Tomas Pueyo is the author of Uncharted Territories, a newsletter where he tries to deeply understand how the world works to understand where it’s going and nudge it in the right direction. He became world viral with his COVID articles, notably The Hammer and the Dance. He has 75,000 readers, and 300,000 on Twitter, where you can find him at @tomaspueyo. Before Uncharted Territories, he has worked in tech companies in Silicon Valley for 15 years.
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Welcome back to the PolicyViz podcast. I am your host, Jon Schwabish. On this week’s episode of the show, I talked to Tomas Pueyo, who runs the Uncharted Territories newsletter on Substack. Tomas’ content covers, well, basically everything, from climate change to the war in Ukraine, to sex and romance and relationships. COVID, I mean, you name it, he is going deep into these various topics, and so, what you’ll hear in our conversation is how he goes about doing that. And, more importantly, if you’re listening to this because of data visualization, his thoughts on maps, he has a terrific Twitter thread that I will link to in the show notes on how maps distort our perceptions of the world. And so, we talk at length about how maps do that, and how AI and new technologies might help us make maps better. So before I let you go into this week’s episode, I would just ask you if you could – if you could take a moment, rate or review this podcast on your favorite podcast provider, be an Apple, be it Botify, be it Google podcasts, whatever you listen to, please consider leaving a rating or review. And while you’re heading over to the Uncharted Territories newsletter from Tomas, please consider signing up for my PolicyViz newsletter, it comes out every other week to correspond with the podcast. You get a draft blog post or other things that I’m working on, a list of things I’m reading and watching, a list of data visualizations that I think are particularly interesting; and in this week’s newsletter, a little poll to ask you what you think I should be doing on my YouTube channel. So enough of that, let’s get into the podcast episode. Here is my conversation with Tomas Pueyo of Uncharted Territories.
Jon Schwabish: Hi Tomas. Good to meet you. Welcome to the show.
Tomas Pueyo: Hi Jon. Thanks for having me.
JS: Very excited to chat with you. We’ve got a lot to talk about, because your Substack newsletter, Uncharted Territories, you cover a lot of ground, so I think we have a lot to chat about. But I thought we would just start with maybe you talk a little bit about your background and how you kind of got to the point now where on your Substack newsletter’s like your thing, your gig.
TP: Yeah. So I used to live in the Bay Area, and I worked in tech. I did that for around 15 years doing product and growth. And I started writing on the side, I never published anything, but after a few years, I decided, okay, I’ll just start writing, I posted on Medium. And then, at the beginning of COVID, I got a couple of articles that exploded virally. So I started gathering an audience there, and eventually moved to Substack. And for some reason that I have a hard time understanding, some people are willing to pay money to hear my opinions, and there’s enough of them now that I can live off of it. And so, you know, this year, I dropped my product and tech career, and I’m focusing full time on this.
JS: Yeah, and you are covering, I mean, I was just scrolling through like the archives, which is great on Substack, you just kind of like look through everything, but, like, you cover attraction between people, you talk about Ukraine, climate change, maps, which we’ll talk about in a second, like, what inspires you or how do you find, I mean, there’s plenty of content, but what drives you to write about the topics that you worry about?
TP: Oh my god, there’s too much of it. In fact, as a creator, it’s a penalty, right, because people, they want to follow, for example, oh, an expert on COVID, right, or an expert on economy or something like this, and they have a really hard time understanding the person who touches a lot of topics, especially because, like, by definition, if you have breadth, you cannot have death, right? So I think this has penalized me in terms of audience, but I find it so boring to just focus on one thing that I just want to do it. And I think in my case, I just want to understand how the world works; and once we understand that, we can decide, okay, how should we nudge it in the future in the right direction. And I think for me the biggest thing is, everybody’s very siloed; and when people are very siloed, it’s very hard to make decisions that require being cross disciplinary.
I’ll just give you an example. So some people talk about fertility, right? There’s an issue about fertility today, there’s not enough kids, people say there’s too many people. Well, why, some people say that, actually, there’s too many people in the world because of climate change and the environment. So you need to understand environmentalism, if you want to understand it. Others say, actually, no, the cause of the fertility crisis is economic, right? There’s not enough developed economic growth. Others say, no, it’s urbanization. Others say, no, it’s cultural. And so, you actually need to understand the history of fertility, you need to understand economics, you need to understand urbanism, you need to understand all these things to understand some of these topics. And this is one of the reasons why I talk about all these topics, right? You mentioned climate change, but climate change, the origin of that was fertility. And then, you also mentioned maps and geography, and one of the keys there is, we don’t understand today how much our everyday lives are influenced by geography. And if we understand that, then we can understand so much more of how the world is today, and then how we can influence it for the future.
