Outliers, Revisited

Episode Summary

Episode Title: Outliers, Revisited - The episode revisits the "relative age effect" that Malcolm Gladwell discussed in his book Outliers. This refers to the advantage given to older kids in youth sports and academics simply because of their relative age. - In the 1980s, psychologist Roger Barnsley discovered that a disproportionate number of elite youth hockey players in Canada were born early in the year. This is because the age cutoff is January 1, so the older kids within each age group have a physical advantage that makes them more likely to be selected for elite teams and training. - Gladwell argues this arbitrary age advantage becomes entrenched over time. The same patterns show up across various sports and in academic tracking. Older kids are more likely to be labeled "gifted" and younger kids more likely to be seen as struggling. - To illustrate this, Gladwell did an experiment at the University of Pennsylvania. He had a group of seniors answer questions about their birthdays and upbringing, then assigned them "privilege scores" based solely on their birth month. The scores showed a clear pattern - the highest scores went to the oldest students in the group. - When told about the scores, the students resisted the idea of adjusting for age in academics. They argued it would undermine the validity of scores and could be gamed by parents. Gladwell argues their cynicism shows how resigned we've become to unfairness in the system. - The episode concludes by discussing potential solutions like "maturity adjusted scores" that are starting to be used in youth sports. Gladwell argues we should implement similar approaches in education.

Episode Show Notes

Did Malcolm Gladwell blow it in his bestselling book Outliers? What if all he did was write a primer for neurotic helicopter parents? To find out, Revisionist History descends on the University of Pennsylvania to run a roomful of eager students through a mysterious experiment, complete with Sharpies, huge white stickers, and a calculator. It does not end well.

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Episode Transcript

SPEAKER_20: People are excited about what AI will do for them. At IBM, we're excited about what AI will do for business. Your business. Introducing Watson X. A platform designed to multiply output by training AI with your data. When you Watson X your business, you can build AI to help coders code faster, customer service respond quicker, and employees handle repetitive tasks in less time. Let's create AI that transforms business with Watson X. Learn more at ibm.com slash Watson X. IBM. Let's create. SPEAKER_09: From Pushkin Industries and Ruby Studio at iHeartMedia, Incubation is a new show about humanity's struggle against the world's tiniest villains, viruses. I'm Jacob Goldstein, and on this show, you'll hear how viruses attack us, how we fight back, and what we've learned in the course of those fights. Listen to Incubation on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. Is choosing employee benefits harder than you expected? Keep your business competitive by looking out for your employees' needs with quality benefits from The Hartford. The Hartford Group Benefits team makes managing benefits and absences a breeze while providing your employees with a streamlined world-class customer experience that treats them like people, not like policies. Keep your workforce moving forward with group benefits from The Hartford. Learn more at theheartford.com slash benefits. SPEAKER_03: The Hartford Group Benefits team is a proud sponsor of the Hartford Group Benefits team. Pushkin. SPEAKER_03: In the middle of our preparations for season seven of this, Your Favorite Podcast, the revisionist history team got on a train to Philadelphia. Four of us, carrying props, recording equipment, and extra microphones. Our destination, the Gothic ivy-covered cathedral of higher learning that is the University of Pennsylvania. And why did we go? Because we had cooked up a little experiment, and we were curious to see how it would fly. SPEAKER_09: Thank you. Thank you. Thank you. We commandeered one of the main lecture halls SPEAKER_01: at the Wharton School, invited 75 or so students, all seniors, smart, focused, disciplined, SPEAKER_03: future masters of the universe, and asked them to answer 10 simple questions such as, how many years of your K-12 education were a public school, and how many were a private school? How many years of your education were a public school? And how many were a private school? At the time of your graduation from high school, how many continents had you visited? At any point during your middle school and high school years, did your parents provide you with a private tutor? SPEAKER_17: How you doing today, Mr. Balwell? Pretty good. I'm doing really well. SPEAKER_03: I looked out at rows and rows of eager students, hunched over their desks in anticipation, took a deep breath, and began. So my name is Malcolm Gladwell. I am the host of the podcast, Revisionist History. The theme of this season of Revisionist History is experiments, and one of the experiments of this season involves all of you. So you guys are guinea pigs? Yes, guinea pigs. Because in the manner of all guinea pigs, they were entirely in the dark about what we had in store for them. And as you probably guessed from some of the questions that you were given, what I'm trying to do is I'm conducting an experimental investigation into the nature of the privilege of the people in this room. The students quickly finish the questionnaires and put their names and birth dates at the top. My producers, Eloise and Harrison, are sitting at a big table at the front of the room in full view of all the guinea pigs. They go through the completed questions one by one and use the answers to