Weights and Plates Podcast - #75 - Science Is Fake with Stef Bradford, PhD

Episode Date: May 3, 2024

There's seemingly no end to the "evidence based" coaches out there nowadays making all sorts of claims about you should train, backed up by scientific data. Have you actually read any of the papers they cite to back up their claims? It turns out, there are numerous problems with the field of scientific research, from the actual design of the experiments to the reporting of data, the publishing process and peer review, and, last but not least, skewed incentives for the people carrying out research at every level. Dr. Bradford, who earned a PhD in Pharmacology and Molecular Cancer Biology from Duke University in 2004, walks through the problems with the modern scientific process, and why professional research is the not the same as science.   Weights & Plates is now on YouTube! https://youtube.com/@weights_and_plates?si=ebAS8sRtzsPmFQf-   Weights & Plates: https://weightsandplates.com Robert Santana on Instagram: @the_robert_santana   Trent Jones: @marmalade_cream Email: [e-mail]  

Welcome to the Weights and Plates podcast. I am Robert Santana. I am your host along with Trent Jones, my co-host, and we have a guest. We do. Would you like to introduce her, Trent? Sure. After you say yo, of course, your ceremonial yo. Yeah, yo. Yeah, we have a returning guest, actually. The one and only Steph Bradford from Wichita Falls, Texas. Steph, welcome to the

show. Oh, hello, guys. It's good to be here. Thanks for joining us again. I'm going to be of no help in this episode because this one's out of my wheelhouse but uh i'll be i'll be an interested bystander and maybe i can crack a fart joke or something uh somewhere in there i think today we wanted to talk about uh the science right you got to do the echo thing man like rip the science the science tm tm Not actual science, but the. That's right. The. The science. Is it a trademark or a wordmark?

Well, I mean, you can have a trademark can be an actual word and the font and how it's presented. So, starting strength, for example, is a wordmark. It's also copyrighted. I mean, there's all sorts of things that go together and are um are things that can get very technical and mostly what they do is enrich people of a certain profession it should be a legal profession yeah so look at you chasing your tail in various things um that aren't necessarily helpful so this is just how it is so the starting strength the starting strength logo,

like you would see on the blue book, it's the, there's the trademark for the name starting strength, but also like the look of the, like the font and the spacing and all that kind of stuff. Yeah. So on the book is, I mean,

the book's been around for, for a long time. That's not actually the word mark, but if you look at the modern font or the, the modern presentation, the way it is on the website, if you look at how it is on StrengthsFanGems, it's slightly different than the book cover. So the book cover was Adobe Garamond Pro, and the wordmark is actually a specific font that has been modified slightly to make it even more, you know, of a niche. But it's subtle things. Like you can see the difference, but a lot of people wouldn't notice. Yeah. All right. Well, see, there you go. I'm learning stuff already and we haven't even gotten

to the main topic today. Well, I actually, I did have a question, a lead off question before y'all get into it. Cause I know, I know Santana, you've got a lot of things you want to cover today. Sure. But my question I wanted to lead off is, well, actually, I have two questions. First of all, Steph, can you tell us a little bit about your background in academia? So I know you have a PhD, but I don't know what field that PhD is in and what your academic experience was and your education. So can you give us a little bit of background and like what kind of research you've been involved with? Yes. And I can try to do it in a way that's not horribly confused and boring.

Not over my head. So, you know, it's one of those things that I guess you could say I just kind of fell into. There are some people that get in academia because they've always wanted to be, you know, a professor, a teacher, a researcher, something like that. That wasn't me. I just always have been interested in a lot of different things. And somewhere along the way as an undergraduate, I started working in a lab, just kind of a side project. And I liked doing experiments. That was the hook. Okay. I liked doing experiments more than anything. And where I screwed up actually looking back, you know, hindsight is, is, you know, reveals your foolishness. Um, where I screwed up was,

um, I didn't understand that if I wanted to do experiments, I would have been better off to just start working in a lab, maybe get an MS and work as a lab technician. And if I had done that, I might still be doing that today, but that's not what I did because I also always, you know, it was good at school, you know, like a lot of us who end up in academia and, you know, progressing farther along that kind of track. So, you know, you're in there. I was on scholarship. And then with research, unlike, you know, a lot of other fields where people go to school and graduate school, they pay you. So everything's paid. So it's like, oh, cool. I can do experiments and they'll pay me and I'll do this stuff and it'll be fun and it'll be great. So I got hooked and I was doing that for a while. And really by the time

I finished my PhD, I just didn't want to see any of those people ever again. Yeah, sure. Okay. And, and the thing is because you're, you're focusing on the things you like, but like any job or anything you do, there's the things you like and there's all the shit that goes with it. And what you find for a lot of things you like parts of it but you can't handle the rest of the shit that goes with it and what i couldn't handle was the political atmosphere the constant grant chasing the entire bullshit uh the the focus on money it was it was all about money um because you had to have money to to work right to get the work done.

It becomes the singular focus. Yeah, yeah. And the higher up you go, the more you're just grant chasing and bullshitting and not doing the actual work and not doing the interesting, fun stuff. And then on top of that, the people that were at the peak, like the lead researcher in a lab that had people under him, they tend to be complete dicks. Now, some of them are brilliant, right? But it's one of these situations where the guy at the top is milking off of the work that the underlings are doing. And so it was, there's a lot of exploitation kind of thing going on. And that gets old. Even if you like the experiments, that gets old. So, oh like the experiments, that gets old. So, oh, I didn't tell you anything about the subjects. So, I mean, I started, I did some

random stuff like as an undergrad that all over the place. And then I ended up going to Deacon University in their department of, what was it? Pharmacology and Molecular Cancer Biology, which is a long name. So there you go. And what's hard to explain about this is that most of cell biology, biology, all this kind of departments, we think of these old things like biochemistry and pharmacology, but really everyone goes in and you work in a, and it might be part of a certain department, but you borrow techniques and you work with people across different fields. So it kind of all cross-pollinates and gets all mixed up. Sure, yeah. But my subjects I was interested in were neuroscience-related topics.

So I did things with a proline transporter, a high-affinity proline transporter. And then I went and I was looking at excitatory amino acid release. So I've done a lot of different things. Some of them well, some of them not so well. But that was my interest because I always liked, I liked neuroscience, I liked the brain. And I liked a lot of the techniques that we used to study the problems that we were looking into at the time. Sure, sure. Yeah, and it seems like most people that I've talked to that have a PhD, this is a years-long process, right? Do you remember how long it took you? Forever, partly because I was in one lab and I was well along in my project,

but the guy I was working with didn't make tenure and, um, he was a dick, um, particularly guy was a dick. Um, but I really liked the subject, the subject material was very interesting. I had good people in the lab that I worked with other than him. And anyway, when he didn't make tenure, he just kind of like ran away and I had to stop and restart a completely new project. That was very exciting. Oh man. Yeah. So that's probably, I'm imagine years of work that you have to redo. Yeah. Yeah. Or, you know, you're just doing it over and I wasn't really efficient about anything anyway, too, because, um, you know, I knew some people that went in and they were like okay

i'm gonna work with this guy i want to get my phd in this amount of time so there were professors who had kind of projects set up that way you go in you get done in four years five years maybe other ones where it was more interesting was more experimental your projects might not work and then you'd have to like figure something else out that That's kind of the kind of person I always pick the weird thing instead of the mainstream thing. That's just a horrible trait that I have in every single area. Well, I think so. Yeah. I think there's a lot, there's, there's a lot of gold to mine there. Cause I know you, you, you want to talk about a lot of the subjects that you've already brought up stuff during this episode. So yeah So, yeah, I have one other question I wanted to start with before we get into that, though.

It's kind of a dumb question, but I'd be curious to hear what your thoughts on this. What is science? What is, and I'm not talking about the science. Let's set that one aside for now. Set the trademark aside. Yeah, so what is science? What is the field of science or the practice of science?

Man, it's okay. So, you know, when I don't have a definition like right here jumping out of my mind, then I'm not actually very good at articulating it. So, you know, I'm not a rip. So I'm not as good at that as he is. But okay, so there's some things that make up science that are essential to science. And I think they're things that people often put into them. But so essentially, it's the idea of observing, formulating a hypothesis, testing that, refining it, and repeating it um so the idea is just at a very simple level is we're going to play with stuff and we're going to test it and we're going to try to figure out what's going on um so um what's so disappointing about a lot of that is the failures due to the current setup where it's basically a giant bureaucracy filled with people who are not at the core doing those things and are not concerned with uncovering truth about how things operate their motivations are different yeah they're different than that

so that it seems like the the key there is it's observation-based. It's about using our senses to observe the world and then form a hypothesis about why something might happen. And then go explore whether that's the case or not. And then test it. So yeah, there's a lot of elements that go in there as far as being objective, not making up data. It's like actual real data. Taking away biases in how you're observing and measuring things. Because the objective is to figure things out. It's to uncover the truth of how something's working and use that to make predictions and then maybe build you know things things from there that's what i found so interesting because you know i'm the kind of person that it takes everything apart sometimes i put it back together i think i think it's important to say that i think it's important to say that because um i think a lot of people's

impression of what science is now because of our current environment is that science is this thing that a group of experts do. And, um, it's, it's a, it's this sort of consensus that a group of experts who are, who are deemed scientists, uh, come to about why something happens or what you should do about X, Y, and Z thing. And that, that's really really that's like uh looking backwards at the at the you know the whole field of of science right because that's what it has evolved to be but that's not what the basis of science is right the basis of science is more fundamental like you just said observation hypothesis testing um there's this bureaucracy that's built up around it but i think a lot of i think a lot of

i think a lot of people nowadays kind of they confuse the two right they look at the bureaucracy and like oh well that's that's science yeah yeah well it's it's completely inverted it's completely turned on its head um and and people often give science the credit for something that's not science-based and what i mean by that is you know if if you you know how to see how it got to be over the last few years with this whole idiotic the science and the idea of consensus as equaling science and peer review as being an essential facet of science which is not the case at all that's that's a very modern bureaucratic control the narrative type thing is they confuse engineering with science

okay now engineering or like applying and building and making that's like touching the real world by the application um that's how we get some cool stuff um science is more why it's working you don't need to know why it's working and why it's working always follows you don't figure out why it's working and then go, let's build a rocket. It's like, it kind of, you build a rocket and then you kind of figure out some of, oh, the real reason that, I don't always come up with the best examples,

but you figure out like the real reason that worked. You know, the theory doesn't lead. The theory is, it follows. Yeah, yeah. No, that makes sense, right? There was a friend of mine that was talking about some book, or it was a series of lectures given in the 19th century by a famous scientist. I forget who his name was, but it was a lecture about the chemical composition of a candle.

And, uh, it was just a great example because everybody's used a candle. It takes no scientific knowledge to light a candle and watch it burn. But the thing does burn and there's, there's, you know, you don't really know why, but it's actually kind of complicated. There's, there's a lot of things that have to be correct for a candle to burn like it does. But, um, okay. Well, I'm, I'm glad we set that groundwork because, um, I want to dig in now to like what, what the scientific process has become, uh, in the modern day. And, and this is where I leave it to y'all, because you're the experts and have the experience in this field, but...

