Speaker 1: Welcome to the nonprofits again. For the third and final
Speaker 1: segment this week, we set aside the active combat zone
Speaker 1: that is the American educational system and look at something
Speaker 1: a little bit more concrete, global population. There can't be
Speaker 1: any disagreements on that, Ken there, Eli Slack, Please tell
Speaker 1: me there are some things in this world we can
Speaker 1: all agree on absolutely, And.
Speaker 2: Now it's time for the song of My people. Science
Speaker 2: Josiah Slang Ridder, a postdoc researcher from Alto University in Finland,
Speaker 2: and some others are suggesting that the Earth might contain
Speaker 2: significantly more humans than we think. Ridder's paper, published in
Speaker 2: Nature Communications, took data from rural dam projects, where companies
Speaker 2: know exactly how many people they displaced to build the
Speaker 2: dams because they had to pay each of them for
Speaker 2: displacing them, And then they compared that data to official
Speaker 2: estimates of populations and found that official estimates undershot the
Speaker 2: more precise damn project data by between fifty three to
Speaker 2: eighty four percent, depending on the area. Now, on the surface,
Speaker 2: this seems to me like solid reasoning, but experts are
Speaker 2: cautiously skeptical, noting that wow, there's good reason to invest
Speaker 2: more research. Into rural populations. Having a correction on the
Speaker 2: order of a few billion people is a little bit
Speaker 2: outside of the realm of reality for the first preliminary data.
Speaker 2: This story is from Popular Mechanics by Darren Orf on
Speaker 2: June twenty first, twenty twenty five.
Speaker 1: All right, and we're going to come right back to
Speaker 1: you with the questioning beginning with Eli, the science guy,
Speaker 1: Eli the Chris.
Speaker 3: Where the hell is Eli's theme song Scott, Get out
Speaker 3: of your dream World? You know we don't have the
Speaker 3: budget for that kind of a thing.
Speaker 1: All right, all right, well, Eli, anyway, as a fellow nerd,
Speaker 1: what's your take on this?
Speaker 3: It's interesting that that was a bad joke.
Speaker 2: Sorry, continue, It's interesting to me. I like the method.
Speaker 2: I think he knows or suspects at least that the
Speaker 2: damn prod that the companies building the dams are going
Speaker 2: to have more precise and verifiable, honestly records about how
Speaker 2: many people were there because they had to pay them, so,
Speaker 2: they needed bank accounts, they needed addresses, they needed to
Speaker 2: know how many people were in each home, and all
Speaker 2: things like that. So when you compare that to estimates
Speaker 2: from organizations like World pop or GWP, grump, land Scan
Speaker 2: and GHS pop which.
Speaker 3: Sounds like international.
Speaker 2: Yeah, grump sound like international like pop bands in a way.
Speaker 2: But he found the discrepancy, he said, he said, hey, look,
Speaker 2: and it was significant, and so it got published. And
Speaker 2: it does matter because we allocate funds to rural areas
Speaker 2: based on their population densities. So for underrepresenting them, we
Speaker 2: are under serving them. But I think it is also
Speaker 2: a good representation of a scientific method, because we saw
Speaker 2: in the article. He had some criticism from Hong Kong
Speaker 2: University of Science and Technology. A researcher named Stuart geigle
Speaker 2: Baston said, essentially, I'm kind of, you know, extrapolating from
Speaker 2: what he said, but just because it's compelling, that doesn't
Speaker 2: mean that it's true. You know, it's something, it's it's
Speaker 2: it's it's common for it's common to find something and
Speaker 2: think like, oh, like this is you know, if this
Speaker 2: is true, this changes everything. And the first step in
Speaker 2: that is follow that data, see why you have that
Speaker 2: discrepancy before you start making like grandiose claims.
Speaker 3: Right, yeah, exactly, Stephen, what's what's your take on this?
Speaker 1: I I think that you have a slightly less enthusiastic
Speaker 1: perspective here than Eli.
