1 00:00:01,120 --> 00:00:04,280 Speaker 1: Welcome to you Stuff you Should Know from House Stuff 2 00:00:04,320 --> 00:00:12,600 Speaker 1: Works dot com. Hey, and welcome to the podcast. I'm 3 00:00:12,680 --> 00:00:15,800 Speaker 1: Josh Clark, and there's Charles Stuff. Chuck Bryant is the 4 00:00:15,880 --> 00:00:22,239 Speaker 1: Stuff you Should Know podcast. Jerry's over there. Uh, it's 5 00:00:22,280 --> 00:00:26,640 Speaker 1: pretty much the norm. Yep, yep. How you doing man? 6 00:00:26,680 --> 00:00:29,840 Speaker 1: How you feeling? It is a little rough, sir? Are 7 00:00:29,880 --> 00:00:33,520 Speaker 1: you you'll make it through? What? Yeah? Yesterday we celebrated 8 00:00:33,560 --> 00:00:38,639 Speaker 1: the the the beginnings of Gin and Tonic season. It's 9 00:00:38,680 --> 00:00:40,920 Speaker 1: definitely that kind of weather for sure. Yeah, it's hard 10 00:00:40,960 --> 00:00:43,599 Speaker 1: to not sit on the deck and have a citrusy, 11 00:00:43,680 --> 00:00:46,760 Speaker 1: delightful drink. Nice going. So I'm just a little sleepy, 12 00:00:46,760 --> 00:00:48,720 Speaker 1: but I'm feeling good. I feel like this topic is 13 00:00:50,320 --> 00:00:53,720 Speaker 1: is all about being sort of down in the dumps 14 00:00:53,760 --> 00:00:56,600 Speaker 1: a little bill. It depends, it depends on where you land, 15 00:00:56,720 --> 00:00:59,200 Speaker 1: and you just place yourself pretty squarely in the gloom 16 00:00:59,240 --> 00:01:02,000 Speaker 1: and doom camp. My friend. No, I'm actually not in 17 00:01:02,040 --> 00:01:03,920 Speaker 1: the doom and gloom camp. I was about to say, which, 18 00:01:03,920 --> 00:01:06,880 Speaker 1: if I remember correctly, in our episode, was Malthus right 19 00:01:06,959 --> 00:01:11,520 Speaker 1: about carrying capacity? You overtly said that you are a 20 00:01:11,520 --> 00:01:19,200 Speaker 1: an optimist. That's right, not Mauthusian uh naysayer. You know, yeah, 21 00:01:19,240 --> 00:01:21,080 Speaker 1: I forgot about that one. We've touched on this a 22 00:01:21,120 --> 00:01:23,920 Speaker 1: few times. We talked about we did a whole profile 23 00:01:23,959 --> 00:01:27,600 Speaker 1: and Norman Borlog alone on our very short lived and 24 00:01:27,680 --> 00:01:31,960 Speaker 1: reasonably so UM live webcast. Do you remember we did 25 00:01:31,959 --> 00:01:36,199 Speaker 1: basically a book report on Norman Borlog. Yeah, he was, um, well, 26 00:01:36,440 --> 00:01:39,320 Speaker 1: I think he's even controversial. He is very much So 27 00:01:39,560 --> 00:01:42,399 Speaker 1: you know, you win a Nobel Prize but for saving 28 00:01:42,400 --> 00:01:45,840 Speaker 1: a billion lives. Yeah, but still people are gonna put you. 29 00:01:45,840 --> 00:01:50,600 Speaker 1: You get interesting stuff. So um, if you don't know 30 00:01:50,600 --> 00:01:52,800 Speaker 1: what we're talking about, should probably press pause, go listen 31 00:01:52,840 --> 00:01:57,360 Speaker 1: to the Malthus episode, Go to stuff you should know 32 00:01:57,440 --> 00:02:02,320 Speaker 1: dot com slash podcast, I think it's plural slash archive. 33 00:02:02,920 --> 00:02:06,120 Speaker 1: Make that your homepage and all seven hundred and change 34 00:02:06,120 --> 00:02:09,280 Speaker 1: episodes are there, and then do control f is everybody 35 00:02:09,280 --> 00:02:11,760 Speaker 1: doing this so far? And then type of mouths m 36 00:02:11,760 --> 00:02:16,080 Speaker 1: A L th h U S. It's gonna highlight that link, 37 00:02:16,600 --> 00:02:20,440 Speaker 1: click that and press play and then come back to us. 38 00:02:20,639 --> 00:02:25,480 Speaker 1: That's right, we'll wait boom. So so we're back an hour. 39 00:02:26,440 --> 00:02:29,600 Speaker 1: We we're talking about is carrying capacity in part, but 40 00:02:29,680 --> 00:02:33,360 Speaker 1: carrying capacity checkers is just kind of a it's a 41 00:02:33,400 --> 00:02:37,239 Speaker 1: reflection of a larger issue, and that larger issues population 42 00:02:37,760 --> 00:02:41,359 Speaker 1: specifically overpopulation, and is that a thing or not is 43 00:02:41,560 --> 00:02:44,040 Speaker 1: a big question, because I mean, at any given point 44 00:02:44,040 --> 00:02:47,400 Speaker 1: in time, you know, they have, like the the CIA 45 00:02:47,480 --> 00:02:50,840 Speaker 1: World back book has you know, a pretty good assessment 46 00:02:50,840 --> 00:02:53,519 Speaker 1: of how many people are alive. It's a total guess. 47 00:02:53,520 --> 00:02:56,160 Speaker 1: It's a total estimate. We could be at ten billion 48 00:02:56,280 --> 00:02:58,120 Speaker 1: right now, we could be at a hundred million, and 49 00:02:58,160 --> 00:03:01,480 Speaker 1: everybody just is really terrible accounting. The point is we 50 00:03:01,639 --> 00:03:06,440 Speaker 1: don't specifically know. It's it's probably pretty accurate, but it's 51 00:03:06,440 --> 00:03:09,800 Speaker 1: still a guess. The point isn't to shoot holes in 52 00:03:09,840 --> 00:03:13,400 Speaker 1: the estimates of how many people are alive on the planet. 53 00:03:13,720 --> 00:03:16,120 Speaker 1: It's to point out that, like, there's so many people 54 00:03:16,440 --> 00:03:19,240 Speaker 1: we don't know and we can't possibly know at any 55 00:03:19,240 --> 00:03:21,680 Speaker 1: given point in time. And that has led a lot 56 00:03:21,680 --> 00:03:24,600 Speaker 1: of people to say, well, wait a minute. There's this 57 00:03:24,639 --> 00:03:27,960 Speaker 1: thing called carrying capacity, which is the Earth's ability to 58 00:03:28,040 --> 00:03:32,880 Speaker 1: support and sustain us humans and really any any creatures. 59 00:03:32,919 --> 00:03:35,520 Speaker 1: But really we're just kind of concerned with us humans 60 00:03:35,560 --> 00:03:42,680 Speaker 1: at this moment um and right and sustainably those two 61 00:03:42,720 --> 00:03:45,240 Speaker 1: factors have to be met or else you're putting a 62 00:03:45,280 --> 00:03:49,320 Speaker 1: tremendous amount of stress on Earth, and you're eventually bringing 63 00:03:49,320 --> 00:03:51,720 Speaker 1: about your own demise. So a lot of people are 64 00:03:51,720 --> 00:03:54,880 Speaker 1: saying like, uh, we're probably past carrying capacity and we 65 00:03:54,920 --> 00:03:58,080 Speaker 1: just don't know it yet. Or other people are saying, 66 00:03:58,240 --> 00:04:00,880 Speaker 1: there's really no such thing as carrying capacity city. Thanks 67 00:04:00,880 --> 00:04:04,040 Speaker 1: to human ingenuity, anytime we come up against it, we'll 68 00:04:04,120 --> 00:04:06,480 Speaker 1: figure out a way around it. And Norman Borlog was 69 00:04:06,480 --> 00:04:09,600 Speaker 1: a way to go. But before Borlog really became famous, 70 00:04:09,880 --> 00:04:13,680 Speaker 1: there was a lot of people who were legitimately concerned 71 00:04:14,040 --> 00:04:17,440 Speaker 1: that we were all going to die. Yeah Borlog, Um, 72 00:04:17,480 --> 00:04:19,480 Speaker 1: I don't if you haven't listened to that one, if 73 00:04:19,480 --> 00:04:23,760 Speaker 1: you didn't follow Josh's instructions like a good little podcast listener. Uh. 74 00:04:23,760 --> 00:04:26,560 Speaker 1: He was the um, one of the leaders of the 75 00:04:26,600 --> 00:04:29,919 Speaker 1: Green Revolution in the sixties and seventies, in which we 76 00:04:30,080 --> 00:04:35,760 Speaker 1: made great advances in agricultural Uh than agriculture in yields. Yeah, 77 00:04:35,839 --> 00:04:38,520 Speaker 1: new new types of wheat in Mexico, new types of 78 00:04:38,600 --> 00:04:42,440 Speaker 1: rice in India that um yielded much much more than 79 00:04:42,480 --> 00:04:45,680 Speaker 1: they ever had. And and plus they were drought resistant, 80 00:04:45,680 --> 00:04:49,320 Speaker 1: flood resistant. They could stand up and and hold more grain. 81 00:04:49,560 --> 00:04:52,640 Speaker 1: They could stand up and say Hello. They basically they 82 00:04:52,640 --> 00:04:56,920 Speaker 1: could pick the day daily double at high Laia. So, uh, 83 00:04:57,120 --> 00:05:02,360 Speaker 1: Borlog was, you know, by all standards, a very smart guy. 84 00:05:02,600 --> 00:05:05,880 Speaker 1: He cared very much about the people. He wasn't doing 85 00:05:05,880 --> 00:05:07,840 Speaker 1: it for fame or riches or anything like that. Like 86 00:05:07,839 --> 00:05:10,080 Speaker 1: this guy felt like he was working against the clock. 87 00:05:10,560 --> 00:05:12,520 Speaker 1: And if he didn't and he wasn't the only one 88 00:05:12,560 --> 00:05:16,480 Speaker 1: doing this, yeah he's the most famous. Um, but if 89 00:05:16,520 --> 00:05:18,480 Speaker 1: he didn't do it, then yeah, a lot of people 90 00:05:18,520 --> 00:05:20,880 Speaker 1: were going to starve. Yeah. And I think, um, I 91 00:05:21,000 --> 00:05:23,000 Speaker 1: proposed to you before this that we do just one 92 00:05:23,000 --> 00:05:25,920 Speaker 1: on the Green Revolution. Uh and I think that would 93 00:05:25,920 --> 00:05:30,320 Speaker 1: be a one to three podcast, sweet one. I love 94 00:05:30,360 --> 00:05:33,920 Speaker 1: this stuff. Psychology population That was another one we did too, 95 00:05:34,000 --> 00:05:37,119 Speaker 1: was how population works. And it sounds so like eye 96 00:05:37,120 --> 00:05:40,800 Speaker 1: bleedingly boring, but it turned out to be really interesting stuff. 97 00:05:40,800 --> 00:05:42,919 Speaker 1: So go go read that too. Well we'll wait, go ahead, 98 00:05:44,600 --> 00:05:49,800 Speaker 1: and we're back and it's yeah, and everybody's a little nervous. 