generate a number, a score, which they write on a giant white sticker with a big fat Sharpie. And now the real experiment begins. I'm going to assign every one of you a number. If they can figure out what their number means, they will understand something essential about how broken the system was that propelled them to the Ivy League and how to fix it. Just peel off the back, and I'd like you to affix the sticker to your chest so we can all see each other's numbers. You're going to look around the room, see everyone else's numbers, see your number, and hopefully that will aid you in your investigation of what exactly the nature of this experiment is. I'll just read... The students sat there with their numbers stuck to their chests, looking around in befuddlement, trying to make sense of everything that was going on. I tried to help them figure it out, gave them hints, nudges. Think about this. I gave you a series of questions. Some of those questions involved a yes or no answer. You saw two people, Eloise and Harrison, who quite quickly, in the space of about five minutes, ten minutes, went through 75 or so responses, and were able to very quickly and easily assign you a number. So, we were able to assign you a number. So, think about this logically. It wasn't a complex algorithm, right? There was no computer used. Eloise, how long would you say you were spending on each questionnaire? Five, six seconds. Okay, that's the clue, guys. SPEAKER_13: Let's go. Come on. SPEAKER_03: Hi, my name is Abe. They might have just looked at the zip code, because that's a pretty good presentation. I'm going to give you a little bit of a quick overview. SPEAKER_04: I might have just looked at the zip code, because that's a pretty good predictor of privilege, just in and of itself. SPEAKER_03: Abe has derived his hypothesis from question six. What is the zip code your family lived in during your high school years? Perhaps, he speculates, the number on his chest was some kind of complex, mysterious derivative of his zip code. SPEAKER_04: I didn't see if you had a computer, but if you did... There was no... Eloise, was there a computer? SPEAKER_03: No, I did have to use the calculator one or two times. SPEAKER_12: Captain, Abraham, with all due respect, SPEAKER_03: are you suggesting that Eloise and Harrison had memorized every zip code? It's plausible. They're very smart. Not that smart. SPEAKER_19: I'm Zach. I think it really has to do strictly with the private versus public education system in the U.S. SPEAKER_03: Nope, that's not what we were looking for. Hi, my name is Joseph. SPEAKER_10: A question that I thought was very interesting on there was about if you have any siblings and if so, how many. Nope, not that either. SPEAKER_19: Hi, I'm Kaylee. One that I don't think I've ever been asked in relation to this was if I drank when I was in high school, what age did I get drunk at. SPEAKER_03: Kaylee's referring to question number nine. In high school, did you drink alcohol? And if yes, when did you first get drunk? Could you come up with any reason why I would have asked that question or do you think that's just one of the ones that I'm just blowing smoke on? SPEAKER_19: I have my own hypothesis, but I can't. Oh, come on. What if I'm wrong? SPEAKER_03: This is all about being wrong. Oh, this is all about being wrong. Once upon a time in 2008, I wrote a book called Outliers, the first chapter of which was devoted to a phenomenon discovered in the 1980s by the Canadian psychologist Roger Barnsley. Here's some of what I wrote. The explanation for who gets to the top of the hockey world is a lot more interesting and complicated than it looks. Good Lord. I do not sound like I'm enjoying reading my own book. Listening to this part of the Outliers audiobook now, I'll admit I have some regrets about that chapter. We'll get to that, I promise. Anyway, it occurred to me as I planned our trip to Philly that I should talk to Barnsley again and go over his discovery one more time, make sure I understood everything. So I called him up and asked him to retell the story of how in the early 1980s, he and his wife, Paula, stumbled upon what has come to be known as the relative age effect. We were living in Lethbridge, Alberta, SPEAKER_02: and we went to a junior A hockey team. It was the Lethbridge Broncos at that time. SPEAKER_03: Barnsley's wife, Paula, started reading the game program, which had the rosters of both teams listed in it. Paula said over to me, SPEAKER_02: Roger, when do you think all these hockey players were born? And I remember thinking to myself, well, you know, that's kind of a silly question. So I did a quick calculation. I said, you know, Paula, their average age, 18, it's about 1982, so they're probably all born in around 1964. And she said, no, no, no, I'm not talking about the year. I'm talking about the month. And I said, what are you talking about? And she opened up the page of the program where they had listed the roster of the team, and it just jumped out at us, just jumped out that the majority of these players were January, February, and March. And then you seem to get the odd April and May and very few in the fall. And I said, my goodness, that's just remarkable. SPEAKER_03: He went home and expanded his search further. Everywhere he looked in competitive hockey, same thing. For some reason, most players were born in the first part of the year. And that's when that famous 40, 30, 20, 10 SPEAKER_02: by the course of the year showed up. SPEAKER_03: The famous 40, 30, 20, 10 phenomenon that he's talking about is what in Outliers I refer to as the iron law of Canadian hockey. Quote, in any elite group of hockey players, the very best of the best, 40% of the players will have been born between January and March, 30% between April and June, 20% between July and September, and 