Oh, let me... Yeah, go for it. Take over. So, while y'all were talking, I pulled up the Merriam-Webster definition of science. Okay, yeah. So, we'll start there. So, science, noun, there are two definitions, and it kind of goes into other context definitions, definitions in other contexts. So 1A, a knowledge or a system of knowledge covering general truths or the operation of general laws, especially as obtained and tested through the scientific method. Now I've got to fucking define that. Shit.

I know what it is. I just, it's what you said earlier. Definitions are always hard because... I'm more on your end than Ritz. I like the second one better because it is a nice cop-out to that last sentence. Such knowledge or such a system of knowledge concerned with the physical world and its phenomena. So, earlier I was listening to you talk and you mentioned some of your projects. So, I was, there were two things I was thinking about. Number one, because people listening probably

don't know the difference between these two terms. So, I was going to ask you if it was more basic science versus applied science and those things we can define. So, I kind of, that was my first question for you. Yeah, yeah um it was basic science that's that's what i thought so what is that which means like which means you know you're you're tinkering around and in fact like a lot of times when you are talking about basic science it's like you're kind of trying to figure out how to do something as you go along to figure out what you're looking at because you're not sure um or or to put it another way like sometimes people ask me well what what's what's this what's what's it going to do what

what's the ultimate purpose of this this and i'm like well i don't know it depends what we find out here because and then there might change that here and it could could be related to this but we don't know if it is that would be interesting, but not there yet. That's a big jump, you know, and so on. So, in many cases, you're looking at very basic processes. So, you're often in a very reduced system. You're testing. Just try to figure out kind of what the general landscape is and then build slowly from there. Nothing practical.

Nothing you would use in your room right now listening to us, right? No. To the listener or viewer, because we're on YouTube now. Yeah. So, I mean, going into detail would kind of be hard. You know what I mean? It would just get on and on. Yeah, we don't need to go there.

And I haven't looked at it in quite some time. So, I haven't looked at any of this in 20 years. So, you know, keep that in mind. But so for example, I was looking at the release of neurotransmitters. So I would set up a system. I would take animals and kill them, take their brains, do things to it, make a preparation. And then I would test that. I would put solutions on it, neurotoxins, and test in different A, B conditions and compare it and see how the release went.

Right? So, you know, so you're using these little, these tools, these neurotoxins, these drugs to try to differentiate what's controlling the release and what is actually released. Can you do anything with that? Not really. I mean, we're not talking about drugs you can give somebody. I mean, unless you really hated them, right? So, like, you know, botulinum toxin, you have to pretty much hate them to give them that. But, you know, things like that are very far away from any kind of practical, applied

kind of situation. So then why is it important? Because the stuff I did is obviously on the applied side. We'll jump into that. But I think this is important for people to understand because there's a big difference between what you're talking about and what I'm about to talk about. So I'm just kind of trying to segue into that. Yeah, that's a good question. So why is it important?

So sometimes you're, and I'm thinking of projects like a lot of different people I knew did, you're looking for different, like the more you know about this, the idea is the more you know about about how the system's working, you can figure out potentially better targets to try to work on to do something useful, like maybe decrease seizures or something. It's a long way from any kind of application though, because there's a million things in the way of that. So it's just kind of an idea of understanding more, gives you more avenues and approaches to the problems you're trying to solve. A lot of it is just fiddling around in little circles because there's a lot of dead ends,

right? Or things you thought were doing, but they turn out to be artifacts of some sort, right? So if you look at actual drug discovery and development, most of that is just a throw it at the wall, see what sticks. Throw it at the wall, see what sticks. Just high output screening of compounds from the environment and, you know, generated chemicals and just see, you know, create assays and test for them. But let's say you wanted to have, like you're thinking, I'm looking for a drug that will do X, right? So, I mean, you kind of have to have an idea of wanting it to do X and then make a little system that you can test 10,000 things at once in little tiny sample sizes. So you might use the basic to come up with a screening test and then you do this high output assay that you just go out in a field literally and just pick plants and make little you know extracts and then put it on and see if

it triggers the reaction you're looking for and then you keep narrowing this down more and more and more and more to get something to use in in a therapeutic setting um so a lot of that's been very much brute force which is not what you think of when you think of somebody thinking and coming up with something smart and testing it and whatever. But there's so many options. You have to just start from things you can actually examine, things you can test. Yeah, it seems like to make a drug, you know, yeah, I can um there's a lot of just like kind of throw throw darts at a dartboard and see what you know see what gets you the bullseye but it seems like you need a huge like volume of information of knowledge rather about basic processes of how things work in

order to even like start to create a drug um i've well i mean a lot of times maybe it kind of goes the other way though you know yeah you guy ate something he threw up well that's an interesting effect right so you know it comes from observation over a long period of time um we're we're kind of some of the testing can be helpful is that you maybe can alter the drug and how it's metabolized to have less side effects, for example. Sure. Right? Okay. Yeah. Those kind of things. Yeah.

So, the key feature here that I always think of when it comes to that sort of thing is there's a greater deal of control, right? Mm-hmm. Sort of. I mean, a lot of those things, you're reducing the system so that you can test it. So you control the variables, so you can just test the thing you're interested in. But you never know about all the things you don't know about that are part of that test system. Right. A lot of times you find all the things you're manipulating, you have a greater deal of control than, say, something that's a little bit more practical. Yeah, and not just practical, but like you're taking it from a more, if you're in a very reduced system, you have a lot more control, right?

And the further you go up into an actual mouse or a person or whatever right there's more stuff you don't know about yeah that's exactly where i was kind of going with that i'll tell you just a just a kind of background thing that i don't think people understand so one of the the biggest uh problems with modern science the way things are being done now is um is, you know, it flip-flops all over the place. I mean, how many times have you, you know, this thing's good, this thing's bad, this thing's good. So some people think like, oh, you know, the science stuff is, you know, crazy or whatever. And they don't realize that the biggest thing that's probably missing right now, other than people who won't, you know, who are just pursuing

things that are interesting because you get grants rather than than actually being important yeah right um is uh is that things aren't being reproduced right so this is one of the key things yeah the original idea is i do i do the experiment say i I present this experiment. Santana goes and does the experiment. Does he get the same result, right? No one repeats experiments. And I'll tell you, having had experience over the years, you'll have the methods in a paper and you're like, I want to use that same method in my lab and I want to use it for X, Y, and Z. I have never, ever been able to get a paper and do the experiment based on the information that's public, that's supposed to be there, so you can reproduce it. Something always goes horribly wrong.

And so then people try to figure out, well, maybe I need the exact same reagents or this or that. You have to have the exact same reagents. Usually you have to go to the other lab, have them train you on to doing the procedure. And so you start to wonder, like, what is going on here? And you start thinking, what do we know about the exact situation that's creating this? Or like, I should be able to do the same thing and get the same results, but I'm not. Right. Yeah, exactly. Yeah. I'm going to dust off my, like the four Greek words that I know, and I'm going to use two of them. So the so the Greek word for, I think, I believe it's the Greek word for science. I think that's how it gets translated. I, you know, I don't know the nuances there, but, um, it's,

it's episteme, which is basically demonstrable knowledge. It's knowledge that can be, you know, so if we take something that's a math, that's a, uh, that's a law, a scientific law, like, uh, mathematics, uh, one plus one equaling two. If you don't believe me, I can always just show you like, here, here's one thing. Here's another thing. You put them together. Now we have two things. So one plus one equals two. And if you're like, okay, I got it now. But then later on, you're like, well, I don't know. Maybe not. We can do it again. So we can reproduce that experiment that proves the fundamental fact that one plus one equals two. So there has to be some amount of demonstration there in order to actually prove that you've actually revealed anything, that you've uncovered any truth. Prove that you've actually revealed anything, that you've uncovered any truth.

So, yeah, that's one of the things I've heard about is I've heard it referred to as the reproducibility crisis. And that when third parties go and try to test the methods or I don't know exactly how they do this. I'd be curious how they do it. But when third parties go and evaluate how many papers have actually been successfully reproduced or been able to reproduce the results it's a huge percentage of them that can't right and part of that if you look at like if you you know pull up older papers is they had this method section that's like you know half the paper right so there's a lot of detail so in modern ones where you you know you pay to have it published you know like the paper right so there's a lot of detail so in modern ones where you know you pay to have it published you know like by the page and they charge you to publish it then they sell the the journals too um it's been compressed so there just isn't enough information so it's

like things probably get left out it's more like a summary of what happened than the actual details. Right. And the data's not in there. So, like, some things, I don't know about you guys, but when I'm figuring out something, I kind of think about it a little bit, I mess with it a little bit, and then I just go and do it when I half understand. And I figure out what I'm not understanding by kind of how it's turning out. So it's kind of like I don't try to figure out all the theory and then go do it. I kind of read a little bit, then I jump in and do it and I go, huh, that didn't work. And I keep going from there. Well, you can't do that because you don't have the data. So people don't understand when you have a paper, when you have something reported,

the reviewers don't see the data. They see your summary of the data that you might have removed things from, that you're displaying in a certain way to kind of push the idea that you're kind of drawing conclusions from and all that kind of stuff. It's all in the presentation. They're not looking at the actual experiments. They're not looking at the data. They're not looking at the lab book. They're not looking at the data. They're not looking at the lab book. They're not looking at the trace off the HPLC. They are assuming and trusting that you are showing them your actual information. If it's something like a Western blot, you know, so you're looking at, you know, this protein separated out and identified or whatever, that you might have

done a hundred times, you know, that you claim you've done a hundred times you're only showing them one representative sample so they have to assume they have to trust you to believe that it's actually representative it hasn't been altered in any way it hasn't photoshopped that isn't the one time you got it to work and it failed 20 other times but guess what all of those things happen and they probably happen a lot more than you think. So, yeah, this segues nicely into the next thing I wanted to touch on. So we've been really hitting on science up to this point. But there's another term that we're going to talk about in contrast to science that I learned from you and Rip years ago when you gave me that short little read called Not Even Trying. And the book's called Not Even Trying, The Corruption of Real Science. Do you remember the author, Steph? I do not remember the author. Yeah, that's Bruce Charlton.

So, I was handed that by Steph. That's not even his best book. He thinks a lot and he puts out some really useful information. It was a good introduction to this concept because he kind of highlighted things that I'd seen that you'd seen. And what I stole from it, that I continue to steal from it, is he differentiated science or scientists from professional researchers or science from professional research, right? And up to this point, we've been talking about science, right? And now I really want to get into the topic of professional research. So you mentioned something earlier, and I forgot what I wanted to ask you, but now I remembered. You said that

your first advisor did not get tenure. A lot of our audience may have heard that term thrown around, but don't know what that means. And I have my own definition of it in my head, and I'm sure that yours is pretty similar, but I think we should start there because professional research, and we're going to touch on that, we really want to talk about the incentives behind why people conduct a lot of these studies now, and that's a big one. That's a big one to start with, I think. So, I don't know, it's like sometimes you look at this stuff and you're like, this is some sort of hazing system, but basically, if you go into academia, there's different levels of progression to you know the little baby professor to the full-fledged professor and if they decide they want to keep you on and make you totally part of the club in that institution um and you're not

just going to be you know replaced with somebody they like better so they've accepted you your work's good enough they you're you're quality. They'll give a person tenure. And in that place, it's basically now you're kind of locked in. So instead of having to get reelected every two years for the House of Representatives, you are in the Supreme Court. You're there until you, like, you know, until you leave. Right? So it's the pressure. Think how different those two pressures are.