99 00:05:49,839 --> 00:05:55,479 Speaker 1: Everyone is nervous. And uh Stanford biology professor Paul airlic Um, 100 00:05:55,520 --> 00:05:58,400 Speaker 1: there's another famous Paul air Like this is Paul are 101 00:05:58,600 --> 00:06:01,400 Speaker 1: airlic I believe, Oh it's a different one. Well, there's 102 00:06:01,440 --> 00:06:04,599 Speaker 1: two dudes, I did not realize that. What do you mean, 103 00:06:05,080 --> 00:06:07,800 Speaker 1: I mean, I'm familiar with the other Airic. Then I guess, well, 104 00:06:07,839 --> 00:06:10,280 Speaker 1: who was the other one? Again? He wrote, um, some 105 00:06:10,360 --> 00:06:12,960 Speaker 1: other famous books. He's a biologist. I think it's it's 106 00:06:12,960 --> 00:06:15,800 Speaker 1: not the same guy. Yeah, the other guy was a 107 00:06:15,880 --> 00:06:23,520 Speaker 1: German physician, uh who worked in chemotherapy immunology. Oh yeah, 108 00:06:23,520 --> 00:06:26,520 Speaker 1: that's not thinking of different guy. So this guy he 109 00:06:26,560 --> 00:06:29,320 Speaker 1: wrote other things besides the Population Bomb. Yeah. So in 110 00:06:29,400 --> 00:06:32,680 Speaker 1: nineteen six eight he writes, the population bomb goes on 111 00:06:32,720 --> 00:06:36,320 Speaker 1: the Tonight Show, it explodes, is huge hit. Apparently he 112 00:06:36,360 --> 00:06:38,839 Speaker 1: was on more than once. Yeah, and everyone got super 113 00:06:38,839 --> 00:06:42,320 Speaker 1: nervous because his book started with these words. The battle 114 00:06:42,400 --> 00:06:44,960 Speaker 1: that he had all the humanity is over in the 115 00:06:45,040 --> 00:06:48,480 Speaker 1: nineteen seventies, the world where under will undergo famines. Hundreds 116 00:06:48,520 --> 00:06:50,400 Speaker 1: of millions of people are going to starve to death 117 00:06:50,720 --> 00:06:53,520 Speaker 1: in spite of any crash programs embarked upon. Now that's 118 00:06:53,520 --> 00:06:55,320 Speaker 1: not so good. That's how he starts his book. He 119 00:06:55,400 --> 00:07:00,120 Speaker 1: basically says there's gonna be a Malthusian collapse. Um. At 120 00:07:00,120 --> 00:07:01,760 Speaker 1: one point in the book, he said, if I was 121 00:07:01,760 --> 00:07:04,000 Speaker 1: a betting man, I would wager by the year two thousand, 122 00:07:04,040 --> 00:07:08,960 Speaker 1: England won't be around boom. He drops the mic um 123 00:07:09,000 --> 00:07:12,320 Speaker 1: and we should probably mention who mouth says Thomas. Malthus 124 00:07:12,440 --> 00:07:17,720 Speaker 1: was a very forward thinking, smart, mathematically inclined minister, I 125 00:07:17,760 --> 00:07:23,200 Speaker 1: believe in the early nineteenth century, late eighteenth century, an economist, 126 00:07:23,440 --> 00:07:25,680 Speaker 1: and he was the one who said, we have a 127 00:07:25,720 --> 00:07:30,600 Speaker 1: problem here everyone. I've just done the math. And population 128 00:07:30,680 --> 00:07:35,760 Speaker 1: grows exponentially, but our food supply grows linearly, and so 129 00:07:35,880 --> 00:07:38,440 Speaker 1: we are destined to outgrow our food supply. And that's 130 00:07:38,440 --> 00:07:41,560 Speaker 1: where the idea of carrying capacity came from. So Malthis 131 00:07:41,600 --> 00:07:45,600 Speaker 1: and Malthusians um are the people who think like we're 132 00:07:45,640 --> 00:07:49,080 Speaker 1: going to exceed the food supply eventually and die from famines. 133 00:07:49,280 --> 00:07:52,360 Speaker 1: And Erlic was one of the most vocal and alarmist 134 00:07:52,480 --> 00:07:56,760 Speaker 1: neo Malthusians around. Yes, absolutely, and he scared the pants 135 00:07:56,760 --> 00:08:00,000 Speaker 1: off of people back then. Uh in night, there were 136 00:08:00,040 --> 00:08:03,640 Speaker 1: about three and a half billion people. And the birth rate. 137 00:08:03,760 --> 00:08:05,680 Speaker 1: We're gonna talk a lot about birth rates and such, 138 00:08:06,360 --> 00:08:08,400 Speaker 1: has a lot to do with this buckle up. Um. 139 00:08:08,760 --> 00:08:12,320 Speaker 1: The American women had three and a half babies on average, 140 00:08:12,560 --> 00:08:16,240 Speaker 1: and the global birth rate was five babies for a woman. 141 00:08:17,000 --> 00:08:20,240 Speaker 1: It seems like a lot to me. It was a 142 00:08:20,240 --> 00:08:25,200 Speaker 1: lot kids. Supposedly, in the fifties we were at six 143 00:08:25,360 --> 00:08:29,640 Speaker 1: the global average fertility it was six babies per woman. 144 00:08:29,880 --> 00:08:33,440 Speaker 1: And that's not just per woman. That's you want to 145 00:08:33,440 --> 00:08:38,280 Speaker 1: talk about fertility rates. So fertility rate basically is the 146 00:08:38,360 --> 00:08:43,000 Speaker 1: number of live births that a population has assigned to 147 00:08:43,760 --> 00:08:47,880 Speaker 1: the population of women thought to reasonably be a reproductive age. 148 00:08:47,920 --> 00:08:52,360 Speaker 1: So fifteen to forty four times a thousand, So you 149 00:08:52,440 --> 00:08:55,680 Speaker 1: take all of those, figure out the the how many 150 00:08:55,720 --> 00:08:58,760 Speaker 1: women there are, and then you multiply it by a thousand, 151 00:08:58,840 --> 00:09:03,080 Speaker 1: so you have something like, um, fifty births per one 152 00:09:03,160 --> 00:09:05,920 Speaker 1: thousand women aged fifteen to forty four, and that's your 153 00:09:05,920 --> 00:09:09,240 Speaker 1: fertility right. Yeah, okay, that's you can figure out how 154 00:09:09,240 --> 00:09:13,760 Speaker 1: many actual births are taking place. Yeah, with reasonable detail. Um. 155 00:09:14,000 --> 00:09:18,400 Speaker 1: So like Mauthis Airlic did the math in the sixties 156 00:09:18,960 --> 00:09:22,000 Speaker 1: and said, you know what, our food production isn't keeping up. 157 00:09:22,040 --> 00:09:25,000 Speaker 1: Just like Mautha said, we're in big, big trouble, wrote 158 00:09:25,000 --> 00:09:29,560 Speaker 1: the population bomb and co founded Zero Population Growth, which 159 00:09:29,559 --> 00:09:32,680 Speaker 1: is an organization that is now called uh what are 160 00:09:32,679 --> 00:09:37,000 Speaker 1: they called now? Population Connection? Population Connection? A very uh, 161 00:09:37,120 --> 00:09:40,679 Speaker 1: a little sunnier sounds Electric company. It does, and you 162 00:09:40,679 --> 00:09:42,319 Speaker 1: should check out their website. It's good. They have a 163 00:09:42,320 --> 00:09:44,320 Speaker 1: lot of good information on it, just to help you, 164 00:09:44,320 --> 00:09:47,959 Speaker 1: you know, figure out what you might want to believe. UM. 165 00:09:48,040 --> 00:09:53,920 Speaker 1: So people are scared the zero population growth group. Their 166 00:09:54,400 --> 00:09:58,600 Speaker 1: aim is to uh, They're big thing is is contraception 167 00:09:58,880 --> 00:10:04,000 Speaker 1: and giving women um control of their reproduction basically in 168 00:10:04,040 --> 00:10:06,800 Speaker 1: their fertility right. That's that you decide how many kids 169 00:10:06,840 --> 00:10:10,240 Speaker 1: you want exactly they have that many. They've identified that 170 00:10:10,200 --> 00:10:15,360 Speaker 1: that there's an issue that could easily address overpopulation, and 171 00:10:15,400 --> 00:10:20,720 Speaker 1: that is cutting out unwanted pregnancies or pregnancies or having 172 00:10:20,800 --> 00:10:25,840 Speaker 1: unwanted kids. They've identified that, you know, plenty of people. 173 00:10:25,960 --> 00:10:29,000 Speaker 1: There are two different fertility rates. There's the wanted fertility 174 00:10:29,120 --> 00:10:32,040 Speaker 1: rate and then there's the unwanted fertility rate, and pretty 175 00:10:32,080 --> 00:10:35,040 Speaker 1: much across the board in any country in the world, 176 00:10:35,400 --> 00:10:39,320 Speaker 1: the unwanted fertility rate is higher, whether slightly or largely, 177 00:10:39,679 --> 00:10:43,040 Speaker 1: than the wanted fertility rate. So they're saying, like, if 178 00:10:43,080 --> 00:10:46,679 Speaker 1: the unwanted fertility rates like three point eight babies per 179 00:10:46,760 --> 00:10:50,079 Speaker 1: woman in a given country and the wanted fertility rate 180 00:10:50,120 --> 00:10:52,440 Speaker 1: is like two point five, well, if we can just 181 00:10:52,480 --> 00:10:56,280 Speaker 1: figure out a way to only have the wanted pregnancies, 182 00:10:56,920 --> 00:11:00,679 Speaker 1: then you are doing a lot to control of a population. 183 00:11:01,040 --> 00:11:03,680 Speaker 1: And the way that they figured out how to address 184 00:11:03,720 --> 00:11:09,480 Speaker 1: this is to just basically spread awareness and access to contraception. Right, 185 00:11:09,559 --> 00:11:12,640 Speaker 1: the two pronged approach. UM what their goal is is 186 00:11:12,800 --> 00:11:15,880 Speaker 1: they aren't saying that people should not have babies like 187 00:11:15,920 --> 00:11:17,760 Speaker 1: you said, They're saying people should only have the babies 188 00:11:17,760 --> 00:11:21,160 Speaker 1: that they want to have, and their their ultimate goal 189 00:11:21,400 --> 00:11:25,439 Speaker 1: is to um to have a sustainable global birth rate 190 00:11:25,520 --> 00:11:28,480 Speaker 1: below the replacement level, which means there's a lot of 191 00:11:28,480 --> 00:11:33,199 Speaker 1: different factors, but it basically means that the world is 192 00:11:33,240 --> 00:11:36,880 Speaker 1: not growing. When it's like, uh, working a club at 193 00:11:37,080 --> 00:11:39,720 Speaker 1: at a door, being a doorman, one person goes out, 194 00:11:39,800 --> 00:11:41,920 Speaker 1: one person comes in. Yeah, you got a little quicker. 195 00:11:42,440 --> 00:11:45,000 Speaker 1: That's basically what that means is, you know, someone dies, 196 00:11:45,040 --> 00:11:47,040 Speaker 1: someone can be born, and of course it's not that 197 00:11:47,080 --> 00:11:49,080 Speaker 1: one to one, but you know, well, if you're a 198 00:11:49,080 --> 00:11:51,559 Speaker 1: big picture away, if you're a bouncer and you're tasked 199 00:11:51,559 --> 00:11:53,960 Speaker 1: with keeping it in even ratio, you just have to 200 00:11:53,960 --> 00:11:56,800 Speaker 1: remember that you can't keep people inside until a new 201 00:11:56,840 --> 00:12:02,040 Speaker 1: person comes along, because that's called kidnapping. You still they 202 00:12:02,080 --> 00:12:03,800 Speaker 1: still have to leave and you have to deal with 203 00:12:03,840 --> 00:12:07,719 Speaker 1: an imbalance for a little while. Right now, the replacement 204 00:12:07,800 --> 00:12:10,240 Speaker 1: level of fertility rate in the US is two point 205 00:12:10,280 --> 00:12:13,680 Speaker 1: one babies for a woman and three point zero and 206 00:12:13,760 --> 00:12:17,040 Speaker 1: other developing countries because they have higher death rates and 207 00:12:17,080 --> 00:12:22,120 Speaker 1: shorter lifespans, which makes sense. So we were onto the 208 00:12:22,200 --> 00:12:25,920 Speaker 1: replacement rate basically, right. The replacement rate is the number 209 00:12:25,960 --> 00:12:30,040 Speaker 1: of kids a woman of reproductive age would have to 210 00:12:30,080 --> 00:12:34,080 Speaker 1: have to replace herself. And she's not just replacing herself, 211 00:12:34,320 --> 00:12:40,559 Speaker 1: she's replacing herself and her male mate who she's reproducing with. Yes, 212 00:12:40,760 --> 00:12:42,520 Speaker 1: and it's kind of gross to think that a woman 213 00:12:42,600 --> 00:12:45,040 Speaker 1: is giving birth to a boy and a girl who 214 00:12:45,080 --> 00:12:47,800 Speaker 1: can mate and reproduce her. That's not the point he 215 00:12:47,840 --> 00:12:51,080 Speaker 1: want them to go mingle with other people's babies. But 216 00:12:51,480 --> 00:12:54,360 Speaker 1: the replacement rate, you would think then is to right 217 00:12:54,840 --> 00:12:58,320 Speaker 1: for every woman, two point zero kids is what you 218 00:12:58,360 --> 00:13:01,120 Speaker 1: need to have to have an even replacement rate. That 219 00:13:01,120 --> 00:13:04,120 Speaker 1: means that people die, new people are born, and the 220 00:13:04,160 --> 00:13:07,680 Speaker 1: population never grows or declines, it stays the same. The 221 00:13:07,760 --> 00:13:10,760 Speaker 1: replacement rate is never actually two point oh though most 222 00:13:10,760 --> 00:13:13,080 Speaker 1: two point one right now, and the reason why is 223 00:13:13,080 --> 00:13:16,959 Speaker 1: because we humans um tend to have more male offspring 224 00:13:17,080 --> 00:13:21,880 Speaker 1: than female. Apparently, for every one hundred girls that are born, 225 00:13:22,120 --> 00:13:24,960 Speaker 1: one hundred and seven boys are born. So the actual 226 00:13:25,040 --> 00:13:27,720 Speaker 1: replacement rate is two point zero seven and then they 227 00:13:27,800 --> 00:13:30,200 Speaker 1: round up to two point one plus there's I mean, 228 00:13:30,200 --> 00:13:32,720 Speaker 1: there's a lot of other factors too, for sure. So 229 00:13:32,960 --> 00:13:35,640 Speaker 1: those other factors include things like you said, like, um, 230 00:13:35,679 --> 00:13:42,199 Speaker 1: infomortality rates, lifespan, immigration into a certain area, And the 231 00:13:42,200 --> 00:13:46,880 Speaker 1: thing is of birth rates or fertility rates and replacement rates. 