Episode 136 - What Are Martingales in Election Predictions?
Election predictions are not just about throwing random numbers on who is more likely to win. There are more factors to consider than what we see on the surface. How can we equally weigh the probabilities to come up with a sound prediction?
In this episode, Max discusses the probabilities in the previous and the upcoming presidential elections. He talks about why election predictions that veer too far off from 50% and have high variance over time carry little weight. We will also learn about the idea of a probability martingale.
Also, it’s been 25 years since the introduction of Windows 95. Why is that interesting and what does it say about the nature of human computer interaction and tech marketing?
Tune in to the episode if you’re interested to learn more about the process of election predictions and computer advancements!
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What is an election martingale?
Discover how launching and marketing operating systems have changed since the introduction of Windows 95.
How does the social dynamics in a pandemic and a terrorist attack differ?
Resources
David Salazar on the issues of election forecasting
HuffPost’s 2016 President Forecast by Natalie Jackson and Adam Hooper
Start Me Up: What Has the Windows 95 Desktop Given us 25 Years Later? by Jenny List
What Windows 95 Changed by Anil Dash
Related Episodes
Episode 90 on the problems with “Professor Prediction last 10 elections” claims
Episode 65 on one-off events
Episode 33 on Nassim Taleb’s criticism of Nate Silver’s election prediction variance
Episode 9 on Lindy’s Law
Episode Highlights
Variance Over Time
The issue with election predictions is the variance over time. If the percentage changes every next day, it calls into question the prediction's accuracy.
A recent Twitter thread by David Salazar spurred this topic, linking Nassim's book on elections and forecasts of events.
Election Predictions & Probability Theory
Max says that making predictions far away from 50% is not right when the election is this far out.
Thinking that there’s a time warp between now and the election is going to collapse the probability.
However, you can base today’s probability on tomorrow’s probability. You average them together to come up with today’s forecast and then wait for what happens tomorrow.
The Importance of Counterbalancing Probability
There must be a counterbalancing probability when you make an extreme prediction on one candidate.
Balancing the probability gets tougher the higher you go to 100% or lower to 0%.
You have to include the possibility that it could equally go up or down.
Having more probability available on the upside to balance that on the downside leads us to a 50% probability.
One-Off Presidential Elections
Not every election has a 50/50 probability. However, there is a higher chance for this for one-off presidential elections.
During presidential elections, third-party candidates don’t have an equal footing.
It is more likely for a major party candidate to drop out before the election than for a third-party candidate to win.
The Republican and Democrat two-party system has been around for 160 years. Using Lindy’s Law, this could last for another 60 years and can be disrupted after another 50 years.
The odds of a third-party winning for this election is less than one out of 100.
Martingale Election Predictions
All the types of predictions that are changing in time series are called a martingale.
The weighted average of your probability predictions for tomorrow is your probability prediction for today.
There are branches of calculus based on functions that change over time probabilistically.
Listen to the full episode for Max's explanation of why the 60% model argument didn't work in Huffington Post's 2016 election prediction.
Windows 95’s 25th Anniversary
It shows how technology and the phases of different platforms have evolved.
Windows marketed Windows 95 like a summer blockbuster movie.
While it was a successful OS, it was the cultural perception that marked this significant change.
A lot of the interface elements of Windows 95 such as the Start menu still exist today.
Public Imagination & Operating Systems
Windows 95 introduced PC users to the graphical interface as the primary way of computer interactions.
There was a backlash on Windows 8 because people were used to the way things were in the past Windows editions.
There’s a deep cultural momentum on operating system interfaces.
Apple had the chance to radically rethink the interface of the first iPhone’s new-form factor.
Introducing a platform is not just about building and marketing it. It’s more about getting into the public imagination and public habits.
9/11’s 19th Anniversary
The social dynamics during a pandemic and a terrorist attack are different because of the nature of the threat.
With 9/11, everybody was going through the same thing, and people relied on each other.
During the pandemic, people feel like the threat is coming from the other people around them.
