47:24.760 flowing mostly there's probably some one-offs that we don't know about but 00:47:24.760 --> 00:47:29.320 seems to mostly be flowing there there are cases where it is already having 00:47:29.320 --> 00:47:34.120 direct impact and one of those is on the research 00:47:34.120 --> 00:47:38.600 experience for undergraduates area which is something that as far as I know 00:47:38.600 --> 00:47:41.640 actually started in mathematics it's definitely something that's very 00:47:41.640 --> 00:47:45.080 strong in mathematics and these are summer programs that 00:47:45.080 --> 00:47:49.480 undergraduate students get to go to and experience 00:47:49.480 --> 00:47:53.880 like doing mathematical research which is and I will say this from my 00:47:53.880 --> 00:47:57.800 personal experience not something that I knew anything about until 00:47:57.800 --> 00:48:02.280 after I had already been in grad school for a while 00:48:02.280 --> 00:48:05.640 it's not even like you start math grad school and you start in classes like you 00:48:05.640 --> 00:48:08.840 don't this is not this is not like biology or physics or 00:48:08.840 --> 00:48:11.720 something like that where there's labs that you go into right away and 00:48:11.720 --> 00:48:18.120 oftentimes you're already in in undergrad times so I would love to 00:48:18.120 --> 00:48:22.040 know if either of you have have had any experience with r.e.u.'s and 00:48:22.040 --> 00:48:26.520 what it could mean if these r.e.u.'s keep shuddering and what that could mean for 00:48:26.520 --> 00:48:30.600 mathematics and and also like the bigger picture of what it could mean 00:48:30.600 --> 00:48:35.000 beyond just our our parochial little area of academia 00:48:35.000 --> 00:48:38.200 DL: I wouldn't be talking to you today if it wasn't for an r.e.u. 00:48:38.200 --> 00:48:42.280 I wouldn't I wouldn't be a mathematician if it wasn't for an r.e.u. so when I was 00:48:42.280 --> 00:48:45.800 when I was an undergrad I was a computer science major and I was 00:48:45.800 --> 00:48:49.800 I did a math major too just for funsies to make myself a little different 00:48:49.800 --> 00:48:54.120 but one of the one of the elder math majors shared about what they did in a 00:48:54.120 --> 00:48:57.320 r.e.u. experience this summer before and I thought this was amazing that you 00:48:57.320 --> 00:49:01.720 could go get paid to do math so I went and did one of these and 00:49:01.720 --> 00:49:05.480 learned what math research was and then immediately decided I'm not going to go 00:49:05.480 --> 00:49:09.320 be a programmer bro for the rest of my life I'm going to apply to grad school 00:49:09.320 --> 00:49:14.600 in math and I don't think that's a unique story I 00:49:14.600 --> 00:49:18.680 I shared this on blue sky the other day and a bunch of people are 00:49:18.680 --> 00:49:22.920 applying yes me too I did a r.e.u. I would not be a scientist today if I had 00:49:22.920 --> 00:49:27.960 not had this r.e.u. experience back at back at the time 00:49:27.960 --> 00:49:31.880 and we're seeing so many of these are being canceled this summer because of a 00:49:31.880 --> 00:49:35.320 lack of funding and I think what's really crucial about the r.e.u.'s 00:49:35.320 --> 00:49:40.280 is they happen for students at a very particular time 00:49:40.280 --> 00:49:45.400 in their preparation career right you do these in the summer 00:49:45.400 --> 00:49:49.720 while you're an undergraduate and that often is the catalyst to get 00:49:49.720 --> 00:49:53.640 undergraduate students to think oh I could go get a PhD I could be a 00:49:53.640 --> 00:49:57.080 scientist and when you take that away at that critical time 00:49:57.080 --> 00:50:00.920 right they're never even going to think that they have this opportunity to 00:50:00.920 --> 00:50:04.120 come do that and so it's just going to be an incredible loss 00:50:04.120 --> 00:50:08.680 for us you know 10 20 years down the road when these would have been 00:50:08.680 --> 00:50:12.760 scientists with PhDs doing the the cutting-edge you know math and science 00:50:12.760 --> 00:50:17.000 research that we want to happen 00:50:12.760 --> 00:50:17.000 CDZ: Yeah back when I was talking about 00:50:17.000 --> 00:50:23.720 program officers at meetings like