Speaker 3: So what can you add that as a counterpoint?
Speaker 4: Yeah, No, I think this is really good science for
Speaker 4: when you're sitting on the shitter. I think it's really
Speaker 4: entertaining for.
Speaker 1: It when the best science happens anyway, Right, isn't that kind.
Speaker 2: Of where you guys read for the show?
Speaker 4: No, like you know, like again like this isn't this
Speaker 4: isn't my field of expertise. But it seems to me
Speaker 4: that there are snags, there are unaccounted shortcomings in this approach,
Speaker 4: whether you're looking at areas that are specifically affected by
Speaker 4: dam so that isn't a fair representation of the global
Speaker 4: rural population, right, areas where there's going to be dams
Speaker 4: or areas where there is going to be water and
Speaker 4: there's going to be already an abnormally large number of people.
Speaker 4: So that kind of tracks with the data, it seems,
Speaker 4: and like thirty five areas is really a niche area,
Speaker 4: and especially when it's like yeah, like river based areas
Speaker 4: thirty five across the global Like, that's that's not a
Speaker 4: very in depth So you.
Speaker 1: Want to bigger you like a big sample size, is
Speaker 1: what you're saying. Steven Harder loves a big example.
Speaker 3: Size.
Speaker 4: The bigger the better. Absolutely, that's right, That's what I'm
Speaker 4: all about here, right to know, Yeah, like and if
Speaker 4: like and again like, I'm I can be an expert
Speaker 4: in everything. I can be an expert in many things.
Speaker 4: And if so, I rely on experts who actually have
Speaker 4: dug into the material to know their shit. And if
Speaker 4: the experts aren't convinced, then I find I'm like, I
Speaker 4: trust them until they have when they when they have
Speaker 4: good reason to, you know, draw a red flag around it,
Speaker 4: then then that's I think is a great time to
Speaker 4: draw more conclusions, not to start investigating, but to yeah,
Speaker 4: let's let's get a more robust understanding.
Speaker 3: Fair point, fair point. I have to have to hand
Speaker 3: that to you.
Speaker 1: So as a math teacher, of course, this article is
Speaker 1: really like just gold for me.
Speaker 3: Right.
Speaker 1: It was basically we're talking about people that messed up
Speaker 1: the math because they were making incorrect assumptions. And I
Speaker 1: love throwing those kind of problems out to my students
Speaker 1: to not only show not only to practice the math
Speaker 1: and then they have to use math to justify their arguments,
Speaker 1: but then to realize that we all make assumptions in
Speaker 1: all cases and so we need to make sure that
Speaker 1: we are aware of the assumptions that we're making, and
Speaker 1: we need to test those assumptions. So here's a situation
Speaker 1: where we had a lot of money and effort and
Speaker 1: science has gone into things like predicting world population and
Speaker 1: we discover a flaw in our system based off of
Speaker 1: faulty assumptions. That is just the math teacher mother load
Speaker 1: right there. It's just perfect learning opportunities. So I'll ask
Speaker 1: Eli here first, So what lessons can we learn from this,
Speaker 1: either generally about you know, being good scientists, or specifically
Speaker 1: about this issue. What do you think we can learn here?
Speaker 2: I think, in part, we can't always trust our measurements,
Speaker 2: and it's either because you know, these international pop bands
Speaker 2: are incorrect about the world population, or because language.
Speaker 3: I can't trust an international pop band. Who can you trust?
Speaker 2: I'm maybe maybe Josiah's lang Ritter. Maybe he's got the
Speaker 2: right answer, but.
Speaker 3: Maybe he's got Grump backing him up.
Speaker 2: Though well no, he he disagrees with Grump all right.
Speaker 3: The discrepancy.
Speaker 2: But that's what I think is when you find a
Speaker 2: discrepancy between your data and other data, somebody got it wrong.
Speaker 2: Don't assume that it's not you. I think it's it's
Speaker 2: just as it's just as plausible for it to be
Speaker 2: you as it is for it to be the other guy.