JS: Right. And where does, because I do want to talk about maps, because you have this great Twitter thread, and that was the original instinct for me reaching out, but where does the data come into play in your — both in the workflow, like, how do you start collecting data, and then also, in the final product, I mean, you are more or less making an argument sort of telling stories, but you’re – everything is sort of supported with data, so how are you thinking about, you know, I guess, the first question is, where are you looking for data, how are you working with it, processing it, and then, how do you think about weaving that into an article where people are not going to just, you know, nod off and say this is [inaudible 00:07:48] give me a bunch of numbers? I mean, that’s not easy.
TP: It is, you’re right, I think this goes at the heart of how this is fascinating. There’s two pieces that you need to do really well independently, right, you need to do the content well, and then, you need to do the communication well. And most of the people do one or the other. Right? You can see this, for example, in every scientific paper. There’s a lot of content in there that nobody reads them, and vice versa. Most of the communication today feels shallow, right? And so, the reason why this is the case is because the skill set for one or the other is completely different, and you really need to master them both, if you want, I think to be really impactful. And so, on the content side, because there’s so much communication that is very shallow and superficial, you need to go to the people who really have the content, and that means most of the time reading scientific papers. And so, like, for example, lately, I’m talking a lot about sex, differences between sexes, and how that shapes human behavior, I’ve probably read at this point, about 200 papers, maybe like 50 of them full, the rest skimmed or abstract, but I go straight to the papers, because that’s really where the source information is. And for each topic that I take, I go deep into that, and so, that incurs a lot of time, of course, but that’s one of the good sides of doing something that you’re passionate about is like, you can’t see the time, I can spend 60 hours a week reading papers, and I’m not going to be tired. So that’s on the content side. I really love a lot of these primary sources, and then, the key becomes how you package them in an interesting way. And there, I studied the storytelling, a lot of storytelling, when I went to Stanford, I took scriptwriting classes, I wrote a book about storytelling, I gave a TEDx about storytelling. All of that was to force myself to understand storytelling better, and then, I used those structures in all the articles I read.
JS: I see. So I wonder if you could give folks maybe some advice on how to read scientific papers, because that is also a skill, and a lot of people are not, you know, they’re not academics, they don’t have higher degrees, and, like, I think the idea of reading an academic paper is daunting for a lot of people. But like you said, that’s where the source material’s from. So, I mean, let’s just take one, like, your background may not be in sex and fertility, right? So where do you start, how do you start, how do you start reading those papers so that you feel like you can become an expert, at least, for the goal of writing three, four six, 10 newsletter articles?
TP: Yeah. So there’s a few ways to do that. One is, first, you need to find them, and there’s a couple of ways to do this, like, there’s a few search engines such as consensus thing that’s called; or, they’re just going straight to Google, you put your question, you write your question, and then, you add paper, and then, file type, PDF. And so, that usually is going to get either the search engine is this, that’s going to give you a lot of these papers. Then the papers are always going to have an abstract, which is a summary, it’s usually 10 lines, it takes you three minutes to read. They are usually written with a lot of jargon, but because it’s just 10 lines, even with jargon, you can make an effort and try to understand. And in most cases, you just need to read the abstract, to give a sense, to understand what the article is saying. If you need to go into the detail, I think a couple of keys there is the structure of the article itself. Usually, there’s an introduction, then there’s maybe methodology, then there’s results, and then, there’s the discussion. The introduction is put the study in context with all the other studies. And so, it’s actually very good to start in a field by reading one or two papers on the field, because it’s going to point you to all the other relevant people and relevant papers. And so, you very, very quickly can understand, like, who are the most relevant people here, and who are the most relevant papers. And so, there you can just follow the thread, and get to the top papers. Many of these papers are going to be-meta analyses, and the meta-analyses are the best to start, to really have a good sense of what’s happening.