Okay. Now, I mean, you probably want to think about them too much because thinking about politicians is painful. Thinking about judges and this is very similar insanity there is painful, too. But you can see how that's a completely different environment to work in once you've been given the golden ticket, which is basically what tenure is, is a golden ticket. which is basically what tenure is, is a golden ticket. It's extremely difficult to fire these people. In many cases, and I don't know if this is state by state, but they're unionized too, which has another layer to that. But when you go take that a step further, when I was looking for an advisor, I learned the terms senior faculty and junior faculty.

And I remember this one student talking to another student and said, never, ever take an advisor who is junior faculty because they want to get tenure and they're going to work the shit out of you and try to basically stretch the boundaries as much as possible because that's their incentive. That's true. But they do a lot of cool stuff because so what the thing is, what you tend to see is a lot of times the, the guys that are the up and coming guys, you know, you have that balance. You want to have something new and exciting. So a lot of things they're doing are things that attract students because they're more like interesting problems. They're less established. Right. So, um, yeah, but it's the whole thing's more risky. So, the project's more risky.

Sometimes the people are crazier. There's plenty that goes on with the senior faculty, but it is a more stable situation where you'd be working. That was good advice. I probably wouldn't have taken it because I'm kind of dumb that way i did i didn't it was a mistake too i mean the same thing and we both got like fucking hell yeah i got i i got told by one so the way they had it set up when you first went in like the first year you you go to different labs and do some projects and kind of see like if you kind of like the lab environment and the professor there you know all that kind of stuff and i remember being told like well that'll be kind of risky project i was like was like, oh, good. Same here. That's exactly what I was thinking.

So, yeah, everything, you know, I always get the weird thing if it's possible. So, I probably wouldn't have listened. I started out with someone who was notorious for getting people out in three years. And she sticks it to me to this day if i were to talk to her she'd say if you just listen to me so you know what five and a half no it was a seven year stretch five and a half which were spent in the program so i took a year and a half off um but uh had i just stayed with her but her you but her projects were pretty easy, fast, quick, efficient. You learn enough.

And I kind of bought into the flashy stuff the other guy was doing. And man, I learned what not to do. Yeah, and it depends what your objective was. So I had one lab I went in. I did the project. It was great. I thought it was interesting. And then there was another girl that she had been just before me she went back and stayed in that lab

and part of her goal was i'm going to be done to be out of here in four years like it's guaranteed it's not going to go a different way i'm gonna be done and be completely done and she was and she got a job and you know i i don't know what she's doing. She probably is still working in some kind of research capacity. She was working for a company, but I don't know. But there were times where I looked at it and I was like, I don't know. I could have done that too. That could have been me, you know. But that's not the choice I made.

Me either. But, you know, I think we learned a lot, especially about human behavior and motivations behind why people do certain things. So to get tenure, as far as I remember, there were three things that they looked at. There was research activity, service, and teaching. And depending on the type of institution you're at, some of those things are weighed differently. I was at a – it sounds like – no, you definitely were, too. We were at institutions that are considered high research activity. So that's weighed very heavily, right?

The place where I got my master's was a more of a teaching institution. They didn't have, I think they added one EDD at the very end. And we're not going to go into that. That's irrelevant, but it's a doctorate with some sort of research component involved in it. But for the most part, it was just all masters and nothing higher than that. And over there, it was weighed pretty low. You know, research was weighed pretty low. If somebody got dinged on research, the person in charge didn't like them and didn't want to give them tenure. I saw that happen once.

And, of course, the guy was good at what he did, of course, because it's typically how it goes in academia, sadly enough. But, yeah, your weight on those three things. So, you know, they look at your teaching scores. They look at service you've done outside and, of course, your research. So where I was at, at ASU, was high research activity. You were at Duke. That's high research activity. So this kind of sets the tone for why these guys are motivated to do certain things.

This kind of sets the tone for why these guys are motivated to do certain things. So, right, when they're doing research, the lay public hears about studies that are published, and they assume that, you know, first of all, they assume that the lead author, or I guess depending on the journal, but, you know, the guy in charge, we're just going to use that because the guy in the, because the first name could mean one thing in one journal, and the last name could mean one thing in another journal in terms of the order of the authors. So we're just going to say the guy in charge, right? They assume the guy in charge is sitting there in a lab coat with beakers doing the work. And that is not what he is doing. It's completely different. And I'll let you kind of describe that because I learned it from you. So I'm stealing information you taught me. And I started thinking about it. I started thinking backwards retrospectively, like, oh, yeah, everything she's saying is fucking true. That's exactly what they're doing. My summation of it was these guys are analogous to general contractors.

They go, they get the money, they move to the next job, and they send a bunch of fucking skilled labor under them to do all the work. But that was my synopsis after taking in everything you said, so I'll let you kind of explain that system. Yeah, I might have done a better job before than I will do today. But yeah, you can look at those guys at the GC or as a project manager. They just kind of coordinate things. But as far as the money goes, and this is the thing I think is the biggest problem is these guys are selling whatever the researchers are doing. So it's basically almost even a marketing kind of capacity as far as what their role is. They're not actually doing research, with some exceptions where some will go

in and do a little bit of it. What they're doing is they're getting grant money. And one reason these big institutions love that grant money is because that golden, golden gravy flows to the institution itself. So professors aren't typically, I mean, I'm sure it varies in some places, but so if this guy is, you know, Mr. Professor here, he gets the grant money. The grant money pays most of his salary. It pays for the building and all this kind of stuff. So these guys are supporting the institution by bringing in money. So this guy is like a fundraiser for the institution. He's fundraising for himself and his prestige. He's fundraising for the institution and all administrators. The money coming in here, it pays people in their employment. So like, for example,

for me, it's like I had my tuition paid for i got money every month so it was like it was a job you know i didn't i had some people in some departments some friends of mine would also teach i didn't teach i just did research i mean i would teach some you know new people in the lab or something but as far as like classes i wasn't teaching any kind of classes i wasn't a teacher assistant i did lab work lab work. I was just the hired person. So they use the people, the up-and-coming people, to do all the work that's getting done. The other guys are running around schmoozing, making grant proposals to try to sound a certain way to sell the project they're doing here to get money in here for this other

stuff sometimes there's pilot studies you do with that money like a slush fund to get the next project so here's as great as i think d-i-n-i-h you need to fund it you get the money funds that project but they also use it to try to figure out the next the next thing they're going to use to get money. So it's a giant fundraising operation is what it is. And it's extremely shitty. And what I mean by that is, so it gets very quickly driven by political funds, you know, because it's like the NIH is, you know, getting the money, you know, it's like there's a lot of money in certain diseases, right? What's the popular disease right now, right? So it can be something that's completely overfunded, like breast cancer. Sorry,

completely overfunded. Other things that got popular at different times, so there's just a lot of money thrown at them, things like HIV. You know, it's great and all, but, you know, it's because the money's there for political reasons. It also, there's a lot of intersections with drug companies as well, right? Where money's coming in from drug company grants. And, you know, I'm sure you guys see where someone might criticize, oh, this study came out of Pfizer, so we can't trust it because it's a drug company. Or this study was funded by ExxonMobil, you know? So whatever it is, it's corrupted. Guess what, guys? NIH is political. And getting funding from government is just from

a different entity that people are producing. They're whores, guys. I mean, they're producing stuff to get money. That's what they're doing. And depending what the policy is, it's corrupted because you know the answer they want to get. You know the answer they want to get. And it doesn't have to be as obvious as say, oh, Exxon, oil, oil, oil, fine, whatever. But you know what? These guys want something too. They want things to go a certain way. Yeah. If you had asked me five, six years ago about this, I, I would have, I guess I would have, I had this idea, this naive idea that if you were a scientist, if you were a researcher that, that you had a, you know, you've just had a topic of interest

and you just would go explore that. And, you know, you would find different avenues to explore that question. And that's it. You know, that's sort of, it's all driven by, you know, by your own desires and interest and what you want to study. And I mean, looking back, that's an incredibly naive way to look at science because, yeah, it's like somebody's got to pay for all these labs and uh carrying out all these experiments and so the flow of the money yeah you can see how there's a lot of pressure to produce you know to study certain questions so other questions don't get explored don't get studied and then yeah like to produce certain results that are favorable um that'll get you the next grant but

yeah i guess i just never even thought about it before i don't think many people do think about yeah and the thing the thing is that's not like new okay but it's on a larger scale so if you think back you know hundreds of years ago when these you know some of these pioneers and in various fields were operating and you think of that as kind of the golden age in some ways it was because when there's less money in it you get people that are there for things other than money but you still had to have a patron same way they did with arts right it's like you know you had to like play the game because money had to come from somewhere you know um you know there's certain things you can kind of do on your own um certain kind of observational or you know exploratory things but people had to get money to fund their expeditions or their experiments. It had to come from somewhere. So there always was that kind of pressure. So you might ask,

like, well, what's different? And well, the more you take something to the masses, the worse it's going to get, right? Because you're going to get more people there just for the money. And because of the way the system works itself by creating a bureaucracy, that stifles everything that goes on, right? It's a lot more restrictive. Because now, because why? Because people are coming for the money, you know? You're attracting a lower quality of people at that point. And we see this in in kind of anything right if you start start scaling

you start getting it if something gets popular it starts getting crappy right it doesn't get wonderful right there's a certain leading edge where it's great and then it's like oh now everyone's doing it it sucks why because you know you're regressing to the mean, right? Yeah, like how many premier research institutions are there for any given scientific question? And if there's, are there 50 universities that are just like the premier

university for studying this particular cancer question? I would kind of doubt it, but there might be 50 universities chasing that grant money, or 5,000. I don't even know how many, the scale of what we're talking about, but yeah, that certainly makes sense that if you have this huge incentive to chase grant money, then you're going to get a lot of players in the field, some of whom are just, I mean, there's just totally different caliber of, of, of talent there. Yeah. And you just get more people that are there to play the game versus to do it for real. I mean, it's kind of like how, like, um, you know, Google will periodically change certain things that have

to do with, you know, rankings or something like that. It's because what happens when they figure out how you're doing the rankings and people start gaming their rankings so then you have to change them you know it just keeps going and going um but when something has a lot of uh bureaucratic structure you can't keep changing you know i'm saying it's it's now people are playing a game because that's what's there now it's a game right and i think that's probably where we get, you know, we can, we get the absurdities that start to happen. Like, um, I've heard about these, these, uh, people who will submit sham papers to journals for peer review. You hear about people that have gotten caught submitting sham papers. Well, yeah, there's people that have gotten caught and there, and there are teams that

have intentionally submitted bogus research papers to journals to see how many time you know how many journals admitted them and uh yeah and yeah so the people that have just you know totally falsified results and and there's just they're supposed to go into a peer-reviewed journal but they get published anyway because there is no peer review no i mean it's just some guy slapping his name on the... Or there's not as much information in the paper as you think. You know what I'm saying? It's like this looks... Think of the problem.

