384. This Man Ended Affirmative Action | Dr. Peter Arcidiacono

[0] Hello everyone watching and listening.

[1] Today I'm speaking with Professor, Researcher, and Economatrician, Peter Parsidi O 'Connell.

[2] We discussed the recent landmark decision by the Supreme Court to end race -based affirmative action, how Peter's research was instrumental in that outcome, why merit has repeatedly proven to be the best indicator of success, and what merit is, by the way, how compassion is used to cloak racial discrimination and what might actually yield results in service to the under -resourced communities across the United States.

[3] So, Peter, let's start with this.

[4] The affirmative action has been in the news a lot, well, for a long time, but particularly in recent weeks, given the new Supreme Court decision.

[5] I think we should, first of all, alert