232 00:13:47,080 --> 00:13:50,640 Speaker 1: The replacement rate tends to be a little more stable. Um. 233 00:13:50,840 --> 00:13:53,920 Speaker 1: The the birth rate. The fertility rate has a lot 234 00:13:53,960 --> 00:13:58,000 Speaker 1: more to do with social attitudes, access to healthcare, education, 235 00:13:58,480 --> 00:14:01,960 Speaker 1: and it's a it can change, uh dramatically from place 236 00:14:02,000 --> 00:14:04,880 Speaker 1: to place, whereas say, anywhere in the western world, the 237 00:14:04,960 --> 00:14:10,360 Speaker 1: developed world, the replacement rates about two point one exactly. 238 00:14:10,760 --> 00:14:13,080 Speaker 1: That's in the yeah, the three point oh for the 239 00:14:13,400 --> 00:14:16,960 Speaker 1: developing countries. All the monographers just stood up and we're clapping. 240 00:14:17,600 --> 00:14:22,920 Speaker 1: So clearly Aerlic was not correct in his dire predictions. 241 00:14:23,760 --> 00:14:28,400 Speaker 1: Here we are in and um, there are problems, but 242 00:14:28,600 --> 00:14:36,120 Speaker 1: England is still around four billion people haven't starved to death. Um. 243 00:14:36,160 --> 00:14:39,680 Speaker 1: But does that mean that he was wrong altogether? Not 244 00:14:39,720 --> 00:14:43,680 Speaker 1: necessarily because right now, uh, and This was a pretty 245 00:14:43,760 --> 00:14:46,520 Speaker 1: startling stat to me. Over the past hundred and ten years, 246 00:14:47,080 --> 00:14:49,840 Speaker 1: we have grown from one point six billion people to 247 00:14:49,960 --> 00:14:53,800 Speaker 1: seven point to billion people in a hundred and ten years. Well, 248 00:14:53,840 --> 00:14:56,160 Speaker 1: we're expected to get up to nine point two and 249 00:14:56,280 --> 00:15:01,120 Speaker 1: another uh thirty five years by twenty and so one 250 00:15:01,120 --> 00:15:04,000 Speaker 1: of the reasons we have this many people, uh, most 251 00:15:04,040 --> 00:15:07,600 Speaker 1: of the reasons are positive because of like advances in healthcare. 252 00:15:08,320 --> 00:15:11,400 Speaker 1: The lifespan in nineteen hundred was thirty one years old 253 00:15:11,720 --> 00:15:14,240 Speaker 1: and now it's seventy or maybe even little bit higher 254 00:15:14,280 --> 00:15:17,480 Speaker 1: because that was two thousand, twelve UM, so imagine it's 255 00:15:17,480 --> 00:15:21,080 Speaker 1: a little bit higher. And the infant mortality rate globally 256 00:15:21,120 --> 00:15:24,280 Speaker 1: in nineteen hundred was a hundred and sixty five deaths 257 00:15:24,280 --> 00:15:28,480 Speaker 1: per one thousand live births was down to thirty four. 258 00:15:29,000 --> 00:15:31,040 Speaker 1: So that's why there's more people, because we're doing better 259 00:15:31,080 --> 00:15:33,400 Speaker 1: at taking care of ourselves. Yeah, and that those are 260 00:15:33,440 --> 00:15:37,240 Speaker 1: two huge factors when it comes to um demographics and 261 00:15:37,280 --> 00:15:41,480 Speaker 1: population because though the longer you live, the more old 262 00:15:41,520 --> 00:15:44,360 Speaker 1: people you have, so therefore the less babies you need 263 00:15:44,560 --> 00:15:49,040 Speaker 1: to replace those people, and the fewer babies that die 264 00:15:49,120 --> 00:15:54,040 Speaker 1: or that survive infancy UM will be adults one day exactly. 265 00:15:54,560 --> 00:15:57,600 Speaker 1: But these are the really if you're a demographer, the 266 00:15:57,640 --> 00:16:01,400 Speaker 1: sweet spot is that working age. So when you're a demographer, 267 00:16:01,480 --> 00:16:06,680 Speaker 1: especially one that's um economics minded, chuck that sweet spot 268 00:16:06,760 --> 00:16:11,560 Speaker 1: the reproductive working age people. That's a good sizeable population 269 00:16:11,600 --> 00:16:13,720 Speaker 1: you want to have. If you have a lot of babies, 270 00:16:13,920 --> 00:16:16,040 Speaker 1: well then you have a lot of people who are 271 00:16:16,520 --> 00:16:19,000 Speaker 1: raising those babies, so those babies are dependent on So 272 00:16:19,080 --> 00:16:21,480 Speaker 1: say you have a lot fewer women in the workforce, 273 00:16:21,560 --> 00:16:23,960 Speaker 1: so your workforce is depleted. If you have a lot 274 00:16:24,000 --> 00:16:26,720 Speaker 1: of like an aging population, you have a lot of 275 00:16:26,800 --> 00:16:29,680 Speaker 1: older people who have already aged out of the workforce 276 00:16:29,680 --> 00:16:33,120 Speaker 1: and are now dependent on the taxes paid by that workforce. 277 00:16:33,600 --> 00:16:37,600 Speaker 1: So a large population of either babies or old people, 278 00:16:37,800 --> 00:16:40,480 Speaker 1: and god forbid both at the same time. It puts 279 00:16:40,520 --> 00:16:42,880 Speaker 1: a lot of strain on the middle you know what 280 00:16:42,920 --> 00:16:46,560 Speaker 1: I'm saying. Sure, So when you have a longer life 281 00:16:46,560 --> 00:16:51,240 Speaker 1: expectancy and a lower infant mortality rate like we have 282 00:16:51,360 --> 00:16:54,000 Speaker 1: now in the developed world, you want to have something 283 00:16:54,040 --> 00:16:58,800 Speaker 1: closer to the replacement rate, you know, which makes sense. Um, 284 00:16:58,840 --> 00:17:01,720 Speaker 1: I got some more stats that would uh seem to 285 00:17:01,760 --> 00:17:05,439 Speaker 1: back up air likes. Predictions are not predictions. But at 286 00:17:05,480 --> 00:17:09,920 Speaker 1: least his gloomy outlook currently. You know, I couldn't find 287 00:17:09,960 --> 00:17:12,840 Speaker 1: much on what he felt today. Yeah, I'm curious that 288 00:17:12,880 --> 00:17:16,040 Speaker 1: he's still around. I'm curious about there's some good interviews. 289 00:17:16,040 --> 00:17:18,320 Speaker 1: I'm gonna check that out. You know what, We'll post 290 00:17:18,359 --> 00:17:23,639 Speaker 1: it on uh the website because now we're posting links, yeah, 291 00:17:23,720 --> 00:17:26,119 Speaker 1: to like the research that we do stuff. You should know, 292 00:17:26,840 --> 00:17:30,880 Speaker 1: great links on that on the podcast page for this episode. Guys. 293 00:17:30,920 --> 00:17:34,800 Speaker 1: So currently, as of last year and estimated eight hundred 294 00:17:34,800 --> 00:17:37,960 Speaker 1: and five million people go to bed Hungary every night, 295 00:17:38,440 --> 00:17:41,040 Speaker 1: more than half of which are in Asia. One in 296 00:17:41,200 --> 00:17:46,200 Speaker 1: four people in Sub Saharan Africa was chronically malnourished UM 297 00:17:46,280 --> 00:17:49,359 Speaker 1: seven hundred fifty million people worldwide like access to clean 298 00:17:49,400 --> 00:17:53,920 Speaker 1: water UM, contributing to about eight hundred and fifty thousand 299 00:17:53,920 --> 00:17:58,480 Speaker 1: deaths per year. And UM, here's the thing, though, is 300 00:17:58,800 --> 00:18:02,359 Speaker 1: we're living in cities out more than ever. UM. People 301 00:18:02,359 --> 00:18:04,320 Speaker 1: are moving into cities, which is a good thing and 302 00:18:04,520 --> 00:18:08,320 Speaker 1: one way because it provides a lot of opportunity, economic 303 00:18:08,640 --> 00:18:12,760 Speaker 1: economic opportunity for people, especially in developing countries. But when 304 00:18:12,800 --> 00:18:14,880 Speaker 1: you look at these cities, a lot of them are 305 00:18:15,800 --> 00:18:20,160 Speaker 1: full of slums and sweatshops. In these developing nations, something 306 00:18:20,240 --> 00:18:22,679 Speaker 1: like um half of the population and a lot of 307 00:18:22,720 --> 00:18:27,959 Speaker 1: cities live in slum conditions in Africa, that's right. So 308 00:18:28,160 --> 00:18:31,479 Speaker 1: you think sub Saharan Africa, I think rural in a 309 00:18:31,480 --> 00:18:35,040 Speaker 1: lot of ways. So yes, I'm aware that they they 310 00:18:35,119 --> 00:18:38,200 Speaker 1: lack access to clean drinking water, and that's an issue 311 00:18:38,240 --> 00:18:41,240 Speaker 1: that Sub Saharan Africa faces. You don't think about that 312 00:18:41,320 --> 00:18:44,119 Speaker 1: being an issue in a city. But the problem with 313 00:18:44,200 --> 00:18:47,720 Speaker 1: slums is they very rarely have access to clean drinking 314 00:18:47,720 --> 00:18:50,439 Speaker 1: water in the exact same way that places like rural 315 00:18:50,440 --> 00:18:53,239 Speaker 1: Africa have the same problem. Yeah, and and we're not 316 00:18:53,280 --> 00:18:55,679 Speaker 1: even I mean that's that's clean drinking water and like 317 00:18:55,720 --> 00:18:59,240 Speaker 1: sanitation and shelter. We're not even talking about education and 318 00:18:59,320 --> 00:19:02,840 Speaker 1: healthcare and like all the things that people need to 319 00:19:02,880 --> 00:19:07,600 Speaker 1: live a fruitful life. You know. So cities are a problem. 