10% between October and December. End quote. Now, why is this? It's because Canada is obsessed with hockey and coaches start picking players for all-star travelling squads at the age of 9 or 10. Since the eligibility cutoff for Canadian hockey is January 1st, that means the coaches are choosing among 9-year-olds who are as much as 12 months apart. And 12 months age difference at the age of 9 is a lot. The January kids are bigger and stronger and more coordinated than the December kids, which means that the January kid is more likely to be chosen by the coaches for the travelling squad, which means, in turn, that they will practice two or three times as often, play more games, have better coaches, better competition than the kids left behind. And what began as a completely arbitrary advantage based on a quirk of birthdays turns over time into a real advantage. SPEAKER_03: The same phenomenon holds true in other sports, soccer, swimming, you name it. You can find the relative age effect everywhere. And of course, it also applies to the classroom. Teachers aren't any better than coaches at disentangling ability from maturity. So relatively older kids in elementary and middle school end up getting more encouragement. They tend to get better grades. And they're more likely to be chosen for things like gifted and talented programs. Meanwhile, relatively younger kids are more likely to be diagnosed with learning disorders or flagged for problem behaviour. I cannot tell you how many parents have come up to me over the years and said, because I read your book, Outliers, I held my kid back from starting school and it was the best decision I ever made. Of course it was. But parents holding their kids back doesn't solve the problem. It just creates a relative age effect arms race. There's a fancy private school near me where so many parents of younger children have held their kids back that now the parents of the formerly eldest children have responded by holding their kids back. Whereupon the first set of parents are increasingly holding their kids back a second time. Meaning that there is at least a theoretical possibility that in the most competitive corners of American private education some kids may never graduate from high school. Maybe I should have seen all that coming when I wrote Outliers. I should have made it clear that I was not trying to teach neurotic upper-middle class helicopter parents how to game the system. I just wanted schools and sports leagues to stop behaving like idiots. So, Barnsley's paper on relative age effect came out in 1985. Outliers, which was I think the first time Barnsley's work got wide publicity was published in 2008. The world has been alerted for decades to the fact that all kinds of supposedly meritocratic systems have been hijacked. Has anything changed? You're in front of your computer. I am. Are you? I put the question to Roger Barnsley. The OG of relative age effect research. What have we learned? Can you Google the roster of the Canadian junior hockey team, national hockey team for 2021-22, the current roster? I'll do it right now. And I want you to go down the list of the forwards just use the forwards for the sake of simplicity. And I want you to just read the 21 months of birth of the forwards on the current Canadian junior national hockey team. Their birth dates are just their names. I just want their birth months. SPEAKER_03: Okay, I see. And then Barnsley repeated what his wife Paula did decades ago at the Lethbridge Broncos hockey game. He listed the birth months by number of the members of the national junior hockey team. Listen for birth months of seven or higher. Two, ten, one, one, one, two, eleven, eight, four, SPEAKER_02: two, ten, five, four, five, two, six, one, three, one, one, five, three, two, four, seven, one. It's the same thing. It's the same thing. They've learned nothing. It's the same phenomenon you saw this 40 years ago. SPEAKER_03: The iron law of Canadian hockey is still an iron law. Isn't that funny? SPEAKER_03: It's not funny at all. It's depressing. Very depressing. Very depressing. Here we are, both Canadians. We are citizens of a country that cares more about the world than we do about the world. SPEAKER_02: We are citizens of a country that cares more about the world SPEAKER_03: than anything else. Let's be clear. Anything else. And we are leaving an astonishing amount of talent on the table. Exactly. And we're fusing to learn. What of Canada's own prominent academics 40 years ago said to the hockey establishment, what are you doing? Yeah, that's right. And they didn't, they haven't done anything. Canadian hockey hasn't done anything, but maybe revision is hitting the table. SPEAKER_03: Canadian hockey hasn't done anything, but maybe revision is history. Can. SPEAKER_20: When you Watson X your business, you can train, tune, and deploy AI all with your trusted data. Let's create the right AI for your business with Watson X. Learn more at ibm.com slash Watson X. IBM. Let's create. SPEAKER_03: Do you know that right now, as you listen to this, there's an astronaut named Frank Rubio in some tiny spacecraft way, way up there in space. He left for the International Space Station in September of last year, thought he was going for six months, and then once he was up there, NASA called him up and said, actually, Frank, we want you out there for a year, 371 days to be exact. My question is if you're NASA and you pull that bait and switch once, how do you recruit the next crop of astronauts? I mean, you say to your recruits, I need you to leave your family and friends and everything, you know, and love dearly eat food out of a tube, but only for six months. And they're like, wait, look at Frank. That's what you told him. And he's still up there. Recruiting for astronauts. If you're NASA is hard. If