So if you have... You're studying, I don't know, nose hair or something, right? And everything gets more specialized, right? So now you're the nose hair expert. Okay. So you have a paper the nose hair expert. Okay. So you have a paper on nose hair. Well, who's the peer? Well, it's the other people studying nose hair.

Well, who are they? They're your competitors, you know what I mean? So they can mess you up or it can be a, hey, now I'm going to let your paper go in. And then, you know, pretty soon mine's coming up. You know what I mean? You also have people turning in their papers and all of a sudden, while their paper's being held up, somebody else produces something very similar. So there's a lot of – it's like part of the game. It's part of the competitive environment for the purpose of doing what?

Winning, right? Getting the prestige, getting the money, getting the tenure position, having little people do your bidding that you can treat badly. All that fun stuff. And I've learned from our friend Dr. Pewter that if you can get to the point where you're the guy writing the textbook for like an undergraduate course, I mean, that's big, big money. You can start getting textbook royalties. So yeah, there's a lot at stake here for sure. Yeah, there's the textbooks and there's the patents and stuff too.

So there's a lot of things that are patented. Now you think, well, wait a minute, you did this on a, let's say a NIH grant, funded this thing. Why should you get the money and not like the government, you know? Right. Well, you grace the right hands, you get to keep and not like the government you know right well you grease the right hands you get to keep the patent that's how it works

ah okay cynical but i am very yeah and the house always wins anyway so yeah no so this comes back to a broader um broader point i wanted to touch on. You know, in research, they talk, I guess we, when we were doing it, talked about, we talk about and we're required to address assumptions and limitations in our studies. And I like those two words because they tie into things that people take for granted, right? So, we're going to define these as best we can. So an assumption is typically something that's, you know, accepted as true or plausible. You know, we're just going to leave it there. That's where we'll draw the line, right? So you just assume that something's, you know, working the way it should or, you know, I'll give some specific examples in a second because I'm

going somewhere with that. A limitation is something that you just have no control over for various reasons. You know, an instrument might be limited to, you know, certain functions, you know, or you might not have enough money to control for certain things, right? Those are limits of your study. Well, nobody ever thinks beyond the study itself, right? There's a big giant assumption in professional research, and that is that a scientist is somehow more honest than a non-scientist. is that a scientist is somehow more honest than a non-scientist you know that's a big one right because the guy is still a fucking human right but you are making that assumption when you take research or the famous phrase studies say at face value right and people don't stop to think and this is a you know it's a point i'm going to hit on the coaches conference this weekend that i may

have hit on on this show before. I'm not sure. I've kind of like delayed really talking about this publicly for a while. I had to be out of school for enough time to get over that PTSD. But that's a big assumption. You're assuming that a scientist or a professional researcher, we're just going to call them what they are. We're assuming that a professional researcher is more honest than the average person, right? That's a big fucking assumption. And then when it comes down to the publication process, people forget

you are reading a self-report. Let that digest for a second. Some of y'all listening that are familiar with research papers, a peer-reviewed article is a self-report. What is being reviewed? research papers. A peer-reviewed article is a self-report. What is being reviewed? What's being reviewed is a written account of what somebody told somebody else happened. So you're playing a game of telephone here. No matter how you want to spin that, that is what it is. So it's a big fucking assumption, right? So you're assuming that what was written reflects what happened. That's a big assumption right there. You're also assuming that the person who reviewed it accepted it as is, that nothing was modified because if things were modified at the behest of the reviewer, that's not going to be reported, right? So you have those assumptions, right?

And you're also assuming that everybody who participated in the study was skilled, experienced, and had knowledge to do what they were doing. That's another big assumption, right? Because what about these low-budget studies, right, have a bunch of master's students, you know, who trained them, right? The doc student who got trained by who? The other doc student? Kind of like we used to talk about, first coach I met, strength coach I met was actually a professor at this institution I did my undergraduate at, Western Illinois University. If you're ever in Macomb, Illinois, Tim Piper, good guy. He supports our stuff. And I remember when I told him I found starting strength, he said, good book. So that was the first time I went to a gym, similar decor to RIPs, lots of old pictures of meets and stuff. It was my

first time in that environment. He taught me how to lift. And the joke he always had was about lifting technique, right? He's like, the senior teaches the freshman who becomes a senior and teaches next freshman. So they're all learning from the senior, right? Sad to say this, I would say, and Steph, you can speak on this too. I think a lot of this happens in academia a lot of the time, but I don't know. I've only been to like two or three institutions and certainly not at the caliber of the one that you went to. So that's a big one, you know? So you got a lot of the blind leading the blind in a lot of these places.

So a lot of people don't know that, right? Like how do they get people to carry out some of these techniques? Sometimes if they have enough money, they might hire somebody with expertise. They might hire a technician that's done it for a living and has done thousands upon thousands of procedures, or they might have students teaching students, which is what I saw, right? But again, you're making a lot of assumptions about human behavior and there is no audit of the work. Nobody's showing up at these labs. Like, the NIH gives us money.

They're not sending people over there to spy on them and see if they're doing what they say they're doing. The assumption is that they are doing exactly what they say they're going to do and that they're going to report it honestly and that the reviewers are going to accept it as is and only, you know, check for fucking, you know, non-technical related stuff, right? And that, the media is going to report it honestly too. Let's not forget that because where do people learn about research? They learn about it on Instagram, social media, New York Times, etc. So, lots of assumptions about human behavior that people don't even consider in all this, right? And that's not to say 100% of it's dishonest, but that is to say that it's probably safe to assume that a good

chunk of it probably is, especially when you're dealing, which you said earlier, you got more and more people involved, right? How many institutions do we have? How many researchers per institution? You're talking about thousands upon thousands at this point, right? Yeah, right. Yeah. Yeah. So this is one of these things, and this came up with this, you know, ridiculous stuff that's gone on over the last several years with, you know, the COVID lies and things that happened with that. So people a lot of times will be like, well, why would somebody lie? Or, you know, they're looking for motivation. Guys, like, take a good look at yourself.

So, first of all, I mean, there's times when you outright lie. You know, when do you lie? Because a lot of times they're, you know, little lies, but they're just, it's convenient for you for whatever reason. Or you just say something to make yourself more, they're kind of small things. You say something to make something more interesting. It's very easy to cut corner, kind of cut corner kind of lying. And that's a lot of the stuff that goes on here. So when we say dishonesty, we're not talking about somebody sitting in a room with Satan

making plans. Yeah, that's right. We're talking about somebody who it's more convenient for them to do this. You know, it gives them some benefit to turn this in. They go along with something instead of calling it out when they see something. People do stuff that's convenient for them. I had this conversation with a guy who lost a job, and he was all upset about what had happened and how it had been handled. And I said, they got rid of you because you weren't convenient for them. It wasn't worth it.

I mean, it wasn't about what you did or didn't do. They just wanted you gone, right? It's the same kind of thing here. So a lot of things that happen, it's like, it's convenient for somebody. They want to keep their job. What do they do when the guy over them wants them to do something? They just go, okay, I didn't see it. I didn't see anything. They're not going to call it out and lose their job. I mean, some people will, but guess what? They're not in those positions for very long. There's just a thousand compromising things that happen all the time. And you do them too, because everyone figures out ways to excuse their behavior, right? To rationalize it.

You do what you want, what's convenient, for whatever reason right then. And then you find a way to say it's okay. Now, the thing is, the assumption people have, though, is this is like some sort of like pureness. This is the pure ivory tower thing. These people are in search of truth. Guys, even when you're in search of truth or trying to do the right thing and be honorable, it's tough, right? Because we're people, like Santana says. But I think a lot of them aren't really trying to pursue that, you know?

Like, we think classically, oh, you want to, you know, science is about the pursuit of truth. It's like, we're talking about people. They're like postmodernists. They don't believe in truth anymore. You know? Yeah. It doesn't even play with them. It's like,

what's good for you? And it's my truth. You're a truth. You know, it's like, have somebody who says something like my truth, be a scientist. It's like,

well, I think there's a fundamental conflict right there. A hundred percent. They don't actually believe in truth. It's kind of hard to not lie constantly, which is already something that we're susceptible to doing, right? So it's like, guys, people suck, you know? We're not skeptics here. time you know what else has changed with the with the bureaucracy getting larger and larger with science and the money getting bigger and bigger well what's changed is we've gone from you know

a bunch of white anglo-saxon protestants to a bunch of atheists who don't believe in truth now fundamentally you know i'm saying don't have a a fundamental uh the same kind of fundamental association with truth as a as a fundamental reality right we have people that are relative it's like obviously you're gonna have problems yes guys yeah and it it's even you know i i can think like on a more mundane level i can imagine if you're if you're looking at test results and, you know, like you said at the beginning of the show, you go down all of these little avenues of tests and tests and tests, and they all, you know, they all turn up negative, right? They're not, that's not right. That's not right. That's not right. You need to reformulate our hypothesis. That's not right. And maybe this

takes years. I can imagine there's an enormous amount of pressure to produce something even though that's good science as we described at the beginning of the show that doesn't i can't imagine that looks good when you're in a panel of your peers and you're going to you know present at symposiums or whatever it's just like well i tried a hundred things and they all failed versus having a breakthrough, you know? Yeah. So the thing is, um, they don't want to publish negative results, but negative results, like you point out, the things that don't work are information that are actually, it's like really actually very important. Sure. Sure. They don't want to, they don't want to put that there. And then going along with that, when you come back to the

dishonesty, it's what I call the cop problem. Okay. So, you know, when a cop knows you're guilty, guess what you are? You're guilty, right? You know, so it's like, I know you're guilty. You know, why did you plant the drugs on him? Because he was using drugs. So obviously, you know what I'm saying? It's like, you're setting up a situation you believe to be correct. Well, if you believe in this idea you have as being the explanation, you find ways to keep believing it. So it's like you look at certain things, you interpret it certain ways. It's like you're not really even trying to be bad, but that's what people do. And they double down down they double down and over and over and over keep going with it instead of considering that maybe their basic assumptions

were not correct maybe something's wrong with their experiment they've invested their time their ego in it you know sure sure well i imagine some some people here are going to say well but we have ways of controlling for bias in research, right? We have random sampling, right? Oh, yeah. Do we want to jump into that? Well, yeah, sure. So, yeah, you've talked about this on the show a few times, Santa. I go off about this a lot. So, the type of research that I was involved in was applied research because it was based upon what, you know, what I do now. You know, I wanted to learn more about that. And I

thought the good old ivory tower would teach me something. And, you know, I came into the industry as a professional. You know, I've been training or training people for, you know, at some capacity for over 20 years, but I started working, working about 14 years ago, right? And there were two things that were dominating the industry. One was this corrective exercise, fake physical therapy bullshit that doesn't seem to fucking die. And two was citations, you know, we're starting to circulate, you know, and then all of a sudden, you know, guys that, you know, claim to be gym trainers or strength coaches or bodybuilding coaches or whatever the fuck suddenly have, you know, PhD or DO or MD next to their name, you know, suddenly everybody's a

doctor, you know, and DPT, I guess. So, you know, I thought, you know, a lot, you know, as a self-employed person, I'm like, well, to be competitive in this shit, I need to do that too, you know, because I need to understand this because people keep asking about it. Now that I'm older, I look back and I'm like, I was just in a fucking bubble because most people don't give a flying fuck about this shit. And the people that do, I don't really want to do business with a lot of them because of what I'm about to talk about now. So when you start getting into human subjects research, which is applied science at its finest, you know, you have a couple of problems that you run into. So, you know, there's guys on the Internet that will, you know, sit there and tout randomized control trials, right?