320 00:19:07,640 --> 00:19:11,800 Speaker 1: Even if air look was wrong, there are clearly issues. Um. 321 00:19:11,920 --> 00:19:13,919 Speaker 1: Some people will argue and we'll get to the critics 322 00:19:13,920 --> 00:19:16,320 Speaker 1: and stuff later, but a lot of people argued that 323 00:19:16,359 --> 00:19:18,560 Speaker 1: it's distribution of food and stuff like that, Like we 324 00:19:18,640 --> 00:19:22,840 Speaker 1: have the resources, we're just not dividing it out properly. Right, 325 00:19:22,920 --> 00:19:28,080 Speaker 1: And apparently if I read that if everyone lived like 326 00:19:28,119 --> 00:19:32,800 Speaker 1: an American and consumed like an American does, the caring 327 00:19:32,800 --> 00:19:35,480 Speaker 1: capacity would be something like two billion, So we would 328 00:19:35,480 --> 00:19:38,680 Speaker 1: have already far exceeded it. But if everybody lived with 329 00:19:38,800 --> 00:19:41,199 Speaker 1: just the minimal amount that they need to live, the 330 00:19:41,240 --> 00:19:44,399 Speaker 1: caring capacity would be something like forty billion. We've been 331 00:19:44,440 --> 00:19:47,439 Speaker 1: able to sustain the caring capacity as it is right 332 00:19:47,480 --> 00:19:50,600 Speaker 1: now because not everybody lives like an American. But if 333 00:19:50,600 --> 00:19:53,119 Speaker 1: you're an American, that means that a lot of the 334 00:19:53,119 --> 00:19:56,880 Speaker 1: other world, especially developing world, thinks that you are over 335 00:19:56,960 --> 00:20:00,880 Speaker 1: consuming by a lot. And that's really evident. And um 336 00:20:00,920 --> 00:20:03,240 Speaker 1: there's a graph that went around recently that shows water 337 00:20:03,400 --> 00:20:07,600 Speaker 1: use in agriculture by type of product, so everything from 338 00:20:07,640 --> 00:20:11,680 Speaker 1: like soy to beef. It showed how much water? Did 339 00:20:11,680 --> 00:20:13,400 Speaker 1: you see that? I didn't see that, but I've seen 340 00:20:13,560 --> 00:20:17,240 Speaker 1: stuff like that. Beef is like a huge consumer water, right, 341 00:20:17,320 --> 00:20:20,040 Speaker 1: A hundred and six point to eight gallons of water 342 00:20:20,240 --> 00:20:24,000 Speaker 1: used to produce one ounce of beef. That's a lot. 343 00:20:24,840 --> 00:20:27,680 Speaker 1: That's a lot of water. And so that's that's part 344 00:20:27,720 --> 00:20:31,200 Speaker 1: of the point. Whereas if everybody's and apparently in China 345 00:20:31,240 --> 00:20:35,280 Speaker 1: and India and these ascending countries with ascending economies. Um. 346 00:20:35,720 --> 00:20:38,280 Speaker 1: One of the one of the great benefits of being 347 00:20:38,359 --> 00:20:40,720 Speaker 1: part of the developed worlds. You can get steak anytime 348 00:20:40,760 --> 00:20:43,480 Speaker 1: you want, baby, and uh, I want a big one 349 00:20:43,600 --> 00:20:45,280 Speaker 1: right now, put it in front of me. I'll give 350 00:20:45,320 --> 00:20:48,000 Speaker 1: you some money here. Here, just take this and and 351 00:20:48,320 --> 00:20:50,199 Speaker 1: put in your pocket. There's some money for you. Give 352 00:20:50,240 --> 00:20:52,840 Speaker 1: me my steak, and you don't care how much water 353 00:20:52,920 --> 00:20:57,200 Speaker 1: it took. And they're these people who are saying they 354 00:20:57,200 --> 00:20:59,720 Speaker 1: don't necessarily agree with their like, but they're saying, he 355 00:20:59,840 --> 00:21:04,600 Speaker 1: was totally off here, he was alarmed. They're saying, this 356 00:21:04,720 --> 00:21:06,800 Speaker 1: is one of the problems. You know, this is one 357 00:21:06,800 --> 00:21:09,239 Speaker 1: of the problems with too many people. Yeah, and so 358 00:21:09,400 --> 00:21:13,639 Speaker 1: getting back to to uh, contraception and zero population growth 359 00:21:14,240 --> 00:21:18,040 Speaker 1: or now the population connection they're big goal. They say 360 00:21:18,040 --> 00:21:21,879 Speaker 1: there are two two million women in the developing world 361 00:21:21,880 --> 00:21:24,680 Speaker 1: who have an unmet need for family planning. So they're 362 00:21:24,680 --> 00:21:27,880 Speaker 1: not saying, you know, we want to put our ideals 363 00:21:27,880 --> 00:21:30,000 Speaker 1: on you and you shouldn't be having kids. They're saying 364 00:21:30,040 --> 00:21:32,240 Speaker 1: they're that many women that are like, I don't want 365 00:21:32,480 --> 00:21:36,119 Speaker 1: these five kids. I would have wanted to and I 366 00:21:36,280 --> 00:21:40,199 Speaker 1: either don't know about contraception, don't have contraception or I 367 00:21:40,240 --> 00:21:44,960 Speaker 1: have literally no idea how conception works for a lot 368 00:21:45,040 --> 00:21:47,960 Speaker 1: of them. Well, I shouldn't say a lot. The first 369 00:21:48,000 --> 00:21:52,119 Speaker 1: idea that women just need access to contraception and they 370 00:21:52,119 --> 00:21:55,880 Speaker 1: will use it. Yeah, and they're they're they're working on that, right, 371 00:21:56,280 --> 00:21:58,840 Speaker 1: But they found in studies it's something like ten percent 372 00:21:58,960 --> 00:22:01,760 Speaker 1: or less of the women who are defined as having 373 00:22:01,840 --> 00:22:07,400 Speaker 1: unmet contraceptive needs. Um site a lack of access as 374 00:22:07,400 --> 00:22:11,080 Speaker 1: to why they're having unwanted kids. Instead, they're saying it's 375 00:22:11,119 --> 00:22:14,159 Speaker 1: things like family pressure or societal pressure to have a 376 00:22:14,200 --> 00:22:17,719 Speaker 1: bunch of kids. Um Like you're saying, like not understanding 377 00:22:17,760 --> 00:22:20,960 Speaker 1: contraception or how conception works. Yeah, they say they don't 378 00:22:21,000 --> 00:22:24,119 Speaker 1: believe that they need contraception. If you have sex infrequently 379 00:22:24,920 --> 00:22:27,720 Speaker 1: or after birth, after I've had one kid, we don't 380 00:22:27,720 --> 00:22:31,480 Speaker 1: need to use contraception anymore. Like literally not knowing how 381 00:22:31,960 --> 00:22:37,520 Speaker 1: conception works. So that's a big educational hurdle that Population 382 00:22:37,880 --> 00:22:40,560 Speaker 1: Connection is trying to overcome. Right, So they're saying it's 383 00:22:40,600 --> 00:22:44,159 Speaker 1: not just getting contraception to women, is educating them on 384 00:22:44,200 --> 00:22:47,480 Speaker 1: how to use it and changing their social outlook. Yeah, 385 00:22:47,560 --> 00:22:53,359 Speaker 1: changing the culture. Yeah, largely men, you know, saying you know, 386 00:22:53,560 --> 00:22:58,240 Speaker 1: like revolutionary road or something. You know. Alright, So, uh, 387 00:22:58,320 --> 00:23:00,399 Speaker 1: we're gonna talk a little bit after the break about 388 00:23:00,720 --> 00:23:24,560 Speaker 1: what the critics of zero population growth have to say. 389 00:23:28,200 --> 00:23:33,320 Speaker 1: So we're back. We're talking about solutions to overpopulation. But 390 00:23:33,359 --> 00:23:36,320 Speaker 1: not everybody thinks it's a problem. Some people say over 391 00:23:36,400 --> 00:23:40,320 Speaker 1: population is a myth. They say that are like in 392 00:23:40,400 --> 00:23:45,080 Speaker 1: and of it himself damaged his own argument. Yeah, he 393 00:23:45,119 --> 00:23:47,800 Speaker 1: got a lot of personal heat. Yeah, still does because 394 00:23:47,800 --> 00:23:50,320 Speaker 1: of the language he used. It was so alarmed as 395 00:23:50,359 --> 00:23:52,959 Speaker 1: starting his book off with, you know that we've already 396 00:23:52,960 --> 00:23:55,320 Speaker 1: lost and no matter what we do, billions of people 397 00:23:55,359 --> 00:23:58,240 Speaker 1: are going to die. Um and then it not panning 398 00:23:58,240 --> 00:24:00,960 Speaker 1: out saying that England is going to be around in 399 00:24:01,080 --> 00:24:03,840 Speaker 1: thirty years. I mean that was putting a lot on 400 00:24:03,880 --> 00:24:07,720 Speaker 1: the line. And so a lot of people said, you're 401 00:24:07,760 --> 00:24:13,560 Speaker 1: your specific landmarks or um or milestones were unmet. Therefore 402 00:24:13,560 --> 00:24:17,000 Speaker 1: your heart whole arguments out the window. And some people 403 00:24:17,280 --> 00:24:20,880 Speaker 1: believe that other people are like, that's not necessarily true. 404 00:24:20,920 --> 00:24:25,160 Speaker 1: That is alarmist as well, possibly your reactionary at least. 405 00:24:25,480 --> 00:24:27,800 Speaker 1: But some people say, I still don't agree with Earli 406 00:24:28,160 --> 00:24:31,440 Speaker 1: because humans are smart. We can figure our way out 407 00:24:31,480 --> 00:24:34,880 Speaker 1: of any problem. That's right. Critics will say that humans 408 00:24:35,040 --> 00:24:37,439 Speaker 1: UM are not parasites to the earth. We are the 409 00:24:37,440 --> 00:24:40,480 Speaker 1: saviors of Earth, and we are the ones that are 410 00:24:40,480 --> 00:24:44,439 Speaker 1: coming up with these solutions like the Green Revolution and uh, 411 00:24:44,640 --> 00:24:48,200 Speaker 1: longer lifespans and progressing medically to help people live longer. 412 00:24:48,400 --> 00:24:50,960 Speaker 1: I don't know about saviors of Earth, you know, Like 413 00:24:51,359 --> 00:24:53,360 Speaker 1: I think that's stretching it a little bit. I think 414 00:24:53,400 --> 00:24:56,080 Speaker 1: we um extract a little too much to be called 415 00:24:56,160 --> 00:24:58,679 Speaker 1: saviors of Earth. Well, I've guarantee you there's a lot 416 00:24:58,720 --> 00:25:00,560 Speaker 1: of people that think humans are saying years of birth. 