only there was some sophisticated job recruiting site capable of finding those few Americans who are perfectly happy to float around in space for an undetermined length of time. Sadly for NASA, there's no such tool, but for the rest of us. Oh yes, there is. Zip recruiter. New hires cost an average $4,700 for all of us, non space flight companies. And with that kind of money at stake, you have to get it right. So what's the most effective way to find the right people for your roles. Zip recruiter. See for yourself right now. You can try it for free at ziprecruiter.com slash Gladwell and experience the value zip recruiter brings to hiring. Once you post your job, ZipRecruiter's smart technology works quickly to identify people whose skills and experience line up with exactly what you want. It's simple. ZipRecruiter helps you get hiring right. Four out of five employers who post on ZipRecruiter get a quality candidate within the first day. See for yourself, go to this exclusive web address to try ZipRecruiter for free before you commit ziprecruiter.com slash Gladwell. Again, that's ziprecruiter.com slash G L A D W E L L. ZipRecruiter, the smartest way to hire. Somewhere out there, believe it or not, there's someone who wants Frank Rubio's job. SPEAKER_09: Viruses attack us and how we fight back. I'm Jacob Goldstein. And on incubation, we'll hear how scientists have pioneered new techniques in the fight against viruses. There was just something about the way the virus was shaped. SPEAKER_14: It always felt like there was no hope for creating a vaccine until now, until now we'll celebrate the victories like the incredible story of how SPEAKER_09: smallpox was wiped off the face of the earth. Eradication means you have to get to whatever disease you're targeting SPEAKER_16: everywhere, wherever it exists. Listen to incubation on the iHeartRadio app, Apple podcasts, SPEAKER_09: or wherever you get your podcasts. SPEAKER_03: The inspiration for the Revisionist History Wharton School Relative Age Effect Experiment came to me when I was talking to Adam Kelly, former footballer turned university professor. Kelly is a disciple of Roger Barnsley. He works with sports leagues to help them solve their age-related problems, like England's Basketball Federation, which spent a small fortune setting up regional centres to identify promising players. We looked at the proportion of players who were selected into those talent SPEAKER_04: centres across the nation. And that was age groups selected from 13 to 15. Both male and female. And those who were born in birth quarter one, were 10 times more likely to be selected. 10 times? Birth quarter one is the three months closest to the English basketball SPEAKER_03: eligibility cutoff date. Yeah, which is absolutely crazy, isn't it? SPEAKER_04: Same old story. SPEAKER_03: The talent spotters thought they were picking the most promising players, but in fact, they were just picking the oldest kids, because the oldest kids were, of course, the tallest and most coordinated. Anyway, Kelly's also thought a lot about education. Why is everyone taking their exam at exactly the same time? SPEAKER_04: Surely we should all be taking it at that same time within our lifespan. So if you're born in August, you're taking your exam almost 12 months earlier than someone who's born in September. So that person's had 12 months more learning than you. Which is super obvious when you think about it. In New York state, SPEAKER_03: all the big elementary school math and English standardized tests are in late March, early April. We're talking third graders, eight and nine year olds. At that age, kids get smarter every week. Yet we're trying to assess kids by their test scores. And some of the kids we're judging had been around as much as a year longer than other kids. Why don't we have the January kids all take the test in January and the February kids in February and on and on down the line? I have no idea, honestly, no idea. So I gathered the research arm of Revisionist History with our props, recording equipment and extra microphones, and headed for the Gothic ivy covered cathedral of higher learning that is the University of Pennsylvania to see if a group of really, really smart young people can figure out the importance of the month when they happen to be born. Turn over your pieces of paper, put your name at the top. And once you're finished, we will collect them. And then we will commence the exercise. So we give out our elaborate questionnaire, but secretly all we're interested in is people's birthdays. And then Eloise and Harrison go through each questionnaire and use the birth dates to do a simple calculation. Technically, the youngest you could be as a college senior at the time of our experiment was to be born in September 2001. So if you were born then, you got a zero. Zero birth privilege. If you were one month older, born in August 2001, you got a one. July 2001, you got a two and so on. The higher the number on the sticker, the older the student wearing it. We even had a contingency for students who might have skipped a grade somewhere along the way. You'd get a negative number if you were younger than the expected age of a college senior. First thing we found out, there were no negative numbers in the room. Back when I was in college, I knew dozens of people who had skipped grades. Apparently that doesn't happen much anymore, but it was worse than that. There's no zeros. Anyone a one? Two. Two's? Three's? Four's? Five's? Anyone less than 10? Stand up. One student finally stood up in the back row, a college senior who was a few months shy of her 22nd birthday. Oh, you're a 10? Oh, a 10 in the back row. Oh, another 10 emerges. We've got the 12. We've got these 12s. We've got some 10s. Take a look. This is bananas. This is as bad as the Canadian National