So the introduction there is valuable, especially for the first papers, in a field that you’re reading, then methodology, usually a jump, because it’s only relevant insofar as the results are weird. It’s like, or, you have questions about, it, like, oh, they found this thing, that’s weird, like, why, how many people did they research is by sample, things like this. And so, you need to [inaudible 00:12:57] usually, you don’t need to go to the methodology. I usually browse also to see if there’s a graph, because graphs usually are going to show you many of the insights easily summarized. And then, if I really want to understand the details of what happened, I read the results. Results are going to give in details, okay, we did, this was the result of this thing, and this was a result of this thing. And then, finally, the discussion usually is a bit like the abstract but in detail, so bottom line, how to look at the paper, usually just the abstract, if you want to go more details, if you’re new in the field, look at the intro to understand all the other papers in the field; if not, just go to the discussion, and then, if you want to go deeper, you can go to the results; and if you want to go deeper, you can go to the methodology.
JS: Right. Good. Is there a tool that you use to manage your, like, references and citations and all those PDFs?
TP: You know what, I’m so bad, I’m so bad.
JS: Me too.
TP: So [inaudible 00:13:53] I have to write, I have to write. I read this somewhere, I’m sorry. I heard people use Zotero.
TP: I never used it.
JS: Yeah, I haven’t used it either, but a colleague of mine swears by it, like, I saw him yesterday, and he was giving me a hard time because I’m not using Zotero.
JS: But it’s I think it’s a big startup cost when you have like a whole library that you just want to move in. It’s not like you could go to, like, I don’t think, you can go to Google Scholar, like, copy the citation to drop it into Zotero. I think it’s a little bit more manual than that.
TP: Yeah, in my case, I don’t even – I have no system. My system is really linking the articles, like, the papers in my articles, and that becomes my index, because I remember my articles, and so, I can go back, oh, what was this paper. That’s not why, like, which is shitty, it’s terrible, but I think the point there is, you can go pretty far without any system. So I’m the kind of person to say, if you’re not a pro, and you’re thinking about your system for citations, that you’re doing something wrong, you’re procrastinating into actually just starting and working on this.
JS: Right. So let’s go to maps, because this was the reason I reached out in the first place, because you have this amazing Twitter thread about geography and about maps, which tags back to what you were talking about earlier, and how you sort of think about this broad landscape of content. And so, one of the things I was looking back, and I think you have a thread that sort of pulls all of your maps together, it is this tremendously long gray thread, but, like, you talk about how maps distort the world, and I was hoping you could talk more about that and how it distorts countries, governments, people, how policy works.
TP: Yeah, for sure, so there’s this, the big – the biggest way in which they’re distorted is the fact that you need to put a sphere in a plane, right? So the equator is the biggest part of the world, the poles are just the points, and if you need to put them into a rectangle, you need to expand the poles a lot, and you keep the equator straight, right, and so, the same. And so, the result of doing this is the farther up you go, north or south you go away from the equator, the bigger the space is going to look like. And it happens that the closer you are to the equator, the poorer the countries usually are, and we can talk about that in a second, because it’s fascinating why; and the farther away you go, the wealthier the countries. And so, it ends up being that the richer the country, the bigger it looks like on a map as opposed to reality. So, for example, if you look on a normal map, which is America projection, Greenland and Africa, they look kind of the same size, when in fact, it’s massively bigger than the other. And for me, I think two or three of the examples that are the most shocking here is the width of Africa is about the same as the width of Russia. It looks like it’s so much smaller, but it’s broadly the same width. And then another one that really shocked me is Indonesia, the country of Indonesia is about the same extension as Europe, all of Europe. In fact, one of the things that is an interesting shortcut to use is there’s a lot of big areas in the world that are quite similar inside. So the US is similar to Canada, Australia, India, China, Europe, you have all these big areas that are actually quite similar in size, and it definitely does not look like it in the map.
JS: Yeah, I think the one that I always come back to is that Greenland, Saudi Arabia, and the Democratic Republic of the Congo are all about the same size.
TP: That’s right.
JS: I mean, Greenland is such the, like, outlier there, right, and the way it’s portrayed.
TP: It’s sort of, and [inaudible 00:18:13] is that DRC is not even the Democratic Republic of the Congo, it’s not even the biggest country in Africa, it’s Algeria, and so, not even, let’s face it.