417 00:25:01,119 --> 00:25:03,399 Speaker 1: You know. I would see us more as like Homer 418 00:25:03,480 --> 00:25:05,960 Speaker 1: with Pincy the lobster again and the salt water and 419 00:25:06,000 --> 00:25:10,040 Speaker 1: fresh water, trying to strike the balance. I wouldn't call 420 00:25:10,119 --> 00:25:12,640 Speaker 1: him a savior of either the goldfish or Pinchy at 421 00:25:12,640 --> 00:25:16,440 Speaker 1: that moment. He's just keeping them both in stasis. How 422 00:25:16,440 --> 00:25:19,240 Speaker 1: many times have you referenced pinch there's probably seven seven 423 00:25:19,640 --> 00:25:23,680 Speaker 1: It's not bad. It's one for every one shows roughly. UM. 424 00:25:24,119 --> 00:25:26,720 Speaker 1: Other critics will say that low birth rates are no 425 00:25:26,800 --> 00:25:29,120 Speaker 1: good for the economy, UM, like you were talking about 426 00:25:29,160 --> 00:25:33,240 Speaker 1: earlier UM, older people and babies. Uh. Well, I guess 427 00:25:33,240 --> 00:25:36,280 Speaker 1: low birth rates wouldn't affect that. But older people are 428 00:25:36,440 --> 00:25:39,480 Speaker 1: more of a tax on society than they are spenders 429 00:25:39,880 --> 00:25:42,320 Speaker 1: and investors, right, But in the same in the same way, 430 00:25:42,359 --> 00:25:44,480 Speaker 1: if you have too many babies, that's a big text 431 00:25:44,560 --> 00:25:48,359 Speaker 1: eventually that those babies will be a workforce like spend 432 00:25:48,400 --> 00:25:52,680 Speaker 1: money exactly. So the baby boom and the post war 433 00:25:53,800 --> 00:25:58,680 Speaker 1: boom economic boom in the United States, it's not coincidental 434 00:25:58,720 --> 00:26:00,520 Speaker 1: that they went hand in hand. There are a bunch 435 00:26:00,560 --> 00:26:03,600 Speaker 1: of people having babies and eventually they grew into the 436 00:26:03,600 --> 00:26:07,040 Speaker 1: workforce and they made a bunch of money in the 437 00:26:07,080 --> 00:26:09,920 Speaker 1: eighties for the United States. Yeah, and there's it's also 438 00:26:09,960 --> 00:26:13,479 Speaker 1: supported in developing countries. Uh. More than seventy countries are 439 00:26:13,520 --> 00:26:17,560 Speaker 1: categorized now as low fertility with two babies or less 440 00:26:17,560 --> 00:26:21,800 Speaker 1: per woman, And those areas are expected to make a 441 00:26:21,800 --> 00:26:25,520 Speaker 1: big economic gains in the coming decades because they're going 442 00:26:25,560 --> 00:26:28,639 Speaker 1: to be people to spend money, right and be in 443 00:26:28,680 --> 00:26:33,560 Speaker 1: the workforce. And there's kind of a few ways that 444 00:26:33,600 --> 00:26:38,520 Speaker 1: the workforce and wealth in the economy and birthrates are 445 00:26:38,560 --> 00:26:41,320 Speaker 1: all kind of tied together too. It turns out that 446 00:26:41,359 --> 00:26:47,400 Speaker 1: if you give a woman rights to her own contraceptive decisions, 447 00:26:48,320 --> 00:26:52,800 Speaker 1: um the birth rate tends to inevitably fall as a result. Uh. 448 00:26:52,840 --> 00:26:55,840 Speaker 1: And then when that happens, it happens because some women 449 00:26:55,880 --> 00:26:58,480 Speaker 1: have more babies than they want to when they don't 450 00:26:58,560 --> 00:27:02,200 Speaker 1: have right to their own count receptive decisions. UM. Another 451 00:27:02,240 --> 00:27:05,520 Speaker 1: reason is when they have those kind of rights, they 452 00:27:05,560 --> 00:27:08,359 Speaker 1: usually also have the right to an education. When they 453 00:27:08,520 --> 00:27:11,399 Speaker 1: enter um school, they will tend to put off having 454 00:27:11,480 --> 00:27:14,520 Speaker 1: kids because once they graduate from school, they'll usually enter 455 00:27:14,520 --> 00:27:17,399 Speaker 1: the workforce, and so just by nature of getting to 456 00:27:17,480 --> 00:27:19,919 Speaker 1: the whole thing later on in life, they're having fewer 457 00:27:20,000 --> 00:27:23,400 Speaker 1: kids as well. Uh. And when you have more educated 458 00:27:23,440 --> 00:27:26,680 Speaker 1: women in the workforce, your economy is stronger too. So 459 00:27:27,160 --> 00:27:31,359 Speaker 1: directly and by proxy, um, lower birth rates are associated 460 00:27:31,400 --> 00:27:34,159 Speaker 1: with the stronger economy. But again, you don't want to 461 00:27:34,200 --> 00:27:36,399 Speaker 1: get too low, because if you get too low, then 462 00:27:36,440 --> 00:27:39,960 Speaker 1: all of a sudden, the generation before it started to 463 00:27:40,040 --> 00:27:42,720 Speaker 1: taper off is going to be bigger than the generation 464 00:27:42,760 --> 00:27:47,320 Speaker 1: that's working. And if it costs fifty dollars in tax 465 00:27:47,400 --> 00:27:51,119 Speaker 1: money to keep the average retiree afloat, say in the 466 00:27:51,200 --> 00:27:55,159 Speaker 1: United States, well that divided by a thousand people is 467 00:27:55,160 --> 00:27:58,160 Speaker 1: a lot easier to bear than divided by a hundred people. 468 00:27:58,280 --> 00:28:00,960 Speaker 1: A hundred working people, you know what I mean. Yeah, 469 00:28:00,960 --> 00:28:02,960 Speaker 1: we gotta keep up the old folks and uh keep 470 00:28:03,000 --> 00:28:05,920 Speaker 1: them in stake and ovaltine right. You know. So if 471 00:28:05,960 --> 00:28:10,280 Speaker 1: you're if you're an economist, demographer, whatever, everybody's kind of 472 00:28:10,320 --> 00:28:13,320 Speaker 1: saying like, you want to get a country developed, and 473 00:28:13,359 --> 00:28:14,920 Speaker 1: you want to get them at the two point one 474 00:28:14,960 --> 00:28:18,120 Speaker 1: replacement rate and everything will be hunky dory from there. Yeah. 475 00:28:18,160 --> 00:28:21,320 Speaker 1: And the other thing a critic might say too is um, 476 00:28:21,320 --> 00:28:23,240 Speaker 1: and this is what we were talking about earlier about 477 00:28:23,280 --> 00:28:26,560 Speaker 1: the environment, Uh, the impact on the environment, Like we're 478 00:28:26,600 --> 00:28:30,160 Speaker 1: just going to destroy our world with so many people. Um. 479 00:28:30,200 --> 00:28:34,879 Speaker 1: It turns out that impact carbon emissions aren't really tied 480 00:28:34,920 --> 00:28:38,960 Speaker 1: to population growth rates. It's tied to per capita income levels. 481 00:28:39,520 --> 00:28:42,080 Speaker 1: By evidence that China in the US have some of 482 00:28:42,080 --> 00:28:45,680 Speaker 1: the lowest UH fertility rates right now, and we are 483 00:28:45,680 --> 00:28:48,560 Speaker 1: the worst polluters. So it's not because we have all 484 00:28:48,560 --> 00:28:54,600 Speaker 1: these people. It's because we're consuming too much as Americans exactly, 485 00:28:54,640 --> 00:28:57,800 Speaker 1: and I guess in China as well, which actually makes 486 00:28:57,840 --> 00:29:01,800 Speaker 1: it seem kind of nerve racking that India and China 487 00:29:02,040 --> 00:29:06,400 Speaker 1: with these enormous populations, are starting to become wealthier and wealthier, 488 00:29:06,760 --> 00:29:10,040 Speaker 1: because that's just going to make it even worse as 489 00:29:10,120 --> 00:29:13,000 Speaker 1: far as the environment goes. Did you check out the 490 00:29:13,040 --> 00:29:16,400 Speaker 1: Population Connection site? No? I didn't. They have a pretty 491 00:29:16,400 --> 00:29:19,200 Speaker 1: interesting f a q um that if you don't know 492 00:29:19,240 --> 00:29:21,960 Speaker 1: where you stand. I mean, it's helpful to read uh 493 00:29:22,160 --> 00:29:25,240 Speaker 1: like they say things like, instead of we want to 494 00:29:25,240 --> 00:29:28,520 Speaker 1: focus on quality of life, not quantity, and instead of 495 00:29:28,560 --> 00:29:31,480 Speaker 1: saying how many people can the earth support, maybe how 496 00:29:31,480 --> 00:29:34,720 Speaker 1: many people can't be or support because right now all 497 00:29:34,760 --> 00:29:38,280 Speaker 1: these people are dying from lack of you know, clean 498 00:29:38,320 --> 00:29:42,920 Speaker 1: water and sanitation and food. Um. And there's the counter 499 00:29:43,000 --> 00:29:44,840 Speaker 1: argument that you hear from critics a lot. I've seen 500 00:29:44,840 --> 00:29:48,400 Speaker 1: this stat thrown around that the entire world's population could 501 00:29:48,400 --> 00:29:52,640 Speaker 1: live in Texas. It's still mind boggling. I have trouble 502 00:29:52,760 --> 00:29:55,400 Speaker 1: like believing it. Well, I think somebody forget to carry 503 00:29:55,400 --> 00:29:58,280 Speaker 1: a one or something. No, it's true. Population Connection says, 504 00:29:58,520 --> 00:30:03,160 Speaker 1: sure they can. Uh, you could fit everyone in Texas. 505 00:30:03,240 --> 00:30:05,440 Speaker 1: You could also fit forty people in a phone booth. 506 00:30:06,200 --> 00:30:09,600 Speaker 1: But um, Texas, they said, in no way has the 507 00:30:09,640 --> 00:30:12,800 Speaker 1: carrying capacity to take care of those people. So it's 508 00:30:12,800 --> 00:30:15,280 Speaker 1: a little bit of a hollow. You know the fact 509 00:30:15,400 --> 00:30:17,280 Speaker 1: that you throw out when you say that, right, like, 510 00:30:17,320 --> 00:30:21,160 Speaker 1: sure you can jam everyone in there. Um. Texas would 511 00:30:21,200 --> 00:30:26,000 Speaker 1: be like what do you guys doing here? Everyone? Um? 512 00:30:26,000 --> 00:30:28,560 Speaker 1: But it's pretty interesting stuff. I recommend people read their 513 00:30:28,600 --> 00:30:31,040 Speaker 1: f a Q U. It seems like they definitely have 514 00:30:31,120 --> 00:30:35,920 Speaker 1: the right um mindset because that what they want to 515 00:30:35,920 --> 00:30:37,800 Speaker 1: do is, you know, make sure people have a good 516 00:30:37,880 --> 00:30:39,840 Speaker 1: quality of life all over the world. Well, I will 517 00:30:39,880 --> 00:30:42,960 Speaker 1: go read the f a Q because I suddenly feel underprepared. 518 00:30:43,120 --> 00:30:45,600 Speaker 1: But I will tell you that the impression that I 519 00:30:45,600 --> 00:30:50,120 Speaker 1: have from researching them without going on their website was, um, 520 00:30:50,200 --> 00:30:54,480 Speaker 1: I didn't find anything like where population connection or the 521 00:30:54,560 --> 00:30:58,200 Speaker 1: population connection myth or anything like that. There's definitely debate 522 00:30:58,240 --> 00:31:02,040 Speaker 1: on the other side saying overpopulation is a myth, but 523 00:31:02,080 --> 00:31:04,560 Speaker 1: no one seems to be attacking population connection is like 524 00:31:04,600 --> 00:31:08,280 Speaker 1: a nefarious organization because they're not saying don't have babies, right, 525 00:31:08,480 --> 00:31:11,040 Speaker 1: And that's a really sticky situation to be in because 526 00:31:11,040 --> 00:31:13,440 Speaker 1: a lot of people are like, well, God wants us 527 00:31:13,480 --> 00:31:15,920 Speaker 1: to have as many babies as we possibly can. Who 528 00:31:16,000 --> 00:31:17,960 Speaker 1: are you to be meddling in that kind of thing. 529 00:31:18,400 --> 00:31:20,520 Speaker 1: It's a it's a fine line that a group like 530 00:31:20,560 --> 00:31:23,120 Speaker 1: that has to walk, and they seem to be walking 531 00:31:23,120 --> 00:31:27,600 Speaker 1: at fine, there's just saying like, here's some contraception. Maybe 532 00:31:27,680 --> 00:31:30,880 Speaker 1: let's not have unwanted babies. Let this little angels stay 533 00:31:30,880 --> 00:31:35,880 Speaker 1: in heaven, and uh, we'll just go from there. I 534 00:31:35,920 --> 00:31:42,000 Speaker 1: think that's their on their homepage, all right, the Behavioral Sink. 535 00:31:42,480 --> 00:31:46,440 Speaker 1: What um, where did you find this? I don't remember 536 00:31:46,480 --> 00:31:48,960 Speaker 1: where I ran across it, but um, I'd read it 537 00:31:49,000 --> 00:31:50,640 Speaker 1: a while back. But I have to give a shout 538 00:31:50,640 --> 00:31:54,000 Speaker 1: out to Josh from Jersey, the original Jersey, not New Jersey, 539 00:31:54,440 --> 00:31:56,840 Speaker 1: who recently wrote in to suggest we we do an 540 00:31:56,840 --> 00:31:59,440 Speaker 1: episode on that and a perfect timing, because he wrote 541 00:31:59,440 --> 00:32:02,959 Speaker 1: in after you'd selected this one, and I was like, 542 00:32:03,080 --> 00:32:05,680 Speaker 1: these two would go great together, hand in hand. Yeah, 543 00:32:05,720 --> 00:32:08,680 Speaker 1: So thanks Josh for reminding us. Well, thank you Josh 544 00:32:08,960 --> 00:32:12,480 Speaker 1: for thanking Josh, which Josh, I'm thinking all the Josh 545 00:32:12,560 --> 00:32:18,160 Speaker 1: is so. In nineteen seventy two, this dude named John B. Calhoun. Um, 546 00:32:18,160 --> 00:32:20,560 Speaker 1: this is one of his experiments. This guy, what he 547 00:32:20,640 --> 00:32:25,000 Speaker 1: liked to do was build um rat and mouse utopias. 