Junior Hockey Team. In our sample of students from one of the world's most selective universities, there were no young seniors. None. Not even close. There was no one at all who had been born in 2001, which is the year you would expect most seniors to be born in. At one point, a student started talking about her experience in a gifted and talented program. So I asked for a show of hands. Do you mind me asking, how many of you guys were in gifted and talented programs? SPEAKER_03: Wow. Basically all of you. Which makes sense, right? These were a group of relatively old students, and being relatively older makes it more likely to get into a gifted and talented program. And getting into a gifted and talented program makes it more likely to get into a school like Penn, which is why a group of seniors that day at Wharton were all really old. What begins as arbitrary advantage hardens into privilege. SPEAKER_03: A simple fact about their own success that our students still hadn't figured out. I'm going to give you another clue, guys. The particular dimension of privilege we're interested in measuring, I'm going to say with a great deal of certainty, is in this room the most significant form of privilege or lack of it that you would have experienced as students. At this point, I've pulled out all the stops, trying to help them. I've had people with the highest numbers stand up. At one point, I made everyone with a number over 20 get up from their seats and line up against the wall. They were still guessing, but it was like they were throwing darts with a blindfold on. SPEAKER_13: There were pretty clear demographic similarities at the top end of the spectrum. Racially was the most obvious in my eyes. Yeah. But also just in general that there were very few at the low end of the spectrum was also noteworthy. How do you feel about being in the higher number group as opposed to the lower number group? SPEAKER_13: I mean, it's just a fact. Like, it is. I would say I'm coming into it. I'm aware of my privilege as a white woman, but I think it's about what you do with that privilege that's important. SPEAKER_03: And then, after 40 minutes of floundering in the shallow end of the revisionist history research pool, a group of students in the front row put their heads together and then raised their hands. SPEAKER_04: We have a hypothesis. SPEAKER_03: That's Adam. Everyone in this front row group had the highest privilege score we handed out. 24 plus. Of course they figured it out first. They were the oldest students in the class. Next to Adam was Joseph. He was wearing a suit and a tie. SPEAKER_10: Yeah, we have a hypothesis, 24 plus, is that a significant factor here is age, our absolute age. Like, how old are you? SPEAKER_04: Because we're all a bunch of old seniors over here. Older than usual. SPEAKER_03: Eureka! SPEAKER_03: Phase one of the experiment was over. Now, phase two. Because I intended to ask them if they wanted to do something about their arbitrary privilege. SPEAKER_20: Phase two. Learn more at ibm.com slash watsonx. IBM. Let's create. SPEAKER_09: From Pushkin Industries and Ruby Studio at iHeartMedia, Incubation is a new podcast about the viruses that shape our lives. It's a show about how viruses attack us and how we fight back. I'm Jacob Goldstein, and on Incubation, we'll hear how scientists have pioneered new techniques in the fight against viruses. SPEAKER_12: There was just something about the way the virus was shaped. SPEAKER_14: It always felt like there was no hope for creating a vaccine. Until now! SPEAKER_09: Until now! We'll celebrate the victories, like the incredible story of how smallpox was wiped off the face of the earth. Eradication means you have to get to whatever disease you're targeting everywhere, wherever it exists. SPEAKER_16: Listen to Incubation on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. SPEAKER_03: Malcolm Gladwell here. Imagine you could rewrite history. What would you change about your current employees' benefits? How could a straightforward change make your life and theirs simpler? Let's talk about what it takes to keep your business competitive. Of course, you need to be responsive to your customers. But it's just as important to look out for the needs of your employees. They're the ones who keep things humming along and fuel your company's success. So let the experts at the Hartford provide the quality benefits that your employees deserve. The Hartford Group Benefits makes managing benefits and absences a breeze, providing world-class customer care to ensure that your employees are treated like people, not policies. The best part? The Hartford offers flexible products and personalized service solutions to meet the many diverse and unique needs of every employee. From supplemental health benefits to coverage for life and loss, the Hartford has got you covered. So keep your workforce moving forward with group benefits from the Hartford. The buck's got your back. Learn more at theheartford.com slash benefits. SPEAKER_03: In Australia, they've invented something called maturity-based corrective adjustment procedures. MatCaps, as it's known, for provisional use in the sport of swimming. I will confess that I am madly in love with this idea. It turns out that if you take a bunch of measurements of kids and plug them into an equation, you can estimate their physical maturity quite accurately. So you don't have to rely on chronological age to assess someone's level of development. You can do one better and measure maturity directly. So what these equations do is they factor in indices like height, weight, chronological age, and sitting height, SPEAKER_17: and they use those factors to then estimate how far away a particular individual is from that point of peak growth. SPEAKER_03: That's Stephen Cobley, a professor at the