And this is considered the gold standard for conducting research. So let me just define a few things here. So you got a couple different types of research. You have experimental research, which I'll define in a second. You have observational research. Observational research is your epidemiology, your correlations where they'll look at things at a single time point or they'll look at things at a single time point or the look at mass population data and look at relationships between it. And you can't really, and you can't really derive a cause and effect relationship from that. So for those of you who've heard correlation is not causation, that's where it comes from. You know, you're just basically gathering data from, in this case, a bunch of

people on, let's say a particular outcome, right? Look at strength levels, right? So you might look at strength levels, but then you might measure other things, right? Like body weight, right? So it's a good one for this audience, right? So you might measure somebody's bench press and then measure their body weight, and then you might do that with 10,000 people, right? Then you'll look at relationships, right? Between body weight and bench press, right? Bigger bench press, bigger body weight. I don't have to pull a citation for that. That's probably true. But, you know, that's your classic observational research. And they have quasi experimental research, which falls under that observation umbrella, where you might assign people to groups, but it's not random. You know, you might have volunteers, you know, say, I'm

going to throw you in a, you know, in a lifting group, and I'm going to throw you in a control group where you sit on your ass eating Cheetos, right? And I'm oversimplifying here. I'm not going to go into any specific design when I'm defining this, but that's, you know, that's non-experimental research. So they call that quasi-experimental. Then you have your experimental research. And when, what makes a research study experimental is the random assignment of people to treatment and controls, right? So the reason you're going to use something, so I'll go into random sampling next, but random assignment pretty much allows you to understand or allows you to infer whether

any effect that took place was because of the treatment, right? So if you had somebody lift and somebody not lift and they gained muscle mass, you can be confident that the group that didn't lift or that did lift put on the muscle because they lifted. Right. Because you randomly assign people have an equal chance of being in either group. Right. So you're washing out any bias there. Right. Can you generalize that? Nobody ever thinks about this, right? So they always talk about the randomized control trial, you know, and then they try to say, well, look what this study found. They used the gold standard. Therefore, you should take this conclusion at face Like you're bench pressing a stability ball bullshit. I don't know if they randomly assigned there, but all the random assignment tells you is that the treatment or intervention probably was the cause of whatever effect was measured, right? It does not tell you what would happen in a broader population. So let's say that you're studying men in my neighborhood and you get people to volunteer and you randomly assign them to a control group or, you know, a training group, right? You know, if they improve, you can be confident that it was because of the training, right? But you can't say that every single person in the neighborhood or the majority of people in the neighborhood are going to benefit from this because these people volunteered. So I always say if you want to generalize your findings,

you have to sample randomly. So what that would look like is, theoretically, because we don't do this, you'd flip a coin, and based on that coin toss, you determine which address is going to be hit up to pull a participant in, right? And then you get a random sample of, let's say, you know, let's say, you know, there's a thousand people in the neighborhood, you get a random sample of, let's say, you know, let's say, you know, there's a thousand people in the neighborhood. You get a random sample of 100, right? You got 10% of the population, right? And I'm just pulling shit out of my ass. So I don't know if that number is correct or incorrect.

I'm just trying to, you know, use some easy round numbers here, right? So you got 10% of the population of people in this neighborhood. And you randomly sampled them, right? So, everybody in the neighborhood, because you used every address in that zip code, everybody in that neighborhood had an equal chance of being in the study. Then you randomly assign, you conduct the study. Now you can generalize because the people who didn't participate had the same chance to be in the study as the people that did participate. When you use volunteers, you don't have that. So, now you got people that are interested, right? You know, how are they? Are they different than people that are not interested?

What about people that are not interested, right? So that's like, you know, one basic question of that, right? So you can only generalize if you randomly sample. Now, what a professional researcher or a wannabe professional researcher on Instagram might say to you is, well, you know, you just recruit enough subjects. Well, who decides what's enough subjects? Well, the next answer they'll give you is, well, look at previous research. Okay, well, how did they decide? Well, they looked at previous research and they looked at previous

research. You know, that's problem number one. You know, there's just this pyramid scheme at this point. You know, you're going back to all these other studies that decided on this number based on what some other guy decided on, right? But then is the number even big enough from a practical standpoint, right? So like, you know, I don't want to turn this into a whole big COVID episode. We're not going there, but I looked at the COVID data and the number of Americans in the Pfizer trial was 14,000. The total sample is 40,000, right? So you had 14,000 volunteers that were American. We're going to set aside that the United States of America is a heterogeneous population. So we have lots of different ethnicities spread out across this country, different by state, different by city,

et cetera, et cetera, et cetera, versus a country like China, where I had to look this up for something I was writing in my PhD, actually. I think 99% of them are Chinese. That's definitely over 90%, right? So that's a homogenous population. But let's set that aside for this argument. So you have 14,000 participants from this country. That's not even a percent of the population. So you've studied this vaccine on a fraction of a percent of the population. And I'm not, you know, confirming or denying the vaccine. I want to kick kicked off fucking YouTube here. And I'm not, you know, confirming or denying the vaccine. I want to kick off fucking YouTube here, but I'm just talking about the stats here, right? We got 14,000 Americans. So 14,000 people in a country of 360 million people. Now I'm not going to quote media because, you know, I can say one thing and they can say, well, it's not exactly

what I said. You know, the inference was that every single American should take this thing. You know, I mean, I'm sure that's not exactly what was said, but, you know, that's kind of what was suggested. Can you really conclude something like that off a fraction of the percent of the population? Because 14,000 sounds like a big number, but not in the context of 330 million, right? So, I always say that. Do we ever have enough subjects? Because we never even, a lot of these studies never even touch a half a percent probably, you know, when you're looking at these controlled trials. But then you go back to assumptions, right? Let's say that you get 1% of the population, right? So, what is that? 3.3 million? Is that right? people, how many humans do you have to hire to carry that out? And then are you going to spread these people across the nation? We're just, you know, fucking, you know, we're in fantasy land

here, obviously, we're not gonna do this. But let's say you had 3.3 million Americans spread across the 50 states, right? Well, now you got different people in different states carrying out different tests, you know, and then you got different, you know, different environmental factors, like, but the main thing that I want to hit on there is you have a lot of people you have to control, right? And as we talked about earlier, once you start scaling shit, things just get shittier, right? Because, you know, it's just gets harder and harder to control human behavior, especially, I will say, as the skill level of the thing you're trying to do gets higher. You can't scale something like that,

right? So how do you monitor, test, assess, carry out an intervention on 3.3 million fucking people, right? You can't. So, you know, typically you're not going to do something like that. You might look at smaller populations, but even then you start looking at this data, like they'll say, oh, this study is on women. What's half the fucking population, right? You're still not going to touch a percent. I don't even know if you'll touch half a percent. So is it ever enough subjects to override the need to randomly sample to give your population an equal chance of being in the study? I would say probably fucking not without having read every single fucking study in PubMed. Probably not, you know? But yet, when you start looking on social media in this business, because I want to keep it to this business, you start looking on social media in this business, because I want to keep it to this business,

you start looking on social media, they'll say, oh, look, this weird angled bicep curl works better to grow your arm because these scientists did a study where they did sets of 30 and God knows what else on, you know, a hundred subjects, a whole hundred, hundreds, a lot of people, you know? And then it's like, the fuck you know like you know there's what was there like four billion females in the we're talking i said females earlier that was the example i used so what we got four billion females on the planet like what women you know what what what uh what country you know what state province etc what city what neighborhood you know what uh you know what are those things they they call when you're looking at zoning? When you're looking at zoning, they have like little quadrants for neighborhoods.

I forgot the name of it. There's a word. Right, right. Yeah. So, I mean, so that's true. I mean, so the idea with a random sample is that the samples are not going to be biased, but it still doesn't mean the samples are the same. Right. But, you know, the thing is you run into other problems mean the samples are the same right but you know the thing is you run

into other problems if the samples are the same so there's there's a lot of you know things that have happened over the years that you know nobody talks about unless you're in the particular area research search and you can start to see some of these problems so back at like you know 1900s around there for some bizarre reason don't ask me why i wasn't there not quite that old people had this hobby it was popular to have mouse colonies people would breed mice which sounds like really not interesting to me but anyway so i mean this was like a thing people did. And so over time, you know, people would develop their little strains and breeding and breeding and breeding, what do you get? You essentially get clones. You get a homogenous population.

So there have been these mouse strains that have been around. And then of course, they got used for research studies because then it's like okay cool now we have basically identical animals in group a and group b so now when we do our we don't have this sampling problem he's talking about we have identical animals well the problem is when you go to extrapolate out you find that well that's true but the effects in one population these little black mice over here, very well are different from these little white mice over here. And so sometimes you can't, you're not going to see an effect because let's say you're doing something that you're trying to see, can the mouse learn? Okay. And you give them a task and, you know, some silly thing in a maze or whatever, right, where the mouse is learning.

Well, what happens if you're running your test on the stupid mice? Takes a while to figure out that they're the stupid mice, right? Right. The stupid mice, the effect is so small because they're just not good at learning. You can't find the effect. Yeah. You know, if you're testing a drug, you can't find the drug that changes their ability to do whatever it is because you're missing.

You're just missing because you're looking in a group that's the same. There's also been cases where researchers thought they were working with the same animal, but they weren't because what happens sometimes in a population? You get a mutation. Yeah, right. We had cases with rats where it was the same rat, but the rat from this company that provided the animals grew twice as fast and grew almost twice as big as the same animal from the other companies that had that same, you see my little air quotes here, the same rat. And so you're like, well, how can them you know right it's not the same you think they're the same they're not and then they're they're not the same because the population being this clone restricts what you can extrapolate to the other populations or like mice as a whole or people or whatever the heck you're trying to take it to so no matter what you're doing there always, it's very easy to be wrong.

And there's a hundred thousand different ways to be wrong. And I can imagine. It's a lot harder to be right. There's a, there's a, the, uh, the lead, the lead, uh, author in the study is like, hey, listen, we've already spent $15,000 on rats. Like you're going to use that rat. Like, you know, just say it's, just say it's the same rat. We don't have the budget for labs

it's still a business yeah labs using that one rat would stay with that because now they're comparing their studies over time but they're at least it's the same rat sort of maybe who knows right yeah who knows what other things you don't know have changed that weren't so damn obvious because you know you can see like why is it so big i thought you know the age is the same right um so there's just and there's just so many things you don't know you're like well what are you feeding your rat versus my rat right right one of the big things is is with animals is the reaction to men versus women have you guys run into that no like humans like the reaction so let's say you're working at lab we you got a new job you have to go in and count mouse poops cut off the tails for dna samples whatever you're doing right so you're the guy that's doing the

experiments you're the poor little graduate student so you got the worst job you got to go in there in the middle of the night and do these things with these mice or rats or whatever. You know what? You know what stresses animals out differently is when you do it versus me. You know why? They're sexist. Cause you're a boy and I'm a girl. Yeah.