JS: Yeah. So maybe talk a little bit about the, so people understand the correlation between the distance from the equator and income, because you had mentioned that, the polar countries tend to be [inaudible 00:18:33].
TP: Yeah, this is crazy. So about two-three centuries ago, people started noticing this, right, like, the colonialist, European colonialists coming from the north or going close to the equator in Africa, in America, in Asia, and seeing that they’re poor, and they’re making – started making this hypothesis. And the hypothesis, of course, is going to be, oh, they’re lazier, right, and they [inaudible 00:18:57].
TP: And so, this racism thing has pervaded through centuries, and usually, I find these kinds of explanations of the world that are based on culture or morality, um, be very poor to actually explain the world. Usually, things are more connected to systems. And so, people are – one of the reasons why they say, like, yes, when you’re closer to the equator, it’s warmer, and so, because it’s so warm, you cannot really work as much. Meanwhile, us Protestants in Northern Europe, we work so much, and we were not so hard worker, right? It’s like, really, it is true that when temperatures increase, productivity decreases, but doesn’t mean that the being just warmer means you work less. So I’m looking into this a lot. There’s actually less written about this than you would imagine. And my current hypothesis is the following: when you’re closer to the equator, because it’s so hot, the places that get inhabited are different than closer to the poles. In Europe, the Alps, for example, the Pyrenees, or, in the US, the Appalachians, those are not populated, it’s too cold; and then, you have the plains that are populated. It is the reverse as you get closer to the equator; for example, if you look at the map of Colombia, all the people are in the mountains, they’re not in the jungles, they’re not in the – in fact, the Inca Empire was on the mountains; the Aztecs were in the mountains, and Mexico is the highest – is very, very high in elevation. La Paz in Bolivia is one of the highest elevation capital in the world.
And so, we have this pattern of the mountains are the ones that are populated when you’re closer to the earth’s equator; and it so happens that mountains are very bad for economic development, because it makes trade so much harder, and so, there’s much less; and so, you need to consume everything locally, which means that you have big local population, but you don’t have a lot of trade, so you don’t make a lot of money, so you import.
JS: Right. Not to mention the colonialism that you mentioned earlier.
TP: That’s right. But then we get into a complete different topic.
TP: If you want one day, we can debate it.
JS: I don’t know if people are going to listen to an eight-hour podcast, so we’ll move on. So you have this understanding or background of thinking about how maps distort our perception of the world. And so, when you write about the various pieces of content that you write about, do you try to educate your readers on some of these aspects of distortion? So when you write about economics, or you write about fertility rates, I mean, any, climate change, any of these things that you’re talking about, and the way that people think about the world is not necessarily true. Like you just said, these distortions that we see in the size of countries and how they’re arranged and how they’re aligned are not necessarily true. So do you try to kind of break that thought process, I find many of your readers have?
TP: Yeah, I think I try to do that with every topic that I try. I’m trying to take example, right? I think one of them is the – illustrate to your point is why the island of Java in Indonesia has more population than all of Russia, which is the biggest country in the world, right? And you can show the sizes, it’s ridiculous how different [inaudible 00:22:51]. And then you can go into the detail, like, you use that as a hook, right, and then you can go into the detail; and it turns out that one of the main reasons why Java is so populated is because of volcanism. Because it’s a volcanic island, it’s east-west, and there’s volcanic eruptions, and then, all the ash falls on the land, and the ash is amazing for the fertility of the ground. And so, the growth of rice there is orders of magnitude better than in neighboring Sumatra, for example. So those are – that’s an example, I think, If you generalize it, this way, I try to do with every – each one of the topics, I just try to go deep and understand which ones of our preconceived opinions were right, and which ones were wrong.
And I’ll give you another example, I was looking into climate change, and I come at every topic without a bias, like, I just want to understand it, like, what’s going on. And so, for climate change, my prior there was the earth is going to be – the survival of Earth is going to be challenged in these event that has never ever happened before. Right? And so, when I looked into the details, it turns out that, well, the temperature of the Earth was higher 3 million years ago and earlier, there was more CO2 at that point, the previous events of mass animal destruction were probably worse than they’re going to be here. And so, you start seeing these claims that, okay, I thought these were true, they’re not, and then, you can narrow – zero in into the ones that are, right? And so, what is true, like, the speed of the change is faster than it’s ever been. That’s one. Then the economic displacement is going to be very, very, very bad. Humans are not going to disappear. Nature is not going to disappear. Most animals are not going to disappear, but it’s going to be really bad for a bunch of animals, and economically for a lot of people which might cause immigrations and wars and things like this, right? But narrowing down what specifically the issue is, that allows us to better understand what problem is, and then, to better solve it.