University of Sydney who created MatCaps along with his colleague Michael Roman. Here's how it works. Imagine we have two 14-year-old swimmers competing in a 100-meter freestyle, both with the exact same birthday, Joey and Tim. So these academics would first calculate the biological maturity status of each swimmer. That is, how far each one is from their estimated point of peak performance. So let's say, for example, Joey is actually 12 months less biologically mature than Tim at this exact moment. Then comes the cool part. Cobley then looks at thousands of data points for 14-year-olds swimming in a 100-meter freestyle and calculates what is 12 months of maturity worth on average in terms of swimming time for kids competing in that age group. He enters the data into the maturation-based corrective adjustment procedures algorithm, and presto. The procedure adjusts Joey's time to account for the fact that at the moment he raced Tim, he was 12 months behind developmentally. An adolescent swim meet in Cobley's ideal universe has two sets of results, the raw results and then the maturity-adjusted results. What you're doing is you're effectively lowering the time of the folks who are slightly behind in terms of their maturity status. SPEAKER_17: Cobley did a test run of the MatCaps algorithm on a sample of 700 Australian swimmers. SPEAKER_03: All boys competing in a 100-meter freestyle. The first thing he discovers is similar to what we found at Penn. Among the top 25% of all adolescent swimmers, there were no late maturing boys. None. Zero. Which is an astonishing fact. Australia is a country that takes swimming as seriously as Canada takes hockey, and they have basically decided to banish a big group of young swimmers from consideration just because their talent happens not to appear soon enough. When you looked at these 700 swimmers, in some sense, the damage has already been done. We've already chased away the slow developers. They've quit. They've got discouraged. They thought they were bad swimmers. They didn't realize they were simply behind. Yeah. So what happens when you run everyone's race times through the MatCaps algorithm, adjusting for maturity? The order of finish in every race changes. The really talented swimmers, who just happen to be slower to mature, now have a chance. They used to be lost to the system. Now you can tell who they are. Now you can go up to young Joey and say, I know you didn't make the final, but take a look at your MatCaps time. You might be the best swimmer out there. What's the most somebody moved up? SPEAKER_17: We've seen large percentage. We've certainly seen big changes in ranks. So if we've got cases for events where someone who was outside, let's say, the top 20 suddenly was in the top three. I read your paper, and the first thought I had was, oh, wow, this belongs in the classroom. Right? SPEAKER_03: When you identify who gets into special gifted and talented programs or when you decide who just isn't smart enough or when you look at who you discourage and who you encourage, you've got to be making the same mistake. Right? SPEAKER_17: Yeah, I think so. I think the cautionary bit that we have to remember is that old question of, yeah, but how far do we go? So if we're going to factor, if we are going to factor relative aging in education or biological development in education adjustments, shouldn't we be factoring in other things that we know are influential? Absolutely. Why wouldn't we? SPEAKER_03: Well, exactly. Why wouldn't we? If we've developed a better way of identifying talent, why wouldn't we want to use it everywhere? Back at Wharton, I climbed up on my soapbox. I talked about how mat caps had freed swimmers from the tyranny of birthdays, communicated my enthusiasm for bringing the Australian Revolution to the shores of the United States. So in Australia, they started to do this. Eleven-year-olds are all swimming the 100-meter freestyle. We've got 12 kids. We have, you know, an order to finish. Then they run the times through an algorithm and have a new order. Now, would you feel comfortable with all of your, if you go back to your K through 12 experiences, would you feel comfortable if they ran all of your test scores through an age correction algorithm? Around the room, I saw young people of promise, focused, eager. They would be my disciples. I was so full of excitement, I put the question to a vote. Yes or no? I say, do a show of hands. Who likes the idea? There was a great stirring and rustling. My heart leapt into my throat. I thought I had brought the birthday rights revolution into the heart of the lion's den. I looked up, looked around, and nothing. No roar of support. Only a long, cold silence. I've never seen less enthusiasm for a great idea in my life. What is the matter with you guys? A young man spoke up first. Well, it's like, to be completely honest, to be selfish about it, SPEAKER_08: it would probably have hurt our chances of being right here in this room, because I'm old for my grade. I did well on my standardized test scores. Maybe if they readjusted it, I would have been more in the median. SPEAKER_03: He was a 22-year-old senior in college. SPEAKER_08: So, selfishly, I would say, no, it's not a good idea. From a societal standpoint, perhaps. So, you're being honest. I'm being honest, yeah. It's like saying, you know, legacy admissions or something like that. My father went to Penn and my mother went to Penn. Oh, you're drowning in privilege. SPEAKER_03: Exactly, I'm drowning in privilege. How did you? If we get rid of this, you know, I'm just going to be honest. SPEAKER_03: That's fantastic. Who else wants to? Then, Mateo raises his hand. He's an 18 on his sticker. An age privilege advantage of a year and a half. And I think that's a poor idea, because it assumes that everyone who is older is