Speaker 2: And when it's you or everyone else for the past
Speaker 2: several decades, you have to realize that it's more likely
Speaker 2: for it to be you. That is wrong. But like
Speaker 2: I said earlier, find why there's a discrepancy. Find like,
Speaker 2: what what would I expect to see if there was
Speaker 2: fifty percent more people on the earth? Then I think
Speaker 2: that there are, And then go out and look for that.
Speaker 2: And if you can't find that, you know, let's reconsider.
Speaker 3: Right maybe or maybe ask me why we didn't find.
Speaker 2: It exactly exactly? Why why wouldn't we find it? Is
Speaker 2: there some reason we wouldn't have found that? Is there
Speaker 2: something else that might that I might see in the result?
Speaker 2: Like you, you can keep investigating it, but it's not
Speaker 2: quite time yet to start making, you know, drawing conclusions
Speaker 2: and like rerouting resources based on one stud.
Speaker 1: Right, Right, I think one of the themes that Eli
Speaker 1: was just talking about is the idea of intellectual humility.
Speaker 3: Right.
Speaker 1: We need to be open to the possibility that we've
Speaker 1: made mistakes because our.
Speaker 3: You know, human, we're human beings. We have egos, we
Speaker 3: have predispositions, we have biases, and so forth. Steven, I
Speaker 3: wonder if you could comment briefly on what what are
Speaker 3: your thoughts on the role of intellectual humility and that
Speaker 3: kind of thing in the scientific community and in just
Speaker 3: in general as we as the human species learn about
Speaker 3: our world and our universe. Yeah, just a tiny little
Speaker 3: question there for you.
Speaker 4: Great Like I one of the best parts about deconstructing
Speaker 4: and stepping away from the faith is the humility that
Speaker 4: I was able to tap into because when I was
Speaker 4: a Christian, I didn't need to be too too, too
Speaker 4: humble because I had all the motherfucking answers. Uh and yeah,
Speaker 4: And that was and what was interesting about you know,
Speaker 4: the looking at this article from a meta perspective is
Speaker 4: how it reminded me of that that desire to be
Speaker 4: to feel like, oh, yeah, I know something that other
Speaker 4: people don't. I understand this world the way that the
Speaker 4: world in a way that the rest of the world
Speaker 4: doesn't understand. I'm a little bit special, right, And I
Speaker 4: think that's what what makes an article heading like this
Speaker 4: one extra alluring, extra appealing. It's just like I have
Speaker 4: this information that what the rest of the world doesn't know,
Speaker 4: like we've been doing this wrong the whole time. Like
Speaker 4: I just as a sucker for that, And that was
Speaker 4: a big draw for me, and and my spirituality was
Speaker 4: just the fact that I had special wisdom. So yeah,
Speaker 4: like humility and being able to understand why we're wrong
Speaker 4: and is a huge thing. That's the only way that
Speaker 4: we can move forward.
Speaker 1: Yeah, and the way that you were phrasing that just
Speaker 1: just triggered something in my brain. So I'm going to
Speaker 1: ask Eli this additional question here conspiracy theories, So how
Speaker 1: can we link that We've been talking about intellectual humility.
Speaker 1: Stephen was talking about having being privy to inside information
Speaker 1: or having the inside scoop on the quote unquote real truth. DM,
Speaker 1: how is this kind of thing do you think this
Speaker 1: would be? Is this fuel for conspiracy theory or is
Speaker 1: this going to maybe debunk a conspiracy theory or how
Speaker 1: is that going to link in there?
Speaker 2: I've already got one as soon as you said conspiracy theory.
Speaker 2: Between then and now, I've got one, So yeah, absolutely,
Speaker 2: like it could. I Mean I don't believe it, but
Speaker 2: you can come up with one that easily the extra
Speaker 2: four billion people are the ancient race of aliens that
Speaker 2: built the pyramids and went underground to hide, and now
Speaker 2: they're coming back up like humans naturally. That's why we
Speaker 2: didn't find them over the past decades worth of data.