548 00:32:25,280 --> 00:32:28,440 Speaker 1: He've been doing it since the forties and basically with 549 00:32:28,520 --> 00:32:31,800 Speaker 1: the aim to see what would happen to a population, 550 00:32:31,880 --> 00:32:34,920 Speaker 1: in this case mice or rats if you gave them 551 00:32:34,960 --> 00:32:39,160 Speaker 1: a perfect mouse world. And he called these world Universes. 552 00:32:40,000 --> 00:32:42,040 Speaker 1: And the one in nineteen seventy two, the one that 553 00:32:42,120 --> 00:32:46,800 Speaker 1: really like made all the headlines I guess, was called Universe, 554 00:32:50,400 --> 00:32:52,680 Speaker 1: and it was pretty good size. It was a hundred 555 00:32:52,880 --> 00:32:56,160 Speaker 1: over a hundred inches square. Um. The walls were fifty 556 00:32:56,160 --> 00:33:01,200 Speaker 1: four inches high. It had space for um, let's see, 557 00:33:01,520 --> 00:33:05,720 Speaker 1: what's two hundred fifty six times fifteen chuck. Um, I'm 558 00:33:05,720 --> 00:33:09,280 Speaker 1: gonna go with about in my head. I'm gonna say 559 00:33:09,320 --> 00:33:15,360 Speaker 1: like close to thirty. It is exactly hundred. Yeah, that's 560 00:33:15,360 --> 00:33:19,200 Speaker 1: what I meant. I meant three thousand, hundred forty okay 561 00:33:19,280 --> 00:33:22,760 Speaker 1: okay um. So there was enough room comfortably for thirty 562 00:33:22,840 --> 00:33:27,680 Speaker 1: eight hundred and forty mice, yes, um. And long before 563 00:33:27,720 --> 00:33:31,320 Speaker 1: that he introduced four breeding pairs, so eight mice he 564 00:33:31,440 --> 00:33:35,800 Speaker 1: first introduced to Universe, and it was well stocked by 565 00:33:35,800 --> 00:33:38,200 Speaker 1: the way. They had everything. They wood, water that was 566 00:33:38,240 --> 00:33:41,200 Speaker 1: cleaned out. They were all disease free. No predators, yeah, 567 00:33:41,280 --> 00:33:43,400 Speaker 1: no yah. He threw a cat in there one right, 568 00:33:43,440 --> 00:33:45,480 Speaker 1: just to keep him on their toes or something. Yeah, 569 00:33:45,480 --> 00:33:47,440 Speaker 1: I mean it was. It was mouse Heaven is what 570 00:33:47,480 --> 00:33:50,120 Speaker 1: they called it. Yes, And he actually did in papers 571 00:33:50,120 --> 00:33:52,640 Speaker 1: about these universes. He would refer to them as heaven 572 00:33:52,720 --> 00:33:55,840 Speaker 1: or utopia, and he would use words like that. Um. 573 00:33:56,040 --> 00:33:58,920 Speaker 1: So he introduces these for breeding pairs of mice to 574 00:33:59,240 --> 00:34:03,760 Speaker 1: UM to verse twenty five and um. After a hundred 575 00:34:03,760 --> 00:34:06,280 Speaker 1: and four days, it took them to finally settle down 576 00:34:06,680 --> 00:34:08,879 Speaker 1: and be like, Okay, this place is actually pretty great. 577 00:34:08,920 --> 00:34:11,680 Speaker 1: It's not too good to be true, um, despite the 578 00:34:11,719 --> 00:34:14,000 Speaker 1: fact that it seems to be built by human hand, 579 00:34:14,760 --> 00:34:18,359 Speaker 1: which is weird, and the temperature never changes. But we're 580 00:34:18,400 --> 00:34:21,719 Speaker 1: just gonna say it's probably fine and start breeding. And 581 00:34:21,760 --> 00:34:25,920 Speaker 1: they started breeding pretty quickly. Yes, they started doubling in 582 00:34:25,960 --> 00:34:29,759 Speaker 1: population every fifty five days after that, right, Yeah, like 583 00:34:29,800 --> 00:34:31,719 Speaker 1: you said, because it was so great there, they were 584 00:34:31,760 --> 00:34:35,239 Speaker 1: just like, hey, let's eat and uh do it and 585 00:34:35,320 --> 00:34:38,120 Speaker 1: make a little baby mice. Like you know, there is 586 00:34:38,120 --> 00:34:42,200 Speaker 1: no end in sight, so you're doubling every fifty five days. Uh. 587 00:34:42,239 --> 00:34:44,920 Speaker 1: This is all a big study to study what overpopulation, 588 00:34:45,560 --> 00:34:48,080 Speaker 1: what would happen. And what he found time after time 589 00:34:48,760 --> 00:34:53,720 Speaker 1: was that things went bad. Yeah, which is really something 590 00:34:53,920 --> 00:34:58,600 Speaker 1: because remember Paul Airic released the population bomb in but 591 00:34:58,800 --> 00:35:05,319 Speaker 1: for decades before that, John Calhoun saw firsthand what the 592 00:35:05,400 --> 00:35:09,840 Speaker 1: real problem was. The real problem wasn't over population leading 593 00:35:09,880 --> 00:35:14,680 Speaker 1: to scarcity of food and conflicts, conflict and resource wars 594 00:35:15,080 --> 00:35:18,360 Speaker 1: and famine and starvation. What he found was that the 595 00:35:18,400 --> 00:35:23,440 Speaker 1: real problem was over population itself, but just too many, 596 00:35:23,600 --> 00:35:27,319 Speaker 1: too many mice, and not enough valuable roles for mice 597 00:35:27,440 --> 00:35:30,200 Speaker 1: to play exactly, so there comes to be a point 598 00:35:30,360 --> 00:35:33,960 Speaker 1: in any mouse population. As far as Calhoun was concerned. 599 00:35:33,960 --> 00:35:36,440 Speaker 1: And again, this is the universe twenty five and he 600 00:35:36,480 --> 00:35:38,359 Speaker 1: wasn't making like one a week or something. These were 601 00:35:38,400 --> 00:35:41,280 Speaker 1: detailed or smart studies. He was hired by the National 602 00:35:41,360 --> 00:35:43,520 Speaker 1: Institutes of Health. He spent like twenty or thirty years 603 00:35:43,560 --> 00:35:48,440 Speaker 1: working there. He was like a bona fide legitimate researcher um, 604 00:35:48,480 --> 00:35:53,080 Speaker 1: and he would find that at some point the abundance 605 00:35:53,120 --> 00:35:56,719 Speaker 1: would lead to overpopulation rather than scarcely. Like he he 606 00:35:57,320 --> 00:35:59,640 Speaker 1: never ran out of food. They always had enough food 607 00:35:59,640 --> 00:36:01,720 Speaker 1: and water and everything. What came to be an issue 608 00:36:01,719 --> 00:36:05,160 Speaker 1: with space and social interactions. There were just too many people. 609 00:36:05,719 --> 00:36:08,439 Speaker 1: There are too many mice, I should say to the mice. 610 00:36:08,480 --> 00:36:12,320 Speaker 1: There people, sure, um, And they're rubbing shoulders up against 611 00:36:12,360 --> 00:36:16,799 Speaker 1: one another, constantly moving past one another. There's not enough room. 612 00:36:16,880 --> 00:36:20,799 Speaker 1: And like you said, there wasn't enough. Um, there were 613 00:36:20,880 --> 00:36:28,319 Speaker 1: too many mice to fulfill the number of social roles needed. Right. Yeah, 614 00:36:28,400 --> 00:36:30,680 Speaker 1: it says by day three fifteen, so this is close 615 00:36:30,719 --> 00:36:33,799 Speaker 1: to a year. Um. A lot of mice are living 616 00:36:33,840 --> 00:36:36,600 Speaker 1: in there. And they said there were more peers to 617 00:36:36,680 --> 00:36:41,520 Speaker 1: defend against. So males were stressed out and stopped defending 618 00:36:41,520 --> 00:36:45,640 Speaker 1: their territory. They abandoned it. Uh said normal social discourse, 619 00:36:45,840 --> 00:36:51,399 Speaker 1: UM broke down completely. Social bonds broke down. UM. There 620 00:36:51,480 --> 00:36:56,040 Speaker 1: was like randomized violence for no reason. It seemed like. Um. 621 00:36:56,520 --> 00:36:59,840 Speaker 1: The female mice, the mothers saw this and would attack 622 00:37:00,000 --> 00:37:05,080 Speaker 1: our own babies. And it was procreation slumped, infant abandonment, 623 00:37:05,160 --> 00:37:09,439 Speaker 1: increase mortality sword um. Then he talked about the beautiful ones, 624 00:37:09,480 --> 00:37:12,239 Speaker 1: which I thought was hysterical. There were these male mice 625 00:37:12,320 --> 00:37:15,600 Speaker 1: that just they never fought, They never sought to reproduce 626 00:37:15,680 --> 00:37:17,960 Speaker 1: or have sex. All they did was eat, sleep and 627 00:37:18,000 --> 00:37:21,759 Speaker 1: groom and just sort of loaf around. So all these 628 00:37:21,760 --> 00:37:25,360 Speaker 1: social barriers are completely being destroyed, these social norms, I 629 00:37:25,360 --> 00:37:28,359 Speaker 1: should say. Yeah, and these the the females that could 630 00:37:28,360 --> 00:37:32,320 Speaker 1: reproduce one off by themselves to quester themselves away from society. 631 00:37:32,400 --> 00:37:34,920 Speaker 1: And the males that were capable of reproducing became those 632 00:37:34,920 --> 00:37:38,880 Speaker 1: beautiful ones and didn't seek sex either. So over time 633 00:37:39,239 --> 00:37:42,640 Speaker 1: they lost their ability to carry out these complex social 634 00:37:42,640 --> 00:37:46,440 Speaker 1: interactions that lead to reproduction, and they just stopped reproducing 635 00:37:46,440 --> 00:37:49,480 Speaker 1: it in general. Yeah, by day five sixty and this 636 00:37:49,520 --> 00:37:54,480 Speaker 1: is um, I guess that's the close to two year mark. Um, well, 637 00:37:54,520 --> 00:37:59,959 Speaker 1: I guess eighteen months they had mice and then growth ceased. Yeah, 638 00:38:00,000 --> 00:38:03,239 Speaker 1: which is even close to the thirty that this place 639 00:38:03,280 --> 00:38:06,360 Speaker 1: could could conceivably hang on to. Yeah, So it was 640 00:38:06,640 --> 00:38:12,640 Speaker 1: how many was they stopped reproducing? Um? Very few My 641 00:38:12,800 --> 00:38:17,520 Speaker 1: survive pass weaning at that point. The beautiful ones were 642 00:38:17,520 --> 00:38:21,160 Speaker 1: still secluded, the females that they basically called this the 643 00:38:21,160 --> 00:38:25,479 Speaker 1: first death of two deaths. He did specifically social death 644 00:38:25,600 --> 00:38:28,560 Speaker 1: essentially exactly like the death of the spirit, the death 645 00:38:28,560 --> 00:38:32,960 Speaker 1: of the society, and then eventually the physical death the 646 00:38:32,960 --> 00:38:35,879 Speaker 1: second death. Yeah, the one leads to the second, like 647 00:38:36,400 --> 00:38:39,200 Speaker 1: there is a point that you pass, and he came 648 00:38:39,280 --> 00:38:41,000 Speaker 1: up with a great name for it, called the behavioral 649 00:38:41,040 --> 00:38:45,359 Speaker 1: sink