always going to be smarter. SPEAKER_07: Everyone who is younger is always going to be less smart. I've seen some pretty old people do some terrible things. No, no, no. Mateo, that's not what it does. It's neutral. It just adjusts for the age gradient. SPEAKER_03: I want my score to be my score. But wait, wait. Can I just harp on that? You said you want your score to be your score. But why is an adjusted score, a score that accounts for your degree of maturity, somehow less characteristic of who you are than an unadjusted score? I would have thought the opposite. SPEAKER_03: A score that doesn't include information on your level of maturity would seem to be more artificial than one that does. I don't know. I guess I would want to look at the algorithm before I made an actual judgment, because I'd be surprised if I was okay with everything, theoretically, everything that the algorithm would say. SPEAKER_07: The students stood up one by one, using their prodigious powers of analysis and imagination, to come up with one objection after another. SPEAKER_03: Why do you think you guys are so hostile to attempts to remedy the situation? SPEAKER_11: My fear with the algorithm is that it could be gamed. If this were implemented where we know that if you're younger, you get, say, a 100-point bump in the SAT, or are viewed more favorably throughout your whole educational career, then we're probably sending our kids off to kindergarten at 4. Or we're planning, whenever we have our kids, looking at whatever the cutoff date is for kindergarten, in September maybe, and saying, all right, we're going to reproduce nine months before that. In December or January. Yeah, but it's the current system that's being gamed. We're responding to the gaming, are we not? SPEAKER_11: Yeah, so I guess the fear is that the algorithm could be re-gamed. Yeah. Yes, exactly. SPEAKER_03: I put my hand on the table to steady myself. My head was spinning. These were the children of outliers. Children raised according to the rules of a game I kind of helped set in motion. And now, the consensus among 75 elderly Ivy Leaguers was that the system should remain rigged in favor of the elderly. The apple cart must remain upright, with the shiniest and oldest apples on the top. Now, do I blame them? No, I don't. This is what happens when we give up on fairness as an essential principle. All that remains is cynicism. The students of Penn do not see the point of changing the system because their parents did not see the point of changing the system. And their parents didn't see the point because the schools didn't see the point. And the schools, for goodness sake, can't even rise from the slumber of their indifference to see that it makes no sense to give everyone an assessment test on the same day. We game the things that we've given up on. I tried my best in outliers, but I subtitled the book The Story of Success. And if I learned anything from that afternoon of Penn, it's that we want to think about success as a word to describe ourselves, our own progress. But it's not really people who are successful. It's the systems around us. Great students and great hockey players come from great teams and great classrooms. And if you want to judge the success of those teams and classrooms, start by looking at their composition. Like, when was everyone born? And if we can't get that one right, God help us with everything else. Alright, thank you guys. I hope this has all been fun. I hope this makes you feel free to wear your numbers for the balance of the school year. My next producer is Mia Lobel, original scoring by Luis Guerra, mastering by Flon Williams, and engineering by Nina Lawrence, fact checking by Keisha Williams. Special thanks to Salman Ohad Khan for production help on this episode. I'm Malcolm Gladwell. Hey, Revisionist History listeners. I'm capping off this episode with a preview of a new Pushkin show that really has me hooked. It's called Death of an Artist. Death of an Artist has all the elements of a gripping story. A suspicious death, a tumultuous relationship, a murder trial, questions of morality, feminism, power imbalance, and a divided art world. On September 8th, 1985, up and coming artist Ana Mendieta fell from the 34th floor window of her husband and famous sculptor Carl Andre's apartment. Host Helen Molesworth asks, was Carl Andre involved? You'll revisit Ana's untimely death, the trial that followed, and both the protests and silence that have followed this story ever since. Okay, here comes a sneak peek. You can follow the story by searching for Death of an Artist wherever you get your podcasts. SPEAKER_06: It's May 1973, Iowa City. There's a damp chill in the air. We are on a sort of shabby block in front of a brick apartment building with a white door in need of a paint job and a storefront window with its blinds drawn shut. The sidewalk just in front of the door is covered in blood. And it looks like the blood might be seeping out from under the door jamb. It's a busy weekday, and as pedestrians pass the puddle of blood, they notice it and casually step around it. Eventually, a man in a green and black plaid jacket pauses and looks around, as if looking for an explanation. When none comes, he walks away. Then a well-dressed white woman uses her umbrella to poke at the bloody puddle. But after a moment or two of inspection, she also walks away. Finally, an older gentleman emerges from a nearby storefront and silently cleans up the mess. And the evidence of whatever happened is suddenly gone, and with it disappears any account of whose blood was spilled and how. The whole scene is being captured by two young women in their 20s, sisters who sit in an old car parked nearby. One of them holds a Super 8 camera, the kind you'd make home movies with back then. The other snaps photos with a 35mm