I was at a meeting an NIH program officer 00:50:23.720 --> 00:50:27.080 was there saying hey like did you know that if your 00:50:27.080 --> 00:50:31.000 advisor has NIH money he can write for a supplement 00:50:31.000 --> 00:50:38.040 to help hire you so that you can spend a semester or a year or however much time 00:50:38.040 --> 00:50:42.920 working on your dissertation and not have to teach and I was like what 00:50:42.920 --> 00:50:46.120 so I went and told my advisor you can hire me 00:50:46.120 --> 00:50:52.680 and he's like I can like like if I if that program officer hadn't been there 00:50:52.680 --> 00:50:56.360 you know I mean how much I

did not need extra years 00:50:56.360 --> 00:51:00.840 believe me to finish my PhD I don't know if I would have finished 00:51:00.840 --> 00:51:07.800 um so yeah these are I think REU's I think there's um I've also seen it in my 00:51:07.800 --> 00:51:11.240 own students grad school admissions are down 00:51:11.240 --> 00:51:16.040 particularly institutions that have that rely on research funds 00:51:16.040 --> 00:51:21.960 to do this I think for some places there is a little bit more going on there 00:51:21.960 --> 00:51:25.320 was renegotiation of union contracts that were already 00:51:25.320 --> 00:51:28.920 raising wages on this teaching and research assistant side 00:51:28.920 --> 00:51:33.160 and then when coupled with all of this uncertainty about federal funding 00:51:33.160 --> 00:51:37.000 it's just like cause some some some places are pausing 00:51:37.000 --> 00:51:42.280 entire graduate enrollments and so I think it is 00:51:42.280 --> 00:51:45.880 going to have impacts for a long long time 00:51:45.880 --> 00:51:52.200 beyond the immediate and what I will say is that even though we are 00:51:52.200 --> 00:51:57.320 talking primarily about federal funding the private sector has not remained 00:51:57.320 --> 00:52:00.840 unscathed so in my community working in inclusive 00:52:00.840 --> 00:52:07.400 STEM education it was a huge shock when the Howard Hughes Medical 00:52:07.400 --> 00:52:13.160 Institute's education foundation side of the 00:52:13.160 --> 00:52:16.600 operations because they have a research side and they have an 00:52:16.600 --> 00:52:21.080 outreach granting agency for education terminated its 00:52:21.080 --> 00:52:25.160 HHMI IE, inclusive excellence funding this means 00:52:25.160 --> 00:52:29.080 we they they had a few different cohorts go through the program 00:52:29.080 --> 00:52:32.840 cohort one has already been done I'm in cohort two 00:52:32.840 --> 00:52:37.640 our funding wasn't was in extension and it's final so we were told 00:52:37.640 --> 00:52:41.160 you know use up your money no final report that's it 00:52:41.160 --> 00:52:48.680 the next group after us was IE three they still had active awards ongoing that 00:52:48.680 --> 00:52:52.280 were closed immediately and again had staff 00:52:52.280 --> 00:52:56.200 working trying to make sure that you know students had 00:52:56.200 --> 00:52:59.960 good advisors or there was professional development for faculty or 00:52:59.960 --> 00:53:04.040 whatever else they had real jobs and didn't have on the next day 00:53:04.040 --> 00:53:07.320 and we're talking about a private funding agency 00:53:07.320 --> 00:53:12.440 that halted its programs Science coverage seems to suggest that this had to 00:53:12.440 --> 00:53:16.440 do with executive order orders targeting the threat of 00:53:16.440 --> 00:53:21.160 removing nonprofit status to foundations that funded DEI work 00:53:21.160 --> 00:53:25.880 I also imagine that because HHMI does both science work 00:53:25.880 --> 00:53:31.720 and has a foundation's arm this is me guessing this is but I think also was 00:53:31.720 --> 00:53:35.720 probably influenced by the instability of the the biomedical funding 00:53:35.720 --> 00:53:40.360 landscape as well so where some might be pivoting 00:53:40.360 --> 00:53:44.440 towards private grants some of those have also been withheld 00:53:44.440 --> 00:53:50.280 and we've seen Mark Zuckerberg's foundation CZI removed one of its 00:53:50.280 --> 00:53:53.880 fellows programs that were targeted towards 00:53:53.880 --> 00:53:57.560 supporting early career research fellows and other 