Local Max Radio’s Call-In Shows
Max is starting a new format of call-in shows to allow community involvement in the podcast.
Listen to the episode for the full details on how you can participate in these call-in shows!
5 Powerful Quotes from This Episode
“Does this mean that every election is 50/50? The answer is certainly not. Not every election—just in these one-off presidential elections, where you have two cases that are very likely and you have many foreseeable possibilities of events that can switch it from one to the other. So it's very volatile.”
“A lot of this (professor prediction) is clickbait, and a lot of this is trying to get attention in this charged political environment.”
“These are very subtle arguments about probability, but they're very cool to wrap your head around them. And once you do, you kind of understand what's going on in the world, and you understand what people are trying to sell you in terms of predictive power.”
“I think there's a very deep cultural momentum now on operating system interfaces. It's like language; it has to gradually change.”
“People have tried to build other platform, but it's not just about trying to build it or marketing it or having people use it. It's really about what Windows 95 did and what the iPhone did, which was really in the public imagination and sort of in the public habits, get them used to using this form of computer–human interaction.”
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To expanding perspectives,
Max
Transcript
Max Sklar: You're listening to The Local Maximum Episode 136.
Time to expand your perspective. Welcome to The Local Maximum. Now here's your host, Max Sklar.
You've reached another Local Maximum. Welcome, everyone. Welcome. We've got another solo show today. So you're just gonna have me talking for a while. I'm going to talk about—let's talk a little bit more about election forecasts and some of the craziness around why the numbers go up and down and why some of these probabilities shouldn't. I'll get into it in a minute. And I'm going to talk about some of the history of technology a little bit—the operating systems, 25th anniversary of Windows 95. I know that might sound… Well, it's interesting. So hang on tight. We'll get to that.
We got a pretty cool sponsor for today. It's The Podcast Discovery Show, which is a podcast that helps you discover other podcasts—very meta, very meta-podcast. I think it's a great idea. It's The Podcast Discovery Show. So we'll talk about that a little later.
First, I wanted to update you on the election predictions—and not my election prediction. I'm not gonna try to predict the election today. But I want to talk about what we've been saying about probability in this case. So if you go all the way back on the Local Maximum to Episode 33, we saw that kind of Twitter fight between Nassim Taleb and Nate Silver about Nate Silver's election predictions. And I think the issue with his election predictions—or a lot of the election predictions that are out there—is the variance over time. So you know, one day it'll be 70% so and so wins. The next day, it'll be 60%, then up to 80%, then down to 50%. And all that variance is sort of a problem; it sort of calls into question the accuracy of the prediction itself. Now, I think that Nate Silver's final prediction for the election in 2016 was that Hillary Clinton has a 70% chance of winning, and Donald Trump has a 30% chance. Of that, in of itself, is actually not so bad because, you know, 30% things happen all the time. I do think it is bad, the ones that said 92%, but I'll get into that in a minute.
So now, we're talking about the election predictions for the election of 2020. And this was spurred by a tweet from David Salazar, who was linking to Nassim Taleb’s book in Chapter 12 on elections and on, essentially, forecasts of events, you know, binary events, yes or no, over time. So it's sort of a time series, and you kind of update your prediction every day. I'm not going to get into the technical details of that because they're kind of very complicated. Maybe I'll get into few of the technical details, but I just want to tell you why making predictions far away from 50% are tough and are probably not right when the election is this far out. So there is a really good graphic that he has where it's like, “Here's what the actual predictions look like,” and the graph is going up and down and up and down, and then, “Here's what it should look like,” where it's kind of, you know, it's going up and down a little bit, but it's very close to 50%, either way—Republican or Democrat—and then it sort of flips at the end. You know, a few days before the election, it should—you can make a bolder prediction. So we'll talk about why that is.