camera. They are Ana and Racline Mendieta, Cuban refugees who landed in this unlikely place as children. In 1973, Ana was a first-year MFA student at the University of Iowa. She was funny, loud, outrageous, and had a take-no-prisoners vibe. And, in the way of sisters, she had roped Racline into helping her make a new piece. And like many works Ana made, it would come to seem tragically prophetic in the wake of her death. SPEAKER_19: She basically staged what looked like the remnants of, you know, physical violence with what looked like blood in the doorway of a building. And I thought it was extremely powerful. For a very young artist to be doing that, and to be doing it in this small, largely white town of Iowa City, was fascinating to me. That's Connie Butler, one of the many curators who would come to admire and study Ana Mendieta's work in the decades that followed. SPEAKER_06: The photos and film the Mendieta sisters took that day would ultimately become a work of art called Moffat Building Piece. The fact that it still exists only in these little 35-millimeter slides, which, you know, you have to get very close to with a loop, SPEAKER_19: and it's a very intimate way of viewing these things, you know, that implicates you as a viewer too, almost as if you are yourself looking at a crime scene. SPEAKER_06: Ana's interest in blood wasn't only meant to shock. She was keenly aware of violence and injustice. When she made the Moffat Building Piece, she was investigating her own community's reaction to a brutal crime, a rape and murder that had happened on campus a few months before. Here's how she explained her inspiration. A young woman was killed, raped and killed at Iowa in one of the dorms, and it just really freaked me out. SPEAKER_00: So I did several rape performances type things at that time using my own body. I did something I believe in and that I felt I had to do. SPEAKER_06: That's not actually Ana Mendieta's voice you're hearing. That was Tanya Bruguera, another artist from Cuba, who you'll hear from more later. Ana Mendieta's question was, could you make art about something so awful? And she used blood, not paint. Blood is the most essential substance of life. Could it jolt people out of their daily routines? Could blood make people pay attention? She didn't know it yet, but the Moffat Building Piece was about to be her first major artwork. And in a circular way, that's kind of terrifying. The question she asked about how we react when we encounter the residue of violence. This question would haunt all of us after she died. I'm your host, Helen Molesworth, and from Pushkin Industries, Something Else, and Sony Music Entertainment, this is Death of an Artist. Episode 1, The Haunting. SPEAKER_12: For my entire professional life, I've been a member of something called the art world. SPEAKER_06: An exclusive network of artists, gallery dealers, curators, collectors, and philanthropists. For two decades, I was lucky enough to be a museum curator, making me one of a small group of cultural insiders who determine what art we see and how we talk about it. In the museum world and in art history, there are a lot of unspoken rules about what you can say publicly and what is supposed to stay private. It turns out I wasn't that good at sticking to the script. And I guess I'm still not good at it because I'm going to tell you Ana Mendieta's whole story all the way to its shocking and troubling end. SPEAKER_12: And much to my surprise, I discovered it's a story many of my colleagues in the art world would prefer I didn't tell. SPEAKER_06: At first blush, it seemed like people didn't want me to talk about it because of who else is part of that story. Ana's husband, the famous sculptor, Carl Andre. He is one of the so-called fathers of minimalism, a cultural hero to many, a revered artist with lots of connections. And he was a suspect in Ana's death. Even though Carl Andre and Ana Mendieta were a highly visible art world couple, even though something terrible happened between them the night she died, you will not read about it on a museum wall label or in most art history textbooks. Reviews of their exhibitions tend to take care of it in a sentence or two. You would not know that Mendieta's death divided the art world in 1985, and in many ways still does. I'm not the first person to try and tell this story. In fact, many of the voices you'll hear in this show are from interviews conducted by investigative journalist Robert Katz. He published a book in 1990 that remains the most comprehensive look into this art world tragedy. He spoke with dozens of Ana and Carl's friends in noisy restaurants, in parks, in busy offices. And you'll hear the voices of some art world insiders on these tapes who have since decided not to talk. Most folks don't want to discuss what happened that night. They don't want to talk about what the ramifications of that night were on the art world. They don't want to contemplate what it means when a community is torn apart by violence. And they don't want to discuss whether or not justice has been served. All these different folks, not talking for all of their different reasons, means that a veil of silence started to fall over this project. And I can't lie, the more silence we encountered, the more sad and frustrated I became. And the more silence we encountered, the more I wanted to talk. A busy airport may not be the best way to ease into vacation mode. SPEAKER_05: But when you're an American Express Platinum card member, the vacation starts in the Centurion Lounge. Hi, welcome to the Centurion Lounge. SPEAKER_12: Mmm, what smells so good? Must be one of the chef's local specialties. SPEAKER_05: And as you sit back and relax, you think to yourself, what'll be on the menu for your Miami layover? 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