00:53:57.560 --> 00:54:01.160 foundations I think Sloan for example has 00:54:01.160 --> 00:54:04.680 sort of said we don't expect to give any high number awards because we think 00:54:04.680 --> 00:54:07.480 we're going to get 10 times the applications and so 00:54:07.480 --> 00:54:10.680 we want to you know we're really probably going to fund 00:54:10.680 --> 00:54:15.640 try to fund more awards for less money and so 00:54:15.640 --> 00:54:19.640 this is having ripple effects throughout the entire ecosystem 00:54:19.640 --> 00:54:26.600 and I think for many years to come and has maybe opened our eyes 00:54:26.600 --> 00:54:33.560 to whether institutions were really fundamentally invested 00:54:33.560 --> 00:54:39.240 in equity and justice or just throwing money at it 00:54:33.560 --> 00:54:39.240 SH: So 00:54:39.240 --> 00:54:45.640 Carolyn Ibberson on Blue Sky I believe it was it was originally 00:54:45.640 --> 00:54:49.480 shared on February 22nd but the list keeps growing 00:54:49.480 --> 00:54:55.640 it shared a spreadsheet of reductions in admission and hiring at 00:54:55.640 --> 00:54:59.960 institutions as far as they are aware and so that now 00:54:59.960 --> 00:55:05.640 includes a reduction slash pause at University of Wisconsin Madison where 00:55:05.640 --> 00:55:11.960 I got my library degree across all programs there is 25 percent 00:55:11.960 --> 00:55:18.840 delaying offers at UNC Chapel Hill there's up to 60 percent admission cut 00:55:18.840 --> 00:55:23.320 at University of Pennsylvania and this is all this expectation of getting 00:55:23.320 --> 00:55:27.240 less and less money and there's also a number of 00:55:27.240 --> 00:55:34.920 places that are also instituting hiring freezes or slowdowns or pauses so 00:55:34.920 --> 00:55:41.880 well while I of course have been focusing us mostly on math today like this is a 00:55:42.680 --> 00:55:49.480 say landscape-wide sort of problem and one that if I'm going to be 00:55:49.480 --> 00:55:53.000 completely honest might actually start impacting math 00:55:53.000 --> 00:55:56.920 well not start that might impact math slightly less 00:55:56.920 --> 00:56:00.680 than the other fields just because math gets slightly less funding 00:56:00.680 --> 00:56:05.240 whereas you know in in health funding the the percentage of 00:56:05.240 --> 00:56:10.040 I mean in healthy

like there's just so much funding that it could 00:56:10.040 --> 00:56:15.480 have outsized impacts 00:56:10.040 --> 00:56:15.480 CDZ: Yeah though I think we have to say for whom 00:56:15.480 --> 00:56:18.600 so I think I think there's a huge asterisk here 00:56:18.600 --> 00:56:25.000 so for example LatMath this year couldn't provide funding for any faculty 00:56:25.000 --> 00:56:31.400 other than who was invited to speak that's a direct result of the freezes 00:56:31.400 --> 00:56:37.240 and the unknowingness of funding so now we're talking about specific 00:56:37.240 --> 00:56:41.160 initiatives that are meant to celebrate and 00:56:41.160 --> 00:56:44.360 build the capacity for mathematics research that 00:56:44.360 --> 00:56:48.840 that happens within the Latino community in the US 00:56:48.840 --> 00:56:52.360 and so I think the the impacts for whom have to be 00:56:52.360 --> 00:56:56.280 I think there has to be a huge asterisk there 00:56:52.360 --> 00:56:56.280 SH: Of course 00:56:56.280 --> 00:57:00.600 yes you are you are very correct because while you might be able to convince 00:57:00.600 --> 00:57:04.520 say your department to give you funding to go out to the joint math meetings 00:57:04.520 --> 00:57:08.200 because they are you know the big one the thing to do 00:57:08.200 --> 00:57:12.440 the smaller conferences could yeah the the for whom 00:57:12.440 --> 00:57:16.760 could impact them a lot more 00:57:12.440 --> 00:57:16.760 CDZ: Or some people don't have departments that 00:57:16.760 --> 00:57:20.760 have money to send them places I've been there before in my life 00:57:20.760 --> 00:57:23.880 and you know 00:57:20.760 --> 00:57:23.880 SH: Oh no no no that that of course I'm like 00:57:23.880 --> 00:57:27.720 but just if you're likely to get any money at all 00:57:27.720 --> 00:57:31.160 it would be probably easier for the for the larger 00:57:31.160 --> 