So, one way to think about this is you can't predict events that occur between now and the election. You know, how many events have already occurred in the year 2020 that were completely unanticipated to you or a lot of people—this year probably has more than most. So, you know, a lot of the events over the next two months are also going to be completely unanticipated. So, and they could move things in either direction, which makes it really hard, again, to predict. In terms of probability theory, often when we hear, “Oh, there's a 70% chance Biden is going to win,” we're thinking that there's kind of a time warp between now and the election, and then a way to die off 70% is going to be thrown, and then boom, it's going to collapse the wave function; it's going to collapse the probability. There's a 70% chance it's going to go to Biden, and there's a 30% chance is going to go to Trump if we timewarp from now to the election. But actually, there are a lot of steps between now and the election, and what you can really do is you can base today's probability on tomorrow's probability.
So let me give you an example. This is sort of, you got to think about this. Let’s do a little thought experiment. Let's suppose I ask you, “What is the probability forecast going to be tomorrow?” That's a really interesting question because now you're thinking probabilistically about what probability I'm going to forecast tomorrow. So let's say this is what I say. Let's say, “Well, there's a ⅓ chance, I'm going to say Biden is 60%, and there's a ⅓ chance, I'm going to say Biden is 55% chance, and there's another ⅓ chance that it's going to be 50/50. So now, you could use that to come up with today's prediction. So you average all of that together, and you average 60, 55, and 50, they're all equally likely. You average them together, and that makes today's forecast 55%, and then you wait for tomorrow, and you see what happens.
So that means that if we're going to make an extreme prediction, say 90% on one candidate today, that means the probability that'll be higher tomorrow has to balance out the probability that it's going to be lower tomorrow. And that gets tougher to do, the higher and higher you go to 100% and the lower and lower you go to 0%. Because even if you think there's a small chance something could happen tomorrow that push, let's say you're at 90, and I say, “Well, could something happen tomorrow? Is there a nonzero chance that something happens tomorrow that pushes your prediction down to 70?” And you say, “Sure, sure. Something could happen tomorrow to push my prediction down to 70.” Then you need kind of a counter-balancing probability, say a possibility it's going to go up to 95%. That sort of balances the probability that goes down to 70%, all else being equal. And going up to 95 has to be—that's only a 5% difference—but going from 90 to 70 is a 20% difference. So the chance that it clicks up to 95 and stays there is going to have to be way more likely—it’s going to be four times as likely—to balance it out.
So that means that kind of a 90% prediction should be really hard to make this far out because you have to include the possibility that it could go up and it could go down in equal amounts and—not equal amounts, but you know, weighted equally—and it’s you're too close to 100%; there's not too much room to go up. And so then you have an argument, “Well, if 90% is unlikely, that means that 85% is unlikely because from 85, I'm not going to go to 90 because I don't want to say, I just said I don't want to say 90 this far out. And so if 85 is no good, then 80 is no good,” and so on and so forth. So with each step of the argument, you go down 80, 75, 70. Each step of the argument is getting weaker and weaker because at each step you make in that chain, you end up with more room to go up, and then you say, “Okay. Well, now, we have more probability available on the upside to balance the possibility on the downside,” and so that means that the probability is closer to 50% are more okay. And so this sort of pushes the prediction towards 50%. The people who are 100% or at high end, you want to go down; the people are low, and you want to go up.
So you can actually kind of see this if you look at the betting markets, if you look at PredictIt, for example, on Biden and Trump, it has them definitely less than 60/40. I think it's actually not even a very efficient market because it's 44/59, so it adds up to 103%—103%. But, let's just say it has Trump at 42% and Biden at 58%. So that's, yeah, that's about as extreme as you're going to want to be in this case. So yeah, that's very interesting. And I also think that it probably should be closer to 50/50 just in terms of my notion of probability. Feel free to bet, however you want. I feel like if you go through 100 of these elections—100 of these one-off elections—and you bet on each one, and you always bet on the one that's cheaper, the one that's lower this far out at two months out, you'd probably come out ahead in 100 elections, but it will take 400 years. So good luck with that. So alright, does this mean that every election is 50/50? The answer is certainly not—not every election—just in these one-off presidential elections, where you have two cases that are very likely, and you have many foreseeable possibilities of events that can switch it from one to the other. So it's very volatile.