um where they think they refer to it as 650 00:38:45,400 --> 00:38:48,200 Speaker 1: the event horizon. Once you pass that, it's all over, right, 651 00:38:48,520 --> 00:38:51,000 Speaker 1: there's no coming back from that, and once there's no 652 00:38:51,080 --> 00:38:54,400 Speaker 1: coming back from that, not only has your society collapsed, 653 00:38:54,520 --> 00:38:59,120 Speaker 1: or does your society collapse? Um, you your population becomes 654 00:38:59,160 --> 00:39:03,560 Speaker 1: extinct because reproduction becomes impossible even he found, which is 655 00:39:03,600 --> 00:39:08,040 Speaker 1: pretty startling. He found that even after enough of the 656 00:39:08,080 --> 00:39:11,720 Speaker 1: population dies off that it returns to those potable, ideal 657 00:39:11,840 --> 00:39:14,560 Speaker 1: numbers of the early days in Universe twenty five or 658 00:39:14,560 --> 00:39:18,080 Speaker 1: any of the universes, they still don't reproduction doesn't start 659 00:39:18,120 --> 00:39:21,919 Speaker 1: up again because remember, social norms and bonds have broken down, 660 00:39:23,040 --> 00:39:26,480 Speaker 1: so they can't even figure out how to reproduce once 661 00:39:26,600 --> 00:39:30,560 Speaker 1: there's room for people enough again. It's it is so interesting, 662 00:39:30,600 --> 00:39:32,839 Speaker 1: he said that. Um. He wrote he wrote this really 663 00:39:33,600 --> 00:39:37,720 Speaker 1: kind of blockbuster paper called Population Density and Social Pathology, 664 00:39:37,800 --> 00:39:40,799 Speaker 1: and it was published in Scientific American in nineteen sixty two, 665 00:39:41,120 --> 00:39:43,960 Speaker 1: and he said that the individuals that are born under 666 00:39:44,000 --> 00:39:47,440 Speaker 1: these circumstances will be so out of touch with reality 667 00:39:47,719 --> 00:39:51,319 Speaker 1: as to be incapable even of alienation, so like they 668 00:39:51,320 --> 00:39:54,080 Speaker 1: can't even feel like they're not connected as society anymore, 669 00:39:54,120 --> 00:39:57,680 Speaker 1: because there's no society for them to ever connect or 670 00:39:57,760 --> 00:40:01,520 Speaker 1: disconnect from. It's right, it really is. And a lot 671 00:40:01,520 --> 00:40:05,640 Speaker 1: of people jumped on this and said, whoa, what's going 672 00:40:05,680 --> 00:40:08,440 Speaker 1: on here, because if you look at his data, every 673 00:40:08,480 --> 00:40:11,879 Speaker 1: time he ran this experiment, the results became the same. 674 00:40:12,440 --> 00:40:16,040 Speaker 1: There was an abundance of resources, there was never scarcity. 675 00:40:16,440 --> 00:40:20,120 Speaker 1: Population became overpopulation. Once they reached the point of the 676 00:40:20,120 --> 00:40:24,960 Speaker 1: behavioral sink, the population slid into extinction. And on the 677 00:40:25,000 --> 00:40:30,399 Speaker 1: way there was violence, cannibalism um like uh and sexualism 678 00:40:31,080 --> 00:40:35,360 Speaker 1: in fanticide um just like all the horrible things you 679 00:40:35,360 --> 00:40:39,160 Speaker 1: can possibly think of, um, right, you know, on the 680 00:40:39,200 --> 00:40:41,839 Speaker 1: way towards extinction. And so a lot of people said, 681 00:40:42,120 --> 00:40:45,040 Speaker 1: you know, these mice kind of a reflective of our 682 00:40:45,080 --> 00:40:49,680 Speaker 1: own society, don't you think and um, Calhoun was kind 683 00:40:49,680 --> 00:40:52,520 Speaker 1: of like, yeah, I would say that's probably correct. Yeah. 684 00:40:52,560 --> 00:40:54,920 Speaker 1: And there was a big boom at the time because 685 00:40:54,920 --> 00:40:58,239 Speaker 1: of this experiment in literature and movies with a lot 686 00:40:58,239 --> 00:41:02,120 Speaker 1: of doomsday uh areas uh. Tom Wolf, the Great writer 687 00:41:02,880 --> 00:41:06,680 Speaker 1: wrote in The Pump House Gang in nine UH he 688 00:41:06,760 --> 00:41:11,200 Speaker 1: actually referenced the behavioral sink um and uh in reference 689 00:41:11,239 --> 00:41:14,040 Speaker 1: to New York City, and he said, I got to uh, 690 00:41:14,239 --> 00:41:16,240 Speaker 1: it was easy to look at New Yorkers as animals, 691 00:41:16,400 --> 00:41:18,919 Speaker 1: especially looking down from someplace like a balcony at Grand 692 00:41:18,960 --> 00:41:21,759 Speaker 1: Central at the rush hour Friday afternoon and the floor 693 00:41:21,800 --> 00:41:24,960 Speaker 1: was filled with poor white humans running around, dodging, blinking 694 00:41:24,960 --> 00:41:27,120 Speaker 1: their eyes, making a sound like a pinfull of starlings 695 00:41:27,200 --> 00:41:30,320 Speaker 1: or rats or something. And there are all these movies 696 00:41:30,360 --> 00:41:34,880 Speaker 1: that came out. There was one called ZPG with Oliver 697 00:41:34,960 --> 00:41:40,239 Speaker 1: Reed and Geraldine Chapman Chaplain that was called Zero Population Growth. Yeah, 698 00:41:40,280 --> 00:41:42,839 Speaker 1: like for a generation the government said no, one's allowed 699 00:41:42,880 --> 00:41:45,360 Speaker 1: to have babies. Here's your robot baby, right, and they're like, no, 700 00:41:45,400 --> 00:41:46,880 Speaker 1: we're gonna have a real baby. And they're like, no, 701 00:41:46,960 --> 00:41:50,520 Speaker 1: you're not. Um, I think it. I didn't see, but 702 00:41:50,560 --> 00:41:53,319 Speaker 1: I'm sure it ended very portly. I didn't see it either. Yeah. 703 00:41:53,680 --> 00:41:56,319 Speaker 1: I saw it on IMDb though. And of course, of 704 00:41:56,360 --> 00:42:01,280 Speaker 1: course Soilent Green. Yeah, great, great movie from the novel 705 00:42:01,400 --> 00:42:07,520 Speaker 1: Make Room, Make Room. And there's there's another novel called 706 00:42:07,560 --> 00:42:12,560 Speaker 1: stand On Zanzibar, and um, there were people called muckers 707 00:42:12,600 --> 00:42:15,799 Speaker 1: who ran them up and just suddenly went crazy and 708 00:42:15,840 --> 00:42:18,760 Speaker 1: started killing a bunch of people. Oh no, what happens. 709 00:42:18,800 --> 00:42:21,160 Speaker 1: From time to time in the news, a lot of 710 00:42:21,160 --> 00:42:25,280 Speaker 1: people would were saying, Yeah, the stuff that Calhoun's finding 711 00:42:25,800 --> 00:42:32,560 Speaker 1: is clearly extrapolateable onto human society, and at the time 712 00:42:32,640 --> 00:42:34,759 Speaker 1: too there was a lot of discussion about what to 713 00:42:34,800 --> 00:42:40,960 Speaker 1: do about um, inner city over population, crime, housing projects. UM. 714 00:42:41,000 --> 00:42:43,680 Speaker 1: There's this really great documentary called The pruitt I go 715 00:42:43,880 --> 00:42:47,239 Speaker 1: Myth and it's about there was this the pruitt I 716 00:42:47,360 --> 00:42:52,759 Speaker 1: Go UM project in St. Louis became I think we've 717 00:42:52,760 --> 00:42:57,920 Speaker 1: talked about it before, but it became like the the 718 00:42:58,120 --> 00:43:01,080 Speaker 1: the poster child for how no matter what you do 719 00:43:01,280 --> 00:43:04,080 Speaker 1: for poor inner city people, they're gonna screw it up 720 00:43:04,120 --> 00:43:06,600 Speaker 1: and it's gonna become crime ridden. And it's them. It's 721 00:43:06,640 --> 00:43:09,920 Speaker 1: not it's not the their their quality of life or 722 00:43:10,080 --> 00:43:13,560 Speaker 1: education or anything like that. It's them. And this this 723 00:43:13,560 --> 00:43:17,399 Speaker 1: this documentary just totally demolishes that idea, but it's still 724 00:43:17,400 --> 00:43:20,200 Speaker 1: a longstanding idea. And there were a group of policy 725 00:43:20,680 --> 00:43:24,680 Speaker 1: policymakers who looked at Calhoun's research and said, clearly, we 726 00:43:24,719 --> 00:43:27,040 Speaker 1: need to we need to do something. There's there's too 727 00:43:27,040 --> 00:43:29,799 Speaker 1: many people, and there's a lot of people who don't 728 00:43:29,840 --> 00:43:33,960 Speaker 1: have um valuable social roles and they're turning a crime 729 00:43:33,960 --> 00:43:38,160 Speaker 1: and everything. UM. It was very much open to interpretation 730 00:43:38,280 --> 00:43:40,680 Speaker 1: because Calhoun, even though he was putting these things in 731 00:43:40,800 --> 00:43:45,040 Speaker 1: terms like heaven and utopia and hell and behavioral sink 732 00:43:45,080 --> 00:43:47,160 Speaker 1: and that kind of stuff. He was still just kind 733 00:43:47,160 --> 00:43:49,400 Speaker 1: of putting data out there and it was up to 734 00:43:49,680 --> 00:43:51,840 Speaker 1: society at large or interpreted, and it really said a 735 00:43:51,880 --> 00:43:54,480 Speaker 1: lot about your attitudes towards your fellow human how you 736 00:43:54,520 --> 00:43:58,799 Speaker 1: interpreted it. But Calhoun himself actually took something of an 737 00:43:58,800 --> 00:44:01,799 Speaker 1: optimistic view of all of this data, which is kind 738 00:44:01,800 --> 00:44:04,480 Speaker 1: of mind boggling. Yeah, I was surprised to read this actually, 739 00:44:04,520 --> 00:44:06,919 Speaker 1: he Um, it makes sense that if you think about it. Yeah. 740 00:44:06,960 --> 00:44:09,959 Speaker 1: He found that there were outliers and that not all 741 00:44:10,160 --> 00:44:16,160 Speaker 1: the mice descended into a hellish violence and looting and 742 00:44:16,320 --> 00:44:19,080 Speaker 1: mouse looting. He found that some could actually handle this 743 00:44:19,600 --> 00:44:21,480 Speaker 1: and what he called the ones that could had a 744 00:44:21,560 --> 00:44:25,839 Speaker 1: high social velocity, UM, mice that fared well with a 745 00:44:25,840 --> 00:44:28,319 Speaker 1: lot of high number of social interactions. And that is 746 00:44:28,360 --> 00:44:31,840 Speaker 1: not me. And he said, I'm a type, A blood type, 747 00:44:32,360 --> 00:44:36,799 Speaker 1: blood personality type. Uh. He said that basically, these mice 748 00:44:36,840 --> 00:44:39,120 Speaker 1: will thrive. Um. And he said, and even the ones 749 00:44:39,120 --> 00:44:43,040 Speaker 1: who don't, what he termed the losers, um, found ways 750 00:44:43,080 --> 00:44:46,520 Speaker 1: to be more creative. And he sufficient, Yeah, he had 751 00:44:46,520 --> 00:44:50,120 Speaker 1: a sunny your outlook, basically saying that man is essentially 752 00:44:50,160 --> 00:44:54,040 Speaker 1: a positive animal and we will create and design our 753 00:44:54,080 --> 00:44:57,920 Speaker 1: own solutions, right, and his solution was since and it 754 00:44:58,000 --> 00:45:02,080 Speaker 1: makes sense because he own that it's not scarcity or 755 00:45:02,160 --> 00:45:07,240 Speaker 1: famines or anything that leads to trouble, it's overpopulation itself. 