So now imagine if you're allowed was studying like stress responses in animals oh man right yeah yeah how much of this quarters cortisol response that we were measuring had to do with the fact that the the guy deal with animals or dudes and the animals go this is a male on alert versus the female where they're like, yeah, whatever. You know? And of course, people in, let's say, they're working with stress response. They're working the HPA axis, cortisol, all that stuff. They're like, okay, I don't know what we're going to do.

But they're at least aware of the problem. What about the people who don't realize that their animals are being stressed and it may be affecting their experiment, but they don't know it because they're not really thinking about stress because that's not what they're really trying to test for. They're doing something else. Right. Yeah. Yeah. It's such complicated. I've seen how dogs react. Let's go to the gym and just get strong because it's a lot easier than this nonsense. I mean, that's what I say, but then you get a lot of guys that read all this weird bullshit, you know, that'll say that science says or research says or so-and-so said that research says that, you know, we need to do a bunch of light weights for high reps because that is the science. And that's what gets you hypertrophy, right? And it's like one of our favorite words to shit on here. It's like one of our favorite words to shit on here. It's unfortunate because it's, you know, it's a scientific word.

You know, it's the enlargement of muscle mass. But it's come to mean that you have to do this weird type of training that is typically done by fucking drug addicts that like to do these quasi beauty contests to impress other drug addicts. And now the lay public thinks they need to do some weird angled fucking super isolated exercise for sets of 30 and keep track of the number of sets they do instead of the amount of weight they're lifting. Because that's what science says. Yeah, and you can frame things kind of however you want. So somebody doing that is using whatever science they're looking at for their marketing, right? That's right. And so they're kind of acting like a lot of scientists when they do that. Right, yeah.

I mean, you know, I used to say this. You know, I thought I might tone it down for the episode, but I'm not going to. to you know i said this about scientists but i've i'm gonna include these people that uh are uh disseminators of science you know they may or may not have a phd that they've never used which i do have a phd i've never used you know i mean i've got it and i do this for a living so i'm not hating on that but you know i also don't call myself fucking scientist you know i barely dropped the credential you know i've been told like uh myself a fucking scientist. You know, I barely dropped the credential, you know, I've been told. Like Neil deGrasse Tyson. Yeah, exactly. Or that Japanese guy with the really good hair.

Yeah. Like every physics video. There's several guys. I don't fucking sit, I don't call myself a fucking scientist or even a professional researcher because I'm not. You know, I'm a gym owner. You know, I've authored some articles. I guess I'm an gym owner. I've authored some articles, so I guess I'm an author too. And I do this podcast episode, but I don't sit here and say I am a scientist. And I don't deconstruct papers because I just, and sometimes the claim is obviously fraudulent and stupid, but sometimes the guy, half of what the guy is saying is probably true, you know? And they'll say, well, look what the research says, and I'm like, you just discredited this bullshitter with this bullshitter, you know?

Like, they're both full ofshitter, you know, like they're both bullshit sometimes, you know, like I've seen that happen many times, but when the whole thing doesn't do what it purports to do, you know, professional research doesn't answer questions about what the fuck you should be doing in your daily life in many cases. Sometimes they get it right, you know, like there's meta analyses out there that say that if you add weight to the fucking bar, you're going to grow no matter what the rep range is. That seems pretty plausible. But then meanwhile, these guys will ignore that part, you know, the no matter what rep range you do and tell you to do sets of 30. And then ignore the part where the sets of 30 were cable bicep curls or knee extensions

or something, some single joint exercise that makes sense to be done at a rep count that high. They're not squatting. They're not deadlifting. They're not bench pressing. You know, they're not pressing and they're not doing chins or anything like that, you know, but they like to leave out the details because again, marketing. So let me get back and not escaping what I said I was going to say. The way I've described these people, and if you want to build on this, Steph or Trent, you can, but when I talk to the lay person about a professional researcher, I say they are used car salesmen with extensive vocabularies. Hmm. Yeah.

And I kind of want to tie into what you were saying there, talking about some of the problems. about you know some of the some of the problems the biggest problem you start taking things over to training which is what we do is none of these studies i'm not the sample sizes have problems the methods have problems the things are measuring have problems the retarded exercises have problems but even if those things didn't the study is this long it's's short, super, super micro short. You know, you can't generalize. You can't generalize any of it. And you're talking about something that extends over a period of time. So it's like your information is just it's irrelevant because it's such a short term thing.

It's irrelevant because it's such a short-term thing. So even when you're just talking about this and you said, talk about the increasing the load, you know, so you're progressing the load, you get the results, doesn't matter the rep range. What matters is if you're doing that 30 rep range, are you able to progress load? You know? So if you're looking at the thing over the time, what you would find is that, okay, sure, do your 30, whatever the heck it is um and you think it's going to help you but then what you find is you can't keep progressing the

load using that rep range you know if you just did it for a while instead of like try to figure it out and be super smart boy and skip the steps and you actually lived it you actually went in training the gym and you increase the weight on the bar and over time you saw your progress go up you'd learn a lot you know sometimes rip will say something like uh someone will post something on the board about this xy guy does this and thinks this and he disagrees or whatever and you know it's like well when you deadlift x amount you and with RIP it changes different times. Let's say this. When you deadlift over 600, you get to have an opinion.

Until you haven't done it, you need to just shut up and just add weight to the bar. You don't need the fancy stuff. You need to actually develop some expertise, which you don't have. And it's expertise not in what you're thinking about doing, what you're planning out, and your your best ideas about the best way it's the expertise that develops from actually having your feet in the gym the bar on top of your back and you're actually doing performance and that just takes that takes time it takes putting in the work thinking about things and arguing on the internet is great if you want to do it i have a limited tolerance for these things but it's like well go

to the gym what are you doing in the gym right now it's complicated by the drug picture so there's a lot of people that start out with pretty good genetics they pile on the drugs and unfortunately most people in general public don't understand that you know the genetics has a huge difference in how things are going to go for you and then the drugs as well and if you have some with good genetics that piles on the drugs guess what yeah right yeah they can yeah they you know they sniff glue and they you know they gain like you know muscular body weight right it's not gonna not going to work for you. So, um, so there's complicating factors there, but the main thing is if you go in and you put in the work,

you'll be able to see where there's problems in this smart boy stuff coming out, like a paper showing X, Y, and Z. And you're like, the paper is dumb. Why is it dumb?

It's just, yeah, it gives you like a hundred reasons. I don't have all day. It gives you context. well you know i could i could think about something like uh rpe came to mind right so like the the concept of rpe and the practice of implementing that into a program if you're if you're a guy and you're squatting 225, like you just don't have the experience of what a heavy squat, a legitimately heavy squat does to you in terms of fatigue and, you know, and the amount of stress it imparts and how you can recover from that over a reasonable, um, window of time. If you can squat

455, you have a much better idea of how much stress you can impart in a workout and how that can affect everything else. And then you might, you have, in the process of getting there to 455, you have found, you have run into problems in your training where the squat has interfered with something else and you had to figure that out. So it gave you context for that concept of RPE that you just, you're never going to get unless you've actually solved that problem before. I think we run into this all the time with these, you know, we see advanced athletes that have had to address these problems, talk about their training programs, and people who are far less advanced try to you know they try to kind of work that back into their own program this doesn't work well the thing that has here's a here's the overlap so you know i shit on rpe every chance i get and rir the new one but you know when you look at like what some of these legitimately strong guys are doing when they're using rpe is the the net result is lighter weights are being lifted for

sets. And you know, we talked about doing that, you know, we got our volume day, you know, volume day intensity date on Texas method, you know, we talked about that. But we're using percentages, we're using objective load. And what I was going to say is, for those guys, when they're doing that, those light weights are hard because they're fatigued and that's really what you're trying to create right you're trying to you're trying to get some work done when you're beat up from the fucking heavy set but the end goal especially you know competitive guys like who was it that popularized rp was that to share that's who i think of yeah yeah yeah yeah so motherfucker what's his best deadlift? Like nine or something? He pulled over nine, right?

It's up there. At least 800. Yeah. Yeah, either way. Either way. Definitely eight, right? So, if that guy goes fucking heavy, he's going to have to lift, quote unquote, light weights, and we're going to define light as a percent of max, right? His percent of max is going to be lower than somebody who's fucking deadlifting 200, right? Well, actually, somebody who's deadlifting 200s on the LP, but I digress. But my point is, those light weights are tiring and anybody who's made it to solid intermediate or advanced understands that when you have to take weight off to build up work so you don't detrain, you're going to use quote-unquote light weights to build that up.

Now, are you also going to be a pussy about it? And, you know, well, you know, this feels right today. No, let's not do that. That's not what we do here, you know? Like, I know that tomorrow I got to squat 360 for four sets of five. I don't want to fucking do it.

If I put an RPE on that, I might do 315, you know? Right. If I said, oh, you know what? I just hit 410 for a set of four and a half last week. So the next week I got, I'm not gonna be able to do that again. So I have to wait a couple weeks. So, you know, I'm just gonna do an RPE seven. Guess what? 410 will go for zero next time because I'll do 275 next week, you know? Right. Yeah. yeah so and there's a lot of context too because you know if you're looking at something like rpe for somebody who's like aggressive in their training they're kind of using that to hold themselves back but the general public is not aggressive

in their training so you have like some guy that thinks he ought to be a little stronger, that thinks a 315-pound deadlift is a lot. And I'm like, yeah, if you're a 100-pound girl, yeah, it is. They have that kind of context. Those people end up, the actual reality of what happens on the ground, those people use RPE to lift less and to get less done. So if you give it to the crazy guy, you're kind of like, oh, just hold back, hold back, because you're going to kill yourself with your training. These other people, you're like kicking them to try to get them to do anything. So it's a completely different context there, right?

That's one reason those things don't carry over. It's because you have to know who you're dealing with, you know? things don't carry over it's because like you have to know what you're dealing with you know and and and they got the aggressive crazy guy you know everything he's doing is centered around lifting a heavier load at some point whereas the other guy wants to completely make load an afterthought that's two completely different situations for one guy it's all about load and for the other guy it's about evading load. Yeah. Yeah. Yeah. So if you give people a way to get out of something, I was mentioning, I was talking about earlier about how people are dishonest in ways where they're not really trying to be dishonest.

They're just trying to make something easier on themselves. It's kind of like, that's how people act with dishonesty. RPA allows you to be dishonest with your training and with the stress you're doing right so you have an excuse to do less people are lazy horrible you know bias coming up with excuses for all sorts of things this is a thing that allows them to do that does everyone do that way no but come on you're dealing with people like human nature yeah it's like i mean you take something that aligns with human nature in a way that's going to give you a bad result you like you already know what's going to happen here you know it's like if you give me ice cream what's going to happen i'm gonna eat the ice cream that's right let's go on but don't bring it to my house yeah i think that that's what i that's that's what i was drawn to when I first found starting strength is that the process of doing the novice linear progression is, I mean, to me, a non-professional, you know, non-educated person over here, that is, it's science, right? Like there's a process of, of observation, you know, so for first you have

to do the training, right? So you do the training, you execute the program, and then there's observation that comes after that. Like, you know, you learn a little bit about a stress, stress recovery and adaptation, and that there's a window of time that it takes for you to recover and to adapt to the point where you can lift more weight. And it's very obvious in an obvious linear progression because it more or less happens in a 48-hour window, but from workout to workout. And then eventually it breaks down and you observe that happening. So you're sort of proving out these theories that you're reading about as you're doing the program. And so it's this iterative process. And if you just pay attention to the patterns

in your own training over the course of a few years you learn a lot about how you know how strength training works you learn a lot about how programming works and um that to me is that sounds like real science you know that's like an actual scientific process right there. I mean, I guess there's not like a hypothesis, you know, maybe there is, I don't know, maybe you can, maybe you can make it work, make the analogy work. But, but the point is like, there is a lot that's demanded of your own experience executing the program. And then like, what are your senses tell you? You know, like, Hey, my back is completely fried. I couldn't break off a warmup, you know, a warmup weight. I couldn't break it off the floor today. Okay. Something's going on.