Speaker 3: So yes, absolutely found to come up.
Speaker 1: I mean it seems like it takes very little excuse,
Speaker 1: just a tiny little kernel of an idea and then
Speaker 1: somebody's making conspiracy theory about that.
Speaker 2: Yeah, and archaeologists are like historians. Ten thousand years from now,
Speaker 2: we'll find that I was the one that started that
Speaker 2: because I'm the first one to say it on the internet.
Speaker 2: All Right, I'm going to be responsible for I'm like.
Speaker 3: Man, right, right, that's your legacy, Eli, right, there is.
Speaker 2: Of all the things I've said. But you know, I think, yes,
Speaker 2: it's absolutely it can be a breeding ground for conspiracy.
Speaker 2: But it's just another reason people say, you know, oh,
Speaker 2: you can't trust scientists. Scientists have an agenda. Scientists are
Speaker 2: controlled by their their benefactors. Donors is the word I
Speaker 2: was looking for. I don't know how benefactors can to
Speaker 2: me easier than donors, but it's this idea that the
Speaker 2: scientific community is they or them or like the government
Speaker 2: and whatever they are saying can't be trusted. So like
Speaker 2: if if they are saying it's raining and you stick
Speaker 2: your hand outside and you feel the rain, you're gonna
Speaker 2: be like, No, they're probably just you know, spraying water
Speaker 2: on my house with a hose to make me think
Speaker 2: it's raining, because I may believe anything except weather manipulation.
Speaker 1: I think is the words you were looking for, their
Speaker 1: weather manipulation. Yeah, because we know, of course that's a
Speaker 1: thing now right.
Speaker 2: Yeah, they're changing my climate.
Speaker 1: Exactly as Okay, So Stephen, I wanted to Eli was
Speaker 1: talking about how we might be undermining trust in in science,
Speaker 1: or at the very least, giving ammunition to those who
Speaker 1: want to foment that kind of distrust in science. Do
Speaker 1: you think I mean, because because when I look at this,
Speaker 1: I see that this as a as a strength of
Speaker 1: the scientific process, the idea that we can correct ourselves.
Speaker 1: And you were mentioning earlier about how you had this
Speaker 1: unassailable you know, knowledge in your brain when when you
Speaker 1: were religious, and I mean, how, how, how how does
Speaker 1: that play into this? Is this going to be the
Speaker 1: the crack in the in the dam that's going to
Speaker 1: break and all science is going to come crumbling down.
Speaker 1: Or is this just a reassurance and reaffirmation of the
Speaker 1: strength of the scientific approach? Is this a Is this
Speaker 1: a good or a bad thing for the scientific method
Speaker 1: and for those of us that care about that.
Speaker 4: I think any like the the system doesn't need to
Speaker 4: be perfect. If there's if there are inconsistencies, if there's questions,
Speaker 4: that signs that this system is working. It's when when
Speaker 4: everything works out just accordingly, just right, just perfectly. That's
Speaker 4: when flags need to be going up and saying like,
Speaker 4: wait a minute, how do we falsify this? If everything
Speaker 4: is going just right, something isn't right, that's a sign
Speaker 4: of the matrix right there. Yeah, So I think no
Speaker 4: like having being able to ask these questions. The only
Speaker 4: way to the only way science gets better is through
Speaker 4: more science, right right right, So yeah, bring on the
Speaker 4: questions and no question is too hard, because that's like
Speaker 4: we as a species are going to evolve and it's
Speaker 4: going to be through these kind of processes.
Speaker 2: Yeah.
Speaker 1: I really like the way that they presented that in
Speaker 1: the article itself. It wasn't a it wasn't a finger pointing,
Speaker 1: it wasn't a blame game. It was like here's what
Speaker 1: we did, Here's what was wrong about it, Here's how
Speaker 1: we can correct it. I mean, it was very practical
Speaker 1: and very straightforward it. I didn't get the impression that
Speaker 1: there was a lot of egos involved or anything like that.