756 00:45:07,760 --> 00:45:10,520 Speaker 1: His idea was, well, let's go find more space. And 757 00:45:10,600 --> 00:45:12,440 Speaker 1: so he was a member of this group called the 758 00:45:12,440 --> 00:45:14,400 Speaker 1: Space Cadets, which was a group of thinkers that we're 759 00:45:14,400 --> 00:45:17,040 Speaker 1: trying to figure out how to establish colonies on like 760 00:45:17,320 --> 00:45:21,160 Speaker 1: Mars or the Moon or wherever, which is exactly what 761 00:45:21,239 --> 00:45:24,280 Speaker 1: Calhoun's point was, is that we just need more space. 762 00:45:24,880 --> 00:45:27,440 Speaker 1: As long as we can sustain ourselves, that's fine. But 763 00:45:27,680 --> 00:45:32,280 Speaker 1: even if we don't stress agriculture, the planet or whatever, 764 00:45:32,480 --> 00:45:34,680 Speaker 1: we're still going to run into problems. So let's go 765 00:45:35,239 --> 00:45:39,399 Speaker 1: off to other worlds and terror form. Oh and did 766 00:45:39,400 --> 00:45:42,080 Speaker 1: you see the thing about the rats of nim Oh? 767 00:45:42,280 --> 00:45:46,320 Speaker 1: Was that taken it? It was based directly on his research, 768 00:45:48,040 --> 00:45:50,880 Speaker 1: Mrs Brisbee and the Rats of nim Nice. Yes, So 769 00:45:51,040 --> 00:45:54,560 Speaker 1: go see that again and also go read the Behavioral Sink, 770 00:45:54,800 --> 00:45:58,520 Speaker 1: Super interesting, an article on Cabinet by Will Wiles that 771 00:45:58,960 --> 00:46:02,359 Speaker 1: informed a lot of episode. Yeah, this stuff is fascinating 772 00:46:02,400 --> 00:46:06,600 Speaker 1: to me because I see kind of both sides. Um 773 00:46:06,640 --> 00:46:09,399 Speaker 1: clearly there are some issues going right now, and uh, 774 00:46:09,800 --> 00:46:13,120 Speaker 1: but I also think that there are solutions around the corner. Yeah. 775 00:46:13,239 --> 00:46:16,360 Speaker 1: I ultimately don't have a strong opinion either way, and 776 00:46:16,400 --> 00:46:19,600 Speaker 1: I think if I think about it, it's because I 777 00:46:20,080 --> 00:46:24,520 Speaker 1: think humans will, yeah, become an ingenuitouve. You can have 778 00:46:24,520 --> 00:46:31,040 Speaker 1: steak tonight, me too, grass fed only you know, it 779 00:46:31,160 --> 00:46:33,880 Speaker 1: doesn't make it any better. I mean that's why beef 780 00:46:33,960 --> 00:46:36,239 Speaker 1: is so it uses so much because it eats so 781 00:46:36,400 --> 00:46:39,799 Speaker 1: much food that also requires water. Right, it requires water 782 00:46:39,880 --> 00:46:43,560 Speaker 1: like two times over at least the dumb cows. Yeah, 783 00:46:43,800 --> 00:46:46,160 Speaker 1: does you feel bad about our steak consumption? Chuck, I 784 00:46:46,160 --> 00:46:48,839 Speaker 1: don't need much steak. Good for you, buddy, It's because 785 00:46:48,880 --> 00:46:51,839 Speaker 1: Emily doesn't eat beef. So oh yeah, you know, usually 786 00:46:51,880 --> 00:46:54,040 Speaker 1: I just will cook chicken because it's not like I'll 787 00:46:54,040 --> 00:46:55,840 Speaker 1: have a steak and I'll cook work chicken every now 788 00:46:55,920 --> 00:46:58,960 Speaker 1: and then. But usually it's just easier because chicken comes 789 00:46:58,960 --> 00:47:01,120 Speaker 1: in like a two or three pack, right, you know. Yah, 790 00:47:01,960 --> 00:47:03,799 Speaker 1: Plus you cook it until it's dry as a bone, 791 00:47:03,840 --> 00:47:07,080 Speaker 1: so you can feel better about the water consumption, that's right. Uh. 792 00:47:07,080 --> 00:47:09,920 Speaker 1: If you want to know more about population growth and 793 00:47:10,000 --> 00:47:13,480 Speaker 1: specifically zero population growth type, those words into the search 794 00:47:13,480 --> 00:47:15,680 Speaker 1: bar house to works dot com and don't forget to 795 00:47:15,719 --> 00:47:17,719 Speaker 1: go to stuff you shaulow dot com and listen to 796 00:47:17,760 --> 00:47:20,920 Speaker 1: this episode and check out the extra great links on 797 00:47:20,960 --> 00:47:23,360 Speaker 1: there too. Uh. And since I said search bar in 798 00:47:23,400 --> 00:47:27,719 Speaker 1: there somewhere, it's time for listener mail. I'm gonna call 799 00:47:27,800 --> 00:47:32,200 Speaker 1: this linguists sticks up for us, all right? Right? Hey, 800 00:47:32,200 --> 00:47:35,320 Speaker 1: guys studied linguistics in college, so it always pickles me 801 00:47:35,360 --> 00:47:37,400 Speaker 1: when you guys go on tangents about words and language. 802 00:47:37,840 --> 00:47:39,560 Speaker 1: The main reason I'm writing is because I want to 803 00:47:39,560 --> 00:47:42,160 Speaker 1: offer you a counterpoint to the language police that have 804 00:47:42,239 --> 00:47:46,480 Speaker 1: been harshing your vibe. Grammar nuts are what we call 805 00:47:46,600 --> 00:47:50,840 Speaker 1: in the biz. Uh, prescriptivists, um, who like to dictate 806 00:47:50,960 --> 00:47:54,239 Speaker 1: how people should speak. Linguists, on the other hand, are 807 00:47:54,560 --> 00:47:59,040 Speaker 1: descriptivists who make their careers out of how people actually 808 00:47:59,120 --> 00:48:02,280 Speaker 1: speak in real war old situations. Oh, I didn't realize. 809 00:48:02,280 --> 00:48:05,040 Speaker 1: I thought linguists could be one or the other. I 810 00:48:05,040 --> 00:48:08,719 Speaker 1: didn't realize that like linguists tend to be descriptive ists. 811 00:48:09,040 --> 00:48:12,480 Speaker 1: That's what she says. What is um who wrote Infinite 812 00:48:12,520 --> 00:48:16,600 Speaker 1: Jess David Foster Wallace. He was a big time prescriptivists, 813 00:48:16,800 --> 00:48:18,839 Speaker 1: really he used to drive him crazy, like how people 814 00:48:18,880 --> 00:48:22,680 Speaker 1: should speak? Yeah, like that, there is a a specific 815 00:48:22,760 --> 00:48:25,640 Speaker 1: way that humans are supposed to speak and right, right 816 00:48:25,680 --> 00:48:29,040 Speaker 1: and communicate, and if you dedate from that, you're about 817 00:48:29,080 --> 00:48:31,440 Speaker 1: as bad as human being and that would be like 818 00:48:31,480 --> 00:48:35,200 Speaker 1: the downfall of society or pretty much on um. We 819 00:48:35,200 --> 00:48:37,560 Speaker 1: don't use the terms good or bad grammar. Instead, we 820 00:48:37,640 --> 00:48:42,160 Speaker 1: prefer standard and non standard Linguists recognize the social functions 821 00:48:42,200 --> 00:48:46,520 Speaker 1: of non standard grammars and observe their uses and functions 822 00:48:46,600 --> 00:48:49,800 Speaker 1: rather than to try and micromanage them. A final point, 823 00:48:50,120 --> 00:48:52,440 Speaker 1: I'm certain your listeners still know what you mean when 824 00:48:52,480 --> 00:48:55,080 Speaker 1: you say things like there's a lot of something, even 825 00:48:55,120 --> 00:48:58,080 Speaker 1: if it isn't standard grammar and the laws of linguistics, 826 00:48:58,440 --> 00:49:08,960 Speaker 1: as long as you're interlocuature, which is a listener interlocutor interlocutor. Yeah, 827 00:49:09,280 --> 00:49:11,080 Speaker 1: as long as they accurately understand what you mean, you 828 00:49:11,120 --> 00:49:14,800 Speaker 1: have successfully communicated. And that's why humans had been in language, 829 00:49:14,840 --> 00:49:17,560 Speaker 1: isn't it. So go be free and know that I 830 00:49:17,600 --> 00:49:19,560 Speaker 1: will always love your show no matter how you speak. 831 00:49:19,600 --> 00:49:22,720 Speaker 1: And that is from Kristen. Thanks Kristen. The supportive linguists 832 00:49:22,760 --> 00:49:26,200 Speaker 1: appreciate that that's funny that Kristen mentioned that as long 833 00:49:26,280 --> 00:49:31,920 Speaker 1: as your interlocutor understands what you're saying, you're communicating correctly. Um, 834 00:49:32,000 --> 00:49:33,919 Speaker 1: someone else, I don't remember who it was, they wrote 835 00:49:33,920 --> 00:49:37,000 Speaker 1: in and suggested we do an episode on shorthand. Oh interested. 836 00:49:37,000 --> 00:49:39,160 Speaker 1: I was just talking about that with Emily last night. Bam, 837 00:49:39,239 --> 00:49:41,200 Speaker 1: it's all over the place. I took speed writing in 838 00:49:41,239 --> 00:49:43,640 Speaker 1: high school and she was, did you very surprised at that? 839 00:49:43,880 --> 00:49:48,840 Speaker 1: So like speedwriting with hands? Speedwriting is like like stenography, No, 840 00:49:49,440 --> 00:49:53,480 Speaker 1: right with your hand. Um, it's basically a version of shorthand, 841 00:49:53,480 --> 00:49:58,000 Speaker 1: but not exact shorthand. Got you. It's a kind of shorthand. 842 00:49:58,440 --> 00:50:01,680 Speaker 1: It sounds like shorthand, but like more aggressive. Yeah, like 843 00:50:01,880 --> 00:50:05,360 Speaker 1: max power or something. The joke was my friend Shannon, 844 00:50:06,120 --> 00:50:09,040 Speaker 1: I won't see her last name, but she would cheat 845 00:50:09,080 --> 00:50:12,799 Speaker 1: and class because she didn't learn the shorthand. So the 846 00:50:12,880 --> 00:50:16,040 Speaker 1: test where they would just read a long passage quickly 847 00:50:16,040 --> 00:50:18,359 Speaker 1: and you would have to do it and then transcribe 848 00:50:18,400 --> 00:50:22,279 Speaker 1: that into longhand. She was just super good at writing 849 00:50:22,280 --> 00:50:25,319 Speaker 1: really fast, so she would just write down everything in 850 00:50:25,320 --> 00:50:28,160 Speaker 1: longhand super fast and then figure out how to transcribe 851 00:50:28,160 --> 00:50:30,719 Speaker 1: it back to shorthand and then back to Longhand and 852 00:50:30,800 --> 00:50:33,080 Speaker 1: she she got caught doing that. Yeah, and the teachers 853 00:50:33,080 --> 00:50:35,719 Speaker 1: like that's cheating. Yeah. It sounds like she was like, 854 00:50:35,760 --> 00:50:41,080 Speaker 1: well name with fast. Nope, that's not speedwriting, that's just 855 00:50:41,160 --> 00:50:44,799 Speaker 1: writing fast. Uh. If you want to get in touch 856 00:50:44,840 --> 00:50:47,520 Speaker 1: with us, either to show us support, criticize us, and 857 00:50:47,680 --> 00:50:50,239 Speaker 1: even something neutral is fine, you can tweet to us 858 00:50:50,239 --> 00:50:52,520 Speaker 1: at s y s K podcast. You can join us 859 00:50:52,560 --> 00:50:54,799 Speaker 1: on Facebook dot com, slash stuff you Should Know. You 860 00:50:54,840 --> 00:50:57,279 Speaker 1: can send us an email to Stuff Podcast at how 861 00:50:57,320 --> 00:50:59,680 Speaker 1: stuff Works dot com and has always joined us at 862 00:50:59,680 --> 00:51:02,040 Speaker 1: our look Curious home on the web, Stuff you Should 863 00:51:02,040 --> 00:51:09,480 Speaker 1: Know dot com. For more on this and thousands of 864 00:51:09,480 --> 00:51:19,560 Speaker 1: other topics, is it how stuff Works dot com