So, for example, in my congressional district, I'm gonna say that the odds are overwhelming that Carolyn Maloney, the Democrat, wins. She's won many elections in the past. And maybe put it at 95% because crazy things do happen, and congressional races are repeatable, so we do see, occasionally, crazy things happen, but probably not. Probably not in this case, but we could test out, you know, what the actual probability of crazy things happening in these safe seats are. And note also, in the presidential election, we don't put these third party candidates on equal footing. So it's more likely that even if one of the major party candidates drops out before the election—which is more likely than a third-party candidate winning—it's more likely that the major party would replace their candidate with someone else, then a third party winning in the US, at least for this election. So you know, the probability of it happening sometime in the next hundred years is much higher because, again, on that time scale, you could have electoral dynamics taking place that, you know, that throw into question everything we know about US politics.
I mean, the two-party system, Republican and Democrat, is about 160 years old. So using Lindy's Law, we could say maybe it lasts another hundred 60 years. So okay, another 50 years, there's a good chance that it will be disrupted. So, at this election, for third party winning, I put the odds at like less than 1 out of 1000. It's, you know, the possibility of that happening is extremely low, but that's not what I'd put it at the election of 2048, for example, and, you know, that's not even what I'd put it at the election of 2024, the next one because so much can happen in the next four years. I mean, you could probably think of cases where another party would be formed. It's not terribly likely, but it's way more likely than I think, 1 in 1000.
So, alright. Presidential elections are sort of they're one-offs. We talked about this in Episode 90 with a professor who claims to predict every election until since like 1984. And again, that's not terribly… Well, there are a few problems with that. First of all, that's not a huge sample size. Some of these elections are a lot easier to predict than 50/50, so it's not like just getting eight coin flips in a row, right? And you kind of want to look at did they change their model over time? And, you know, did they handwave all the election of 2000s? You know, was close enough that I don't really count my prediction for Gore.
So, you know, there's all these exceptions, and so, you see a lot of these clickbaity articles come out. I think that particular professor thought, you know, Trump was going to lose; Biden wasn't the nominee at the time. I've seen one on the Trump side on the Trumpaverse, everyone trying to play up Trump saying, “Oh, this guy predicted the last ten elections, and he says that Trump has a 90% chance of winning.” I think it was based on the turnout of the primary. I just think that's crazy. I think that you can't do that. Obviously, someone's going to win. And so in the end, but I feel that, again, a lot of this is clickbait, and a lot of this is trying to get attention in this charged political environment. So that professor who claims to predict the election—nonsense—and talked about in Episode 90. In Episode 65, we talked about how you can predict unprecedented events—even though a presidential election is not entirely unprecedented—but you could check that one out as well.
So that's really all I want to say about the ele… Oh, one more thing to say about the election predictions, just a little technical note, is that these types of predictions that are updated over time and changing in time series like this, it's called a martingale. And the reason—that's kind of an interesting term—and the reason why it's called a martingale is because your possibilities of probability predictions for tomorrow, their weighted average is your probability prediction for today. So it's sort of, these martingales are kind of used to predict things like the—like does not predict the stock market—I wouldn't say predict the stock market. But to model the stock market, where, say the price of a stock today is the kind of the weighted sum of the community's probabilities over what could be the prices tomorrow and that kind of makes sense when you work your way backwards and try to price this thing.
And so there's whole branches of calculus that are based on functions that kind of change over time, but they change probabilistically. Like usually, when we talk about differential equations, it's deterministic. Like if I start here, and I'm using this differential equation, it's going to draft out this particular curve. But there's something called Itô calculus, where there are probabilities in terms of where the curves is going to go. And so, you can use some scheme to like rank curves in terms of which are more probable than others. It's something that I haven't done a whole lot of modeling on, but I would be very interested in trying that out.