Speaker 1: You know, it was just a straightforward problem solving approach,
Speaker 1: which really appeals to to someone like me.
Speaker 3: We have a little bit of time left.
Speaker 1: I knew that this we were going to have a
Speaker 1: little bit of time at the end of this segment here,
Speaker 1: so I have an extra question prepared here. I want
Speaker 1: us each to put some deep, deep thought into this.
Speaker 3: This is very critical. So here's the question, from.
Speaker 1: The standpoint of pure musicianship and skill with their instruments,
Speaker 1: what is the greatest rock band of all time? Defend
Speaker 1: your answer? Eli, the science guy.
Speaker 4: Go done.
Speaker 2: I already got it. I'm just going to go with
Speaker 2: a scientific consensus, Queen, and I don't need because of
Speaker 2: live aid, I don't need to justify that. But I
Speaker 2: can justify it without live aid. So we have obviously, first,
Speaker 2: of course, Freddie Mercury, if you're talking about mastery of
Speaker 2: an instrument, this is a guy with a four octave
Speaker 2: vocal range, which if he's not. I'm not confident enough
Speaker 2: to say that he's the only singer in like the
Speaker 2: last century or whatever that could do that. But if
Speaker 2: he's not, he's like one of like five or something.
Speaker 2: So that right there by itself, and not only he,
Speaker 2: but the band itself has such a range of style
Speaker 2: from like arena rock will rock you, to like opera
Speaker 2: rock Bohemian rhapsody to like like proto Thrashers, and like, uh,
Speaker 2: I don't know, Want Somebody to Love was kind of
Speaker 2: disco or kind of like I don't really know. So
Speaker 2: they have a range they have.
Speaker 1: He did the Highlander a soundtrack, right, the Highlander soundtrack,
Speaker 1: the whole thing all queen Absolutely.
Speaker 2: I didn't know. I haven't seen Highlanders, so uh yeah,
Speaker 2: I am out of her. That's truth. There can be
Speaker 2: only zero me. But additionally, sir uh Brian Howard May, Yes,
Speaker 2: Sir Brian Howard May, PhD in astrophysics and Commander of
Speaker 2: the British Empire. Uh is another title that he has
Speaker 2: built his own guitar with his dad out of a
Speaker 2: fireplace and a sewing needle. And that's like it's a simplification,
Speaker 2: but it's not like it's true, and uh then after
Speaker 2: the band became famous, he then later was like, I'm
Speaker 2: gonna finish finish my PhD In astrophysics, which he put
Speaker 2: on hold so that he could go be Brian May
Speaker 2: of Queen. I don't know a lot about drums or
Speaker 2: like rhythm.
Speaker 1: Of Yah, and I noticed you're not a lot talking
Speaker 1: a lot about the rhythm section here, so we gotta.
Speaker 2: I I feel you know, I know that you know
Speaker 2: each of the band members contributed to their songs. I
Speaker 2: know that Roger Taylor wrote I'm in Love with My Car.
Speaker 2: That was all him. He's got a pretty solid falsetto himself. Uh,
Speaker 2: powerful backing vocals for for Freddie Mercury, so that was
Speaker 2: a good pairing. John Deacon wrote another one Bite Sadus
Speaker 2: and I Want to Break Free. So two other fantastic
Speaker 2: songs got tight bass lines. It's just they all they
Speaker 2: they genre hopped they I think I think they were
Speaker 2: masters of their instruments.
Speaker 1: And the case strong case you make a very strong
Speaker 1: casey lie you you got us out of the gate
Speaker 1: with a big answer there, Steven, what are your thoughts
Speaker 1: best rock band pure musicianship and skill with their instruments,
Speaker 1: including vocals.