Um, and so you go back and you troubleshoot, it asks you, what are my senses telling me rather than like, what does some expert say that I should do with my training? How many sets and reps I should do? How should I progress it? Yeah, you have to accumulate that training experience to really have that, you know, and every situation is going to be different because as, you know, we talked about earlier, human beings are very different. You know, there's a lot of similarities, but this idea that we're mechanical robots, that you can plug and chug a cookie cutter equation into and yield whatever outcome you're looking for, that's fantasy land. That's not how it works, you know? The state of my advanced training is going to be different than Trent's,

and it's going to be different than Steph's as well, you know? And the way that I have to modify variables for that is going to be different. You know, the further along the adaptation curve you go, the more individual it becomes you know yeah and and the thing is you're doing that on yourself so all that that learning you're doing as you train um you you push into your limits and they're they're in different places for different people you'll find things that work for you. Just the other week at the seminar, we're talking about belts on the press. And you know most people really like belts on the press.

I don't wear a belt on the press. I can't wear a belt on the press. It just messes me up. I don't do it. And I'm a person with a good press. I pressed over body weight. Not very many women have. And it's like just thinking about putting a belt on makes me just not want to press.

Just thinking about putting the belt on because it interferes with my back position. Sure, yeah. But I tell people to put a belt on, right? So there's, you know, that's just things get more and more individual as you go along. And the way you recover from stress, what like just ruins you is going to be different from other people. And you can't just copy anybody. You know, and remember too, you know, this belongs somewhere in our talk earlier of research and, you know, certainly, it's certainly important here. You know, when you're, when you're looking at studies on lifting, you know, since that's what

we're talking, since that's what we're, that's what we do, you know, lifting or diet, you know, none of them control for lifestyle, 0% of them control for lifestyle. So, you know, that's, that's the biggest variable and that's the number one thing people are limited by from coaching, from a coaching perspective, you know, the one i've coached probably thousands of people at this point and i'd say lifestyle is the single greatest limiting factor and um in terms of training and diet progress yeah just i mean just overall health really right it's just it's like what what are you doing yeah that's literally that's literally the question what are you doing can't answer that yeah yeah yeah you can't just change

the little thing up here it's it's everything you're doing right you have to look at that i can't answer that as a coach and they can't answer it as a professional researcher i don't know what the fuck they're doing and they'll tell me one thing they'll tell them the same line of bullshit and but they'll have a fancy form they haven't filled out you know that's been validated you just don't know you can't control for lifestyle and lifestyle is the single greatest limiting factor for not just this stuff a lot of stuff if somebody wants to go from point a to point b at anything lifestyle is going to get in the way you know unless that is their life you know but and that's something else you know if

this is what you do then you know you're gonna do just fine but if you're trying to do if you're trying to improve an outcome in your life and get it above baseline uh and the context of your lifestyle you know that then you know you're gonna have some challenges there you know things will go slower less efficient as what i've noticed yeah living proof over here right now the last two years of my life. So I'm sitting here thinking like, okay, so we've shat all over the modern professional research. What is the scientific method good for in what we do? Does it have any place in health and fitness broadly. I think, you know, when I was talking about the programming problems earlier, one thing that I always cling to is the first principles that I know of, right? One of them being like stress recovery and adaptation. That is a very simplified model of how an actual human being responds to the stress of training in the gym. And then of course, lifestyle has a enormous impact on the recovery part of that equation, but it does work. Like

that is a thing that happens. Like stress is incurred in the gym and recovery does take place over a period of time. And if the two, those two factors are sufficient, we get adaptation. Like I see that happening all the time. I see when it breaks down all the time. So clearly like there was somewhere a scientist figured that out, right? If we go back to Hans Selyes, who we usually credit for that basic model, the general adaptation syndrome, he had to figure that out. So I'm kind of wondering, where do you see the intersection? Where do you see science actually meaningfully contributing to what we do? Okay, so here's the thing. What you just described was an engineering problem,

not a science problem. So what I mean by that is that you're looking at what works and adjusting as you go on, but like the why isn't necessary. Like if it was eating lucky charms is what made you get your squat up. You know what I'm saying? Right. And that was the real reason behind your success. You didn't even need to know that. It's just like you just ate your breakfast and you squatted. So it just has to do with like, this is an applied deal. Sure. Okay. Where I think science helps, and of course this overlaps with engineering too, is what really helps when we're looking at our training and we're deciding what to do in the gym, we're evaluating how things are going, is having a systematic and analytical approach, right? Because it doesn't really matter if some of the things we think are wrong. If we're getting the job done, it doesn't really matter why we fly, right?

Yeah, sure. Right. You don't actually have to know why it works when it's working and when you're making progress. why it works when it's working and when you're making progress so i think just overall the emphasis on science is is a mistake it's it's hubris really because we're so smart we're doing it the magical way you know the right way because we understand everything when the fact is we actually don't right yeah yeah that's i like the way you put that because that's me too the longer that i do this the less i really know about how things work i was a lot more confident you know four or five years ago about how all this stuff worked behind the scenes now i don't really know but i i but yeah i have a process that i can go through to figure out how to solve problems and to get the weight on the bargain.

Right, to solve problems. More like a mechanic than the professional researcher, right? Right. And I mean, all sorts of things that, I mean, there's, you know, if you could just jump forward hundreds of years or whatever, there's going to be all sorts of things where you find out we're complete morons and everyone laughs at us because of what we did. I mean, maybe I can think about training, but just all sorts of dumb things modern people believe. You could look back and laugh about something that people trusted in 1810. And you're like, you do understand that people are going to be laughing about you not too long in the future okay right this is true and not just about your ridiculous 80s hairstyle right they're gonna

they're gonna be laughing about all sorts of things you believed and you're such a retarded yeah they're just gonna be like i can't believe people actually fell for that nonsense you know and died because of it you know right right i can't believe that anyone ever ate crisco you know um just all sorts of things yeah well although although i i i feel like nowadays i look back with a lot more grace at at old thinkers you know and how they came to, you know, so like, if I'm looking at like a medieval physician, it's like, well, we need to balance the humors. You know, you don't want to have an excess of bile or whatever. Like, but what they're really talking about when you take away their specific sort of like model that they have is, well,

there has to be some sort of like balance in, you know, in your life. Like, you can't eat to excess, you can't eat, you know, you can't fast to excess, you can't exercise to excess, you can't exercise, not exercise at all, which more or less makes sense. You know, there's those things sort of, there's these truisms that you keep running into over and over that reveal themselves. Right, right, right. Or, I mean, something taken to excess caused certain problems, but it did help other problems that were a problem. I'm not talking about bloodletting or whatever.

So, yeah, bloodletting is the stupidest thing ever. Hey, how many guys have to go in and donate blood because they have too many red blood cells? It's a pretty common thing, right? So, you know, if you have hemochromocytosis, it's like you have to dump that. So, it's like, have to dump that yeah so it's like it's like yeah maybe every other person maybe if you just were bleeding out let's

not bleed you more but you know it's like there's there were benefits there you know and they probably noticed certain benefits and then maybe they took it too far and applied it too often or whatever the case was, but they weren't just crazy. Yeah. You know? Yeah. There was something behind it that made them think it was worth doing. Yeah, I think that's, I mean, I'm a hopeless, I'm hopelessly into like Western civilization and like the beginnings of Western thought. And I've read very little of him but i'm working on

it uh uncle aristotle is kind of the father of modern science as we understand it in the west and uh most of the specifics that he came up with are probably wrong you know like you know how elephants communicate or whatever um i don't even know if he saw an elephant but you know there's probably some specifics about all the fields of science that he touched on that are that are all wrong but more or less he believed that we have senses and our senses give us fundamentally correct information about our environment they don't they don't lie to us in a in a categorical way like yeah we we can be biased but that's not that's different from it they don't they don't lie to us in a in a categorical way like yeah we we can be biased but that's not that's different from it they don't they're not totally it's not totally false

information so we do have the instruments of in ourselves to evaluate the world and observe and then draw conclusions about what we see and i think that's a pretty powerful uh baseline to your earlier point i don't know that that's the philosophy that everyone ascribes to nowadays i don't know if they truly believe that that you can draw conclusions based on your own observations uh maybe because for some people there is no truth to get to you know there are no fundamental patterns to recognize. Yeah, I think there's a disturbing... I mean, worse, I say worse because they feed into each other, right? So it's hard to say what thing's worse when you have a problem or a series of problems. But I mean, so relativism is a problem. It undermines all sorts of things, right? Yeah. But it seems now that people are getting to the point where they believe they can just make up reality, right?

So it's not just, I saw the event differently from you, Evan. You know, my position is different from yours. And, you know, that's kind of like, you know, just like a difference of opinion because you saw a different side of the, you know, you're in a different place in the movie theater. It just looked different to you. But a more malicious thing where it's like, actually, like, I'm inventing reality. It's like, well, we used to call people that did that crazy. But it seems like now we have to call them whatever they, you know, want. Yeah.

Right? And I just see people that uh they could just go along with it you know so it's like well someone's crazy you know walk away you get that bad feeling in your gut leave right you don't want what's coming next but um it's it's like a reversion to this magical thinking of like how things are going to work. Like, it's like, well, you know, I'm a cat or whatever the deal is, you know, it's like, yeah, for Halloween. Right. And they're like, no, I'm really a cat. Like, no, you're really not. Right. So it's, it's kind of, it's, it's like, it's not,

reality is not real to people like that anymore, you know? Yeah. And I can only imagine that you you can i can only imagine you get to that state by not engaging in reality you know like i love the phrase you know the zoomers nowadays they have this phrase and i love it i steal it all the time they they say uh touch grass like hey you need to go touch grass like you got to get out you got to get out in the real world and experience some things because it teaches you these, these realities. It's, it's fascinating to me. I have a toddler right now. And, um, part of being a toddler is you gain all of these physical skills. Like every week you're learning how to do something new physically, and you have all of this freedom

to explore that you didn't have when you're just a baby and you can barely get around. have when you're just a baby and you can barely get around. And so just like watching him go around the yard, we have a, we have a very weirdly sloped yard out here. So it's all sorts of like, you know, crevices and hills and rocks and stuff for him to climb over and run into. He learns a lot just by going out and experiencing things like, Hey, that's a ledge. If you try to walk off of it, you're going to fall. And it really hurts when you fall or like, that's a ledge. If you try to walk off of it, you're going to fall and it really hurts when you fall. Or like, that's really hard. If you run into that, it's going to hurt. This seems like just obvious things, but you have to learn that. And he's learning that through actual interaction with the world. If he never went out there, he would never

learn these things. And he might draw all sorts of wild conclusions about how the world actually works that are totally different from the way it actually does. Yes. Yeah, so I think that's actually a huge problem. And there's people that live in such an artificially constructed life that they're not touching grass, as you say. They're not absorbing all sorts of things. And they're very susceptible to whatever's put in their head. Right. Because they're not experiencing things for themselves and trusting their own experience.