So, again, we're gonna get more concrete with the presidential elections in the future. I hope you learn something from that. And, you know, I'm hoping to have Alex Andorra back on to talk about, you know, what we get from polls or answers in the polls, actually, how people are going to vote, are we very good? You know, it seems like there's a lot of questions about whether these polls are accurate or not, and so I want to ask them about like, what can go wrong, and is there something that can go wrong this year that we can't otherwise go wrong? So I hope to learn a lot from that, and I'm looking forward to it.
One more thing—I know, I keep saying one more thing—I have to come back to, I think it was the Huffington Post. And let me type this out: Huffington Post 2016 election prediction, just to make sure. New York Times maybe, too. Okay, I think, they had Clinton at 98%. That's weird. I think some places hadn't had her at 90%. And I think you could make the same argument, a similar argument that we made before as to why those are not competent predictions. Because, when you look at Nate Silver's prediction, and even though he could be criticized for having all this variance that doesn't make any sense, let's say that 70% prediction at the end, there's a good percent, that's like—let's just say that's valid. Well, if I have a 90% prediction, when I ask the person saying 90%—maybe don't ask them, “Hey, you think Trump is right that he can win?” Don't ask them that. Say, “Hey, look. Is there a possibility that Nate Silver's 70% prediction is a good, accurate prediction or a good, like a competent valid prediction?” And the person who predict 90% might say, “Yeah, sure. There's a chance that I'm wrong and Nate Silver's right.” Well, in that case, they have to have a possibility that there's a much higher model out there that is even more likely to be right, like a 95% model. So that's why the kind of 90% model argument didn't work in that environment.
So I hope I'm explaining this right. These are sort of, these are very subtle arguments about probability, but they're very cool to wrap your head around them. And once you do, you kind of understand what's going on in the world, and you understand what people are trying to sell you in terms of predictive power. Alright.
So before we get to the rest of the podcast today, I want to talk about The Podcast Discovery Show. There are 30 million podcasts available, and it is a daunting task to find new shows. But The Podcast Discovery Show talks about a new show, a new podcast on each episode, which makes discovering them easier and easier. I’m looking through some of their old episodes. You can use it to discover other tech podcasts like this one or podcasts about science or current events or really anything. And on the other discovery show on their feed, they talk about all the other discoveries they make throughout the week—food, science, history, art—and they're always searching for new incredible things to learn. Take finding your new favorite show into your own hands and engage in new and amazing shows from large shows to independent shows that you would never be able to find. Hey, this show, Local Maximum, is an independent show, so you must be into that. I look at some of the, some small ones in my rotation; I have some bigger ones in rotation. Already, The Podcast Discovery Show has discovered and discussed over 200 podcasts, and this number is only going to grow. Explore the world of podcasts with The Podcast Discovery Show, and remember: there is always more to discover. Alright, now back to this podcast, the Local Maximum.
Alright, one month ago was the 25th anniversary of the launch of Windows 95. And I thought I wasn't sure if I was going to talk about this. I was like, “Well, you know, no one really cares. Why is this such a big deal?” But you know, back then, it was a big deal, and I think that talking about this shows the evolution of technology and the different phases that we've gone through of the different platforms. So, you know, we don't make a huge deal of operating system launches anymore. I know that. You know, look, Apple launches iOS, a new iPhone operating system every year. And yes, we kind of have to pay attention to it in Foursquare because whatever they do, you know, we might have to update our Foursquare apps, but everyone's like, “Oh, cool. I can, there's a new swipey feature now,” or something like that. “So that wasn't there before.” New or night mode or something like that, but it's not a big deal. And also, you know, they don't have to drum up excitement for everyone to go out and buy it; it kind of automatically goes in everybody's phone. Windows—Windows doesn't even come out anymore. I mean, there's Windows 10, and now they're saying, “Well, we're just going to keep updating Windows 10, and we're not going to have these big launches anymore like we used to.”
So there are a couple articles on this that I wanted to fit in and talk about, and I want to talk about like my experiences. So this is from Anil Dash on his podcast. He's pretty good. He's an interesting technology commentator. He says:
“For context, when Windows 95 was released in August of 1995, only about 30% of American homes had any computer at all. Less than 10% had any form of internet access—and virtually none had broadband. There were no smartphones, of course.