JS: Right. And so, it sounds like a lot of your work is in a lot of ways sort of fighting the misinformation and disinformation that’s out there, because you’re trying to go deep, and not necessarily refuting some claim that someone’s made, but educate people on some topic, you know, really based in the literature. Do you feel that responsibility when you’re writing that you’re trying to resolve, you’re trying to fight against that a little bit?
TP: Yes, it’s very much the aim of what I’m trying to do, right, and really deeply understand the world, so you can nudge it in the right direction. And it’s what we were saying, those were [inaudible 00:26:03] communicating are usually better at understanding the content and vice versa. And so, bridging that gap I think is important, and there are a few people doing it, but not enough, and I think, at the end of the day, most of the decisions that we take as a society, either culturally or politically are based on the analysis of these problems. And so, if you don’t understand these problems, you will make poor decisions. I think the best example of this is what I did in COVID, right? And my first articles became very viral, the first one was alerting the world, hey, this is coming, and you don’t understand what’s going on, you need to close your country as fast as possible. That got around 50 million views. And then, the next one after that, the hammer and the dance was a proposal on how actually to manage the pandemic. And the idea of it is, look, you have no idea what’s going on, and so, the only thing you can do is you need to stop everything right now to understand better, and to build some stopgap solutions. And once you understand that, then you need to do a very rational like ROI based analysis on what measures you should have at any given point. The simple idea then, lots of countries actually followed that strategy at the beginning, and that makes sense, but then they started misunderstanding it, and we had lockdowns for more than two years, which I think made sense, because the economic impact that this has is way above the benefit that it gives. And so, you end up in a position where, because human beings understand the problem, you don’t know what are the right solutions, and then, society suffers. And so, what I did for COVID is very much what I tried to do for each one of these other than this.
JS: Right. I want to blend your early career work with your current career work, so we’ve seen, because you’ve written a bit about blockchain, you’ve written a bit about AI, and I’m curious about the DataViz piece of, particularly, of maps, since that’s a focal point and AI, like, how do you see those two interacting in the next few years.
JS: Like, is AI going to make the challenge of making maps and doing geographic analysis easier, or is it going to be – are our misperceptions of geography going to feed into the AI and exacerbate the perceptual problem?
TP: Yeah, I think the current map representations are so much worse than they can be. I’ll give you an example. When you see a normal map, but first, usually, these are political maps, right? So they show states, nation states, but nation states are very recent; like, I think we have close to 200 countries now in the world, but 70 years ago, we had something like 53. Right? And then, if you go 200 years ago, there were only 12 nation states. And so, it’s super recent, super new, and yet, this is what we show. So that tells you another example of how map distorts our perception. Right? For me, one of the even better examples is mountains, like, relief topography maps show you a little bit where there’s planes and where there’s mountains, but they don’t tell you the key insight about planes and mountains, which is mountains are very fucking hard to climb. And so, for example, what is easier, to walk a 100 kilometers, or to climb one kilometer, like, hands down, walking 100 kilometers is easier. Right? But if you show to scale, it’s going to look like, oh, this mountain is tiny thing, it doesn’t matter. And so, you need to show exaggerated, extremely exaggerated altitude maps for a map to convey the key insight, which is not the altitude, it is the difficulty for humans.
TP: And so, this is an example of exaggerated topography maps are relatively recent, and now, like, there’s been an explosion over last few years. And this is an example where if you have an AI tool that can take a data point and display it more easily, then you can have substantial more creativity on how you can show them. So displaying existing data is one of the big, big, big areas for improvement, and the other one is joining data, like, 90% of the work of geographers is just like finding the right data and putting, clearly, but this is like trivial for an AI. And so, sites and AI that can put all this information in one place, easily accessible, and without knowing ArcGIS or any coding thing, any person can map anything, like, there’s going to be an explosion on maps and the insights that come with it. There’s going to be a lot of shit, but the 2% that are amazing, are going to be so much better than anything that we’ve seen before that I think map making is going to see massive, massive results.