This ties back into like we were saying about like trusting the science or trusting the experts. It's like, well, what do you think? And there's a lot of people who seem to have lost just how they talk about things right you can tell they're like well so and so says i read it on the internet this and you're like well what well what did what do you think you know and they actually are in a point where they discount their own experience as secondary yeah as not as legitimate as something that could be entirely fabricated you know right it's coming you you know it's coming over the internet it's like well

you know we like movies look real you know and they're not real right um so the whole thing could be faked and you know they fake things i mean it could be like news right people they they get caught staging things right and left like guys and and you just believe it why they lied to you yesterday why are you listening to these people don't listen to liars right now right um that cuts down on people you have to these people don't listen to liars right now right um that cuts down on people you have to listen to quite a bit but if i'm if i'm dealing with like let's say let's say uh you know you're my next door neighbor and you bullshit me right i you get a lot more feedback about the level of bullshit if that's over it's like you know if you were like internet

dating you're not meeting the person you know they it's like, you know, if you were like internet dating, you're not meeting the person, you know, they can lie about all sorts of things. If you're actually face to face, yes, they can fake it, but they'll slip up. It's easier to see the problem because you can be deceived so easily, much more easily when you're not actually doing real things. Right. Have you ever heard the term dry labbing? Have you ever heard the term dry labbing have you ever heard the term no i haven't heard no i have not i have not dry labbing so okay imagine doing experiment here and

i'm like you know i have this you know cell preparation here and i'm putting chemicals on it that's a wet lab that's an actual experiment dry yeah you're coming up with things in your mind on paper, right? So, I mean, that could just be like thinking of ideas and that's fine. But if you actually decide how something's going to turn out, I'm just telling you, it doesn't work. It never works. So, when somebody made up an experiment with the euphemism for faking data is dry labbing. It's just dry labbed. It's just fantasy. He just made it up, you know? Right.

And people live like that. We've talked about here a lot. I borrowed this phrase from Santana. Does it pass the smell test? We talk about the smell test a lot. Yes. And, you know, somebody's talking about some concept about programming or, you know, exercise selection or whatever, whatever studies they pull out of their ass, at the end of the day, it has to pass the smell test of like, well, does this actually stand up to what we see coaching people every day? And it seems to

me like the good products of professional research are the things that give us some insight into the why something happens, but then they also line up with our practical experience. It's like, oh, yes, I've seen this phenomenon happen in my own sample size of the 300 people I've worked with or whatever that number is. Yeah, I've observed that phenomenon whatever that number is. Yeah. I've seen, I've observed that phenomenon. I've observed that pattern. It lines up with what this research is telling me. That seems like that's the,

you know, that's a useful intersection of research and coaching. Yeah. Well, that's, that's where you're actually like evaluating it. Right. Yeah.

I mean, so like theoretical stuff, it's like, that's nice, but, you know, what really matters is what actually happens. Mm-hmm. Yeah. Right? Sets of 30. I like how the set— I can barely get to three without messing it up, you know?

Yeah, the rep count keeps going up, you know, what high reps are. It used to be 15s, right? 15s, now we've gotten up to 30s. 30s are the new thing now. That's the new thing. Are they? Oh, yeah. But, you know, like,

just before I close out on this, what I've kind of figured out here is when they're talking about 20s and 30s and all that stupid shit, they're not fucking squatting and deadlift. They're not doing anything technical. They're on a fucking knee extension or a bicep curl or something that can be reproduced 30 times in a row, right? Squat can't be reproduced 30 times in a row. You know, deadlift cannot be reproduced 30 times in a fucking row. But then the broader concept that they're inferring is that what happens in one

exercise needs to happen in all exercises and i think that that's not addressed clearly a lot of times um both by people that are you know uh selling that bullshit and by people arguing against it right like okay 30s well were we okay 30s on a fucking knee extension? Does that mean you need to do 30 squats, though? You know, like, ask the right questions, you know? How long is that going to work? Like you said, you know? And how are you going to measure that? Okay, you can't add load anymore, add sets. What are you going to do? 100 sets? Now you're doing cardio, you know? If you have the time to do that, you know? So is it even a strength stimulus anymore, you know? So you can't add sets forever, you you know you can't add load forever on these things i just think that you know in terms

of you know um you know how we talk about eventually you know there's an asymptote you reach your genetic limit right it takes longer to do that on exercise like the squat i think you hit that pretty fucking fast on an exercise like a cable curl, you know? Right. And I think that's what we're talking about here, right? Mm-hmm. You know, how long are you going to progress any extension, you know?

A few months? A year? I mean, I don't know anybody who's silly enough to try and train that year after year, you know, because the guys doing that, they cycle out the exercises too, you know? But, fuck, man. Yeah. I don't know. I think that like, once you start getting into that shit, there's a lot of context that is lost there, you know? So it's like kind of what you said earlier.

It's not like, it's not totally dishonest. It's misleading is probably the better word. Cause yeah, I would not want to do a set of five on a knee extension and throw out my knee, you know? So, sure, 30s makes sense. But then how long are you going to progress the fucking thing, you know? Right. And how does something like that actually affect your overall performance? Exactly. Your strength, your health?

Exactly. It's like, you know, we used to, you know, this is like exercises, right? It's like, great. Like, why are you doing that? And it's like, what is hypertrophy? Okay, so they say that the cross-sectional area of the vastus medialis or the vastus lateralis, sorry, they don't do the medialis because of the arteries. The cross-sectional area of the vastus lateralis, you know, increased after 12 weeks of 10 sets of 10 knee extensions. Well, what the fuck does that mean? How much, you know, am I going to notice that? Are you going to

notice that, you know, if I'm the one that did it, you know, like how much are we talking about here? And is that going to continue? Because we know that if, as you continue applying a stimulus, you know, you get less and less result from it, right? So, you know, what magnitude are we talking about? A year of knee extensions versus a year of squats nobody's going to compare that for a lot of reasons right nobody has you know yes it's the old 25 of what kind of trick exactly yeah you know sorophy, sarcoplasmic hypertrophy, you know. Yeah, I've arrived at the conclusion, for better or worse, that I don't need to read a scientific paper maybe ever again. Did you arrive at that just now?

Well, no, I arrived at that a while ago, but yeah, you know, I just, I don't really see, you know, if I can, I can understand the attraction to the world of science for someone who has, has just an abounding interest in the world and wanting to actually like get in there and experiment with that. The process of, of like good scientific research is interesting to me but yeah from from an actual application you know so if you're listening and you're a coach or if you're listening and you're just a lifter and you're interested in this stuff yeah i mean i i the literature is kind of the last place i think you need to be looking for for for information for insight is that fair to say yeah am i wrong yeah i would agree with that

um i it's kind of like one of these things that i'm just horrified when it happens like someone will get in contact with me maybe it's you know somebody in a prep course maybe just someone online randomly and they want me to look at some paper and And I'm just like, why are you torturing me? I don't want to see it. I don't want to look at it. Please. Why? Why would you do this?

I can think of things that would be so much more fun, like toothpicks shoved underneath my fingernails, you know? Dipping my body in nitric acid, you know? And yet, they come to me and they think, they think because I have the, you know, background that I want to do it. It's like, did you notice that I'm not doing that right now? I'm not doing that right now. Yeah, sure.

Can you give me something on chickens? I'm getting into chickens and- Oh, yeah. If you give me something about chickens, I will read about chickens. Thank you. We'll talk offline more about chickens because yeah, we have chickens now. It's wonderful. That's right. Great little creatures.

They taste good too. Yeah, mine are great. The border collie does not agree with that position. Yeah, we've had some incidences with our dogs. We had to have some conversations. But anyway, well, thank you. Thank you, Steph, for taking some time to talk to us about this. I think it's interesting because a lot of people, you know, if you're in the field and or at least you have some like very tertiary experience with scientific research like I do, I don't have any hands-on experience, but I have read a handful of papers and I've been around a lot of smart people like y'all who have been in it. If you don't have that experience, I think it could

be real easy to get sucked into the hole of like, well, but this science, you know, this paper says, or this expert says, so it's good to see a peek behind the curtain. Yeah. Yeah. Well, thanks for, thanks for having me on. I can, I can kind of wander about on the topic quite a bit. So. to wander about on the topic quite a bit. That's what we do here. Let's do it again. We'll find some paper or topic. I like touching on broad topics that have a lot of papers behind them.

You know, I don't want to deconstruct the paper. Don't torture me. I'm not looking at papers. I don't either. We're on the same page. I do not deconstruct papers. Chicken papers. Yeah, there we go. Chicken papers.

Chickens and board collars. Murray McMurray Hatchery Magazine. We'll use that as our literature. What did we say on the other episode? Well, so on the last episode we did, like we really should have had you on the last episode because we did an episode all about training considerations for women.

So we got two dudes over here, you know, mansplaining. But yeah, I think that would be a more interesting topic to talk about. Cause I know, uh, one of the things we, we talked about was, um, I think people try to, people make this automatic assumption that just because you're training someone who's female, that training has to change. And, uh, that's in my experience, that's not the case. You you know just because you're training a woman doesn't mean that she automatically has to do threes and uh has to have a different program and all that kind of stuff no and you certainly wouldn't start out that way right exactly exactly

so the more athletic the person is the less they're gonna be like that you know yeah so oh i invoked you on that one. There's always weird cases. Yeah. So that, yeah, maybe, maybe if we can get you back on in the future, we can talk about maybe some, like some interesting experiences you've had training other people. Maybe. I don't know. I'm, I'm, I'm not, I don't trust you guys anymore. There's that slight talk about making me look at a paper and I and I'm feeling a little bit like, no. I wouldn't do such a thing.

He said it, not me. What I meant to say is we pick a topic that people like to cite and shit on that. There we go. Okay. Like bench pressing on a stability ball. Yeah, yeah. I can definitely, I don't mind telling other people they're stupid yeah yeah yeah i can be very direct that's stupid that's the fun part all right well you want to you want

to close this out sir sure thing thank you for tuning in to the weights and plates podcast you can find me at weightsandplates.com on instagram at the underscore robert underscore santana or if you're in Metro Phoenix, come by Weights and Plates Gym. We're just south of the airport. We have private training, gym memberships, and really good equipment. All right. Well, hey, you know where to find me. I'm on Instagram at marmalade underscore cream. That's also the name of my audio production company. So if you have a podcast that you need to be produced or that you want to start, I'm the guy to talk to. Send me an email, trent at marmaladecream.com. And Steph, how can we find you if we want to find you? Or can we find you?

Yeah, I can be found. So steph at startingstrength.com is the best way to get in touch with me. All right, excellent. But no papers. Yeah, no papers, please. Do not send her papers. Yeah. We're going to have to hold her back from doing like committing federal crimes. If you send her papers. All right. We'll talk to you all again in a couple of weeks. Thank you.