Speaker 4: Like obviously the answer is the tragically Hip. But as
Speaker 4: two Americans, you have no idea what I'm talking about,
Speaker 4: So I'll try to speak in your language. The White Stripes,
Speaker 4: Jack and Meg White, they're divorced and they're still in
Speaker 4: a band together. That's huge. Meg she plays the drums
Speaker 4: and she just focuses on like keeping a steady rhythm.
Speaker 4: That's huge. And then Jack he plays guitar and other things,
Speaker 4: and he also sings like.
Speaker 3: I'm a big Jack White fan.
Speaker 1: You know, I think the weak spot in the band,
Speaker 1: if the if we would call it a weak spot,
Speaker 1: I think is Meg. Of course, I think, but you know,
Speaker 1: he's kind of the pulse there. Of course I could
Speaker 1: be wrong.
Speaker 3: I could be wrong.
Speaker 2: Maybe the.
Speaker 1: Yeah right right right, Well, I'm gonna throw my answer
Speaker 1: out there, and although I might, I'm on the verge
Speaker 1: of changing my mind here after hearing you know, you can't.
Speaker 1: It's hard to argue with Freddie Mercury. In fact, in
Speaker 1: my book he has he is in the you know,
Speaker 1: he has to be mentioned if you talk about best
Speaker 1: musician on any instrument at all, I think if Freddie
Speaker 1: Mercury is definitely in the discussion there, And of course
Speaker 1: Brian Mays, no slouch, I would say rush, of course,
Speaker 1: I think you know they're just you know, the holy,
Speaker 1: the holy Trinity. Right, we got speaking of bodacious vocalists,
Speaker 1: we got Geddy Lee with his very distinctive voice and
Speaker 1: annoys the hell out of a lot of people. But
Speaker 1: you know he's got he's got a lot of skill there.
Speaker 1: You know, Freddie Mercury wasn't playing bass when he was singing,
Speaker 1: although he would, you know, mess around with the piano
Speaker 1: a little bit. But Geddy Lee's on vocals, on bass
Speaker 1: and on keyboard, all at the same time.
Speaker 3: Right.
Speaker 1: And then of course al Alex Liifs is routinely brought
Speaker 1: up when when discussing the top rock guitarists of all times.
Speaker 1: He's got such a huge range and the master of
Speaker 1: the of the lengthy solo. And so I love Alex Lifsen.
Speaker 1: But of course you have your Freddie Mercury. I have
Speaker 1: Neil Pert, and he is definitely a master musician, routinely
Speaker 1: thrown out as possibly the best drummer of all time.
Speaker 1: I don't want to hear about John Bonham today, but
Speaker 1: Neil Pert was he just mastered. He you know, he
Speaker 1: would learn different styles. He learned how to play jazz drums,
Speaker 1: He learned how to play all different kinds of drums.
Speaker 1: He would rehearse even on concert nights. He would rehearse
Speaker 1: before concerts and so on. He would start working out
Speaker 1: weeks and months before they went on tour, just so
Speaker 1: he could have enough stamina. And my favorite Neil Pert
Speaker 1: song ever was in it was I was during an
Speaker 1: interview and they asked him, do you ever get sick
Speaker 1: of playing Tom Sawyer? And he said, I never get
Speaker 1: sick of playing Tom Sawyer because every once in a
Speaker 1: while I play at per and I just love that.
Speaker 1: It just totally summed up his attitude towards towards music
Speaker 1: right there.
Speaker 3: And so I love that. But you know, good effort,
Speaker 3: good effort from Stevens.
Speaker 1: The white stripes, you know, that's pretty damn good white
Speaker 1: stripes there, Queen. Though you know you're you're definitely threatening
Speaker 1: for that top seat. But I still think Rush might
Speaker 1: might have pulled it out here. Let's hear it from
Speaker 1: all of you out there. Leave a comment below with
Speaker 1: what you think is the greatest band on pure musicianship
Speaker 1: and skill with their instruments ever of all time