00:57:36.600 conferences than a smaller ones that probably have outsized impact 00:57:36.600 --> 00:57:40.200 on the people who attend them as opposed to the 00:57:40.200 --> 00:57:44.120 jmm which could have impact or could just be a giant waste of money for the 00:57:44.120 --> 00:57:46.840 people who attend 00:57:46.840 --> 00:57:51.320 so I mean we've been going for a while so I think we probably need to 00:57:51.320 --> 00:57:56.840 wrap this seminar up and what I would like to do is to ask for any sort of 00:57:56.840 --> 00:58:00.200 final concluding thoughts potential next steps you could 00:58:00.200 --> 00:58:06.280 see for for what we could try to do to survive 00:58:06.280 --> 00:58:10.840 this this changing in the landscape 00:58:06.280 --> 00:58:10.840 JH: Well so I think that Carrie hit on 00:58:10.840 --> 00:58:14.520 something that you know Chad and I have been really sort of zeroing it on 00:58:14.520 --> 00:58:18.440 within our sort of ties to the academic community is 00:58:18.440 --> 00:58:22.040 the things that we believe in fundamentally are worth 00:58:22.040 --> 00:58:26.680 fighting for and being quiet being silent 00:58:26.680 --> 00:58:30.600 about those things is not going to save any of it any of the things that we 00:58:30.600 --> 00:58:34.520 care about right it's it's just not and I I will 00:58:34.520 --> 00:58:40.040 tell you that my personal posture on this is yes everyone has to sort of 00:58:40.040 --> 00:58:43.960 find their path here and I'm not trying to finger wag at anyone right it is a 00:58:43.960 --> 00:58:48.120 weird moment and gravity feels upside down 00:58:48.120 --> 00:58:52.920 right now everything is upturned but I would just encourage 00:58:52.920 --> 00:58:57.160 everyone to know what you stand for and stand for it now 00:58:57.160 --> 00:59:03.400 because it it it will get eroded right out from under you and then it 00:59:03.400 --> 00:59:06.760 there is a point at which it may be too late right and so 00:59:06.760 --> 00:59:10.440 you know again it's like stand for what you stand for now is your moment 00:59:10.440 --> 00:59:15.000 you know we all need to know and we need to stand up strongly and link arms 00:59:15.000 --> 00:59:19.640 with people who believe in science right and who believe in the fundamental 00:59:19.640 --> 00:59:25.000 value of this endeavor 00:59:19.640 --> 00:59:25.000 DL: I guess what I'll suggest for things we can do to survive 00:59:25.000 --> 00:59:28.920 that I found helpful is just finding community with the 00:59:28.920 --> 00:59:32.760 other folks like present company that are committed to 00:59:32.760 --> 00:59:36.840 doing the work no matter what's going on right 00:59:36.840 --> 00:59:40.760 and I think that's been really helpful for me just to just to stay engaged and 00:59:40.760 --> 00:59:44.680 know that there are other folks that still care about this that are still 00:59:44.680 --> 00:59:48.120 doing the work it has to look a little different right now 00:59:48.120 --> 00:59:51.800 we may have to rewrite what shows up on the the public web page 00:59:51.800 --> 00:59:55.160 about our work we're gonna do but we're still gonna show up and 00:59:55.160 --> 00:59:59.320 and do that do that work together so that's that's been giving me 00:59:59.320 --> 01:00:03.960 a little bit of hope as we try and navigate all of this 00:59:59.320 --> 01:00:03.960 CDZ: Yeah I'm gonna 01:00:03.960 --> 01:00:08.520 plus one what Drew said in terms of community I think 01:00:08.520 --> 01:00:12.040 not being alone in this having many community eyes 01:00:12.040 --> 01:00:18.040 in on this and giving updates and I I can speak about you know our RIOS 01:00:18.040 --> 01:00:21.720 community or the data science for social justice community but also the blue 01:00:21.720 --> 01:00:25.240 sky community like coming in at a big time where 01:00:25.240 --> 01:00:29.000 twitter used to be that place where I think it was happening and 01:00:29.000 --> 01:00:36.360 to have blue sky be be there has has been huge I'll also 01:00:36.360 --> 01:00:43.960