JS: Yeah, that is an optimist – I like the optimistic take on it.
TP: As [inaudible 00:31:46].
JS: Do you have a favorite map of any topic, is there like a map that you like?
TP: Yeah, I think those exaggerated topography maps are my favorite. I think they’re just showing these mountains, and [inaudible 00:32:06] really, really gives you a core insight. So that’s one. There’s another one – in technology, there’s always this thing where when a new technology arrives, people just transpose the previous technology to the new one. Right? So, for example if you have cinema for 30 years after cinema, movies were mostly theatre recorded. Right? And then movies like Citizen Kane come around and completely reinvent storytelling based on the media. Something similar I think is happening with maps, because maps were on paper, they were mostly fixed. Right? And I don’t think a fixed map, a static map conveys most information. And I’ll give you an example, for me one of my favorite maps is an animated map that contrasts plains and mountains with population density. And so, if instead of having one or the other, right, so imagine the height, like the height on one side, like the plains, mountains, and the other one is where people live; and so, if you put them side by side, you’re not going to really be able to see the patterns easily, because your eyes need to go from one to the other, and it’s hard to compare. But if you put them one on top of the other, and you show and you take it off, you can very easily see, oh interesting, in temperate areas, there’s a perfect overlap between planes and people. And vice versa, in more equatorial areas, the overlap is on the mountainside.
JS: So what I like about that, the way you describe that is moving away, I guess, from your traditional, like, geographic map or Mercator projection or Robertson projection, but just rethinking how the geography is presented, just layering mountains and plains on top of each other and not worrying about what projection we use, just like, I don’t know, it’s just a different way of thinking about presenting geographic data rather than just like our traditional map.
TP: Yeah, and I think you’re beginning to conserve value, one of them is accuracy, and I think accuracy is very important, and I think we’re going to get even more accuracy in the future. There’s a reason why Mercator has actually been – is being used now too, it’s the one that makes the least holiday, this portion at the zoom-in, zoom-out level, right? So Google Maps use Mercator or used to, because you zoom in, you zoom out, it looks the same, locally, globally, and there’s no problem. Now, I don’t know if you noticed, but if you zoom out enough from Google Maps, then it starts becoming a globe, like, there’s a moment that if you zoom in, it’s playing, but it becomes a globe. And so, I think it’s kind of this type of disruptions we’re solving now, and it’s going to be even easier to solve through AI in the future; and then, once you – so that’s kind of the first, but I think the second there that makes me even more excited is just the insights – by coupling the information in different ways, we’re going to be able to see, to understand geography in a way that we didn’t before.
JS: Right. So before we wrap up, so on your Substack Uncharted Territories, what do you have in the works, like, what can people expect in the next few weeks, months, years as you do this?
TP: So I have, at any given point, I have around 100 to 150 drafts that I’m working on in parallel, so it’s pretty brutal. Right now, I’m still working on the series around the game theory of sex, so there’s a lot of things that come from it, like, for example, understanding slut shaming and body counts, so that why are we seeing problems there and what can we do about that. There’s topic about – there’s an area around real estate, for example, I have this hypothesis that real estate as an investment class is going to be substantially worse in the coming decades, than it was in the previous ones. There’s a question about the future of education. I think education is not at all what we think it is, and the future is going to be massively changed through AI. Questions around climate change, I think, climate change could already be solved right now, if the people who claim, who care about really did what they have to do about it. And so, understanding what are the incentives there, how we can solve it, how we can change the incentives, how many people should we have on Earth, do we have too many, can we have more, how is that linked to progress and economic development. So these are some of these, like, 50 whatever topics I’m…
JS: Just a few small, small topics.
TP: Small questions.
JS: Small questions. Well, Tomas, thanks so much for coming on the show. I’ll put links to your TED Talk, and to the Substack that everybody should check out. So thanks again for coming on the show, really appreciate it.
TP: Jon, I had a lot of fun, I really appreciate it, and thank you for your work.
Thanks to everyone, for tuning in to this week’s episode. I hope you enjoyed that. I hope you’ll check out the list of links that I put in the show notes, including some previous episodes of this podcast that I think are related to the conversation Tomas and I just had around inequality, around maps, and a variety of other topics. So until next time, this has been the PolicyViz podcast. Thanks so much for listening.
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