But more broadly, computers and software were basically not yet something one talked about in polite company. You might have had a friend who “worked in computers” (we didn’t say “work in tech” yet) or call IT for support for your printer at work.” I mean, until 2020, you still have to call IT for your printer at work.
“But software was not part of culture, and the term "apps" wouldn't come into wide usage for more than another decade. In those days, most job listings didn’t even yet ask for “familiarity with MS Office” (ask your parents what that meant).” Yeah, you know, familiarity with Excel, things like that. “And the PlayStation hadn’t been released yet in the U.S. or Europe.”
So, in other words, like, when Windows 95 came out, they marketed this thing like a movie, like some of these like really splashy commercials that you wouldn't see now for an operating system—kind of like a summer blockbuster or something that everyone should be excited to use. You know, “Hey, look, you could use the,” you know, “Look at all the software that's coming out for kids, all these games, all these productivity tools,” things like that. So, Anil Dash argues that while—it ultimately argues for about the legacy of Windows 95—he argues that while it was a successful product and a great operating system, it was really the cultural perception that marked the big change. It was like, “Oh, everybody should be involved in this. Everybody should look into Windows 95 just like everybody should check out the summer blockbuster movies.”
So I remember even back then, you know, people would ask, “Hey, did you get it yet? Did you get Windows 95? Did you try Windows 95?” You know, “Did you have Windows 95? Is it really that good? Is it really as good as they say?” And so, it was always in comparison with Windows 3.1. So that's the kind of the first one that I remember where it was really, it was DOS; it was really the command line. You're always focused on the command line, and it was like, “Ah, today, maybe I'll start up Windows. She type in Windows, and then you wait 5, 10 minutes, and Windows comes on, and then you can click around and do a few things. But Windows was just one program of many; now, it is front and center—the main thing. So we don't, again, we don't talk about operating systems like that right now.
Another great article that I'm going to link on localmaxradio.com/136 is from Jenny List on Hackaday, who did a technical evaluation of Windows 95. It’s some very interesting things after 25, so she makes the point that after 25 years, maybe we could be a little bit more unbiased about what was going on. Interestingly, like some interface elements survive today. For example, the ‘Start menu’, and you know, the ‘Start menu’ even has kind of analogs on the Mac and Linux operating systems to an extent. So a lot of things they introduced are still around, which is very impressive that the design elements stayed for 25 years, we don't even think about anymore. We're like, you know, fish noticing water or something.
So what did people get out of this operating system that they didn't get out of it before? My impression was that, first, it introduced PC users, essentially non-Mac users, to the graphical interface as the primary way of interacting with the machine as opposed to the command line. Obviously, this was being done by the Mac. Before that, it was done by the Macintosh. But I think this was probably marks the flipping point in the public imagination, and you know, some people, Apple fans, would say, “Hey, they kind of ripped off Apple a little bit.” Maybe that's true, but they kind of took it to the masses. And I think Apple came back in the next decade and with a roar and really, really dominated this stuff later. So I also think that the basic layout, look, feel interface has stuck for 25 years, which is very, very impressive, as I said, even when they tried to radically change things for Windows 8. They were like, “Hey, it's been,” I don't know when Windows 8 came out five years ago, “It's been 20 years. Maybe it's time that we radically changed the interface because what's the chance that the interface we designed 20 years ago, is still—obviously we had some changes—but it's still the most optimal way of doing it today. So let's think about this from scratch.”
And so they launched Windows 8, and I don't think it was a bad operating system. Some people say, you know, people hate Windows Vista. Windows 8, I don't think was bad, but there was kind of a backlash to that because, you know, people liked the way things were, and people were used to the way things were. And so things kind of returned to form in Windows 10. I think there's a very deep cultural momentum now on operating system interfaces, and it's like language; it has to gradually change. But people can't just decide, “Okay, we're going to change all the rules.” So when you start something new like this, you know, a lot of decisions you make early on kind of get stuck.
Another interesting point is that the launch of the first iPhone was 12 years later. And with the launch of the iPhone, they were able to kind of radically rethink the interface because it was entirely new form factor. So we're kind of about halfway between—the iPhone launch is about halfway between the launch of Windows 95 in today. So maybe we're due for another user interface revolution, and whether it's voice or glasses—some have said back to text, you know, back to command line. You know, now you're texting to machines with bots. But I don't know, it's a very interesting thing to think about. I'm pretty sure that we'll see… Well, people have tried to build other platform, but it's not just about trying to build it or marketing it or having people use it; it's really about what Windows 95 did and what the iPhone did, which was really in the public imagination and sort of in the public habits, get them used to using this form of computer-human interaction.
So that's my take on that. If you have anything to weigh in or your story about it, go to localmaxradio.com. Well, or go to Local Max or email me at localmaxradio@gmail.com if you'd like to weigh in.
Finally, another anniversary that I want to talk about is the anniversary of 9/11. And, you know, I haven't… I've been doing the show for three years, and I don't think I've mentioned other anniversaries for 9/11. It seems kind of strange to talk about it on the 19 year anniversary instead of 20, but, you know, on the day last week, I was down at the memorial—or “ground zero” as we used to call it on 9/11 in the weeks after—as I usually do, but there were more people down there than ever even during with the pandemic. And sometimes I went, and there really weren't a lot of people some years. I think that people really want something that they can rally behind.
You know, why is it so much more difficult to rally around each other and support each other during a pandemic than it is during a terrorist attack? And you know, my fa… I was thinking about this, and some people think, “Oh, it's just the times. People hate each other now, and that wasn't true then.” And okay, maybe that's true to an extent, but I also think it has to do with the nature of the threat. I think that when 9/11 happened, everybody was going through the same thing. Everybody was upset, and really, it was like if something happens, you relied on the people around you to save you from that threat or, you know, you kind of band together and work together.
Well, in those situations, you know, you heard about the people on the Flight 93 who took down the plane, or you hear stories of firemen going into the buildings on 9/11 and getting people out, and in some cases is, perishing as they did do that. So I feel like there's got to be a sense of community in that sort of thing. But man, this pandemic, as there has been other disasters in New York—you know, certainly Hurricane Sandy and things like that, people helped each other—this one is different. I feel like in the pandemic, it's like, “Where's the threat coming from?” It's people feel like the threat is coming from the other people around them. And so, that really changes the social dynamic among people, which is really sad. And I don't know, hopefully, we can undo that as time goes on. I think there's some very promising numbers from the pandemic right now that things are coming to an end, but we'll see.
Alright. So a couple of interesting shows coming up. As I said, next month, I'm going to talk to Alex Andorra. I have a call-in show coming soon. Oh, this is a new thing that I'm doing that's interesting. I'm going to do call-in shows, where if you want to call into the Local Maximum, let me know, localmaxradio@gmail.com, and it's very simple. Just tell me a thought about something that you had, and then I'll talk to you about it for2, 5, 10 minutes. Very simple conversation, very easy to sort, and you know, this way I don't have to book you as a guest. It would just be like a very quick conversation; you could promote something too, if you want. And then they'll ask you some questions about it. Then I'll put it together into a call-in show. So it's a brand new format that I want to allow community involvement here on the Local Maximum. I have my first call-in show coming soon. I'm not sure if I'll do it next week or the week after, depending if I get another caller, but already have some calls done, and I'm looking forward to experimenting with this new format. I know we've had a stretch without guests, but we have a pretty great lineup for October. I think I've got a topologist coming on to talk more about topology. I'm looking forward to that. Have a great week, everyone.
That's the show. Remember to check out the website at localmaxradio.com. If you want to contact me, the host, or ask a question that I can answer on the show, send an email to localmaxradio@gmail.com. The show is available on iTunes, SoundCloud, Stitcher, and more. If you want to keep up, remember to subscribe to the local maximum on one of these platforms and to follow my Twitter account @maxsklar. Have a great week.