reflect on what Jude said know what you stand for and stand for that now 01:00:43.960 --> 01:00:49.000 one of the things that happened pretty early into this process 01:00:49.000 --> 01:00:55.640 was I feel like as I don't want to say an old person but an older person 01:00:55.640 --> 01:01:00.600 than my students or early career faculty I feel like this isn't the first time 01:01:00.600 --> 01:01:05.800 I've done you know been in the academic ecosystem and and had these you know 01:01:05.800 --> 01:01:09.720 trump as president and and saw climate change get removed from all the 01:01:09.720 --> 01:01:13.240 websites and and all of all of the things 01:01:13.240 --> 01:01:17.560 and I I kind of went back I know there's a lot of differences between what's 01:01:17.560 --> 01:01:21.480 going on today and what happened then in a lot of ways but 01:01:21.480 --> 01:01:26.680 I had done this really interesting study a few years back where I had looked at 01:01:26.680 --> 01:01:31.720 DEI language in a journal archive of educational lesson 01:01:31.720 --> 01:01:35.640 plans and looked at how that journal language changed over time 01:01:35.640 --> 01:01:41.160 and one of the predominant narratives that's been given around our attitudes 01:01:41.160 --> 01:01:44.920 towards DEI is that we've had this shift in 2020 and then people started paying 01:01:44.920 --> 01:01:48.200 attention and so I feel like if I were to look at archives of published lesson 01:01:48.200 --> 01:01:51.880 plans post 2020 I would see this sort of signal of increased 01:01:51.880 --> 01:01:57.160 DEI language in fact what I noticed was earlier 01:01:57.160 --> 01:02:01.480 and I had you know based on the timeline of submission and review and 01:02:01.480 --> 01:02:04.200 everything that this was actually happening closer 01:02:04.200 --> 01:02:08.680 the submissions were happening closer to 2018 2019 01:02:08.680 --> 01:02:12.600 and so I had thought about okay well what's happening in 2018 like what's 01:02:12.600 --> 01:02:16.200 what's going on at NSF or you know released its includes program which was 01:02:16.200 --> 01:02:20.680 focused on on inclusion there was like some real 01:02:20.680 --> 01:02:24.040 funding you know activities and spotlights 01:02:24.040 --> 01:02:27.400 because of that includes program of such a big launch it wasn't the only thing 01:02:27.400 --> 01:02:33.320 that was happening but it was a thing and that's kind of when I had 01:02:33.320 --> 01:02:36.520 done that study that's kind of where I had landed like okay like 01:02:36.520 --> 01:02:39.960 there was a lot of enthusiasm we had a lot of real fine finally some 01:02:39.960 --> 01:02:43.640 investment in that area and then we we we got some 01:02:43.640 --> 01:02:47.320 good research and professional development and then and then this shift 01:02:47.320 --> 01:02:49.800 happened I've been thinking about it a lot 01:02:49.800 --> 01:02:53.960 differently I've been thinking about who I was as an educator 01:02:53.960 --> 01:03:02.600 and where my socio-political turn was and I I think that I doubled down on that 01:03:02.600 --> 01:03:07.960 commitment right after the 2016 election I think the result 01:03:07.960 --> 01:03:12.760 the investments what what we saw happening at the level of NSF and 01:03:12.760 --> 01:03:18.360 all of these other things were not things of 2018 01:03:18.360 --> 01:03:26.360 they were reactions from a community to what was happening in 2016 and 2017 01:03:26.360 --> 01:03:31.480 and we activated we had the women's march we had march for science 01:03:31.480 --> 01:03:38.040 we fought our federal cuts we stood up and I think many of us 01:03:38.040 --> 01:03:43.800 ground down and recommitted to a new vision of what this future could be 01:03:43.800 --> 01:03:51.000 and so when I landed on that narrative I started seeing that this is a place 01:03:51.000 --> 01:03:56.200 of opportunity also for us to do something even better and remake this even 01:03:56.200 --> 01:03:59.800 better than it was before 01:03:56.200 --> 01:03:59.800 SH: Well don't think we're going to get any 01:03:59.800 --> 01:04:03.400 better closing than that so I want to thank 01:04:03.400 --> 01:04:07.160 Jude Drew and Carrie so much for joining me thank you 01:04:07.160 --> 01:04:10.760 for taking part in this seminar 01:04:07.160 --> 01:04:10.760 DL: Thank you it's been a pleasure 01:04:10.760 --> 01:04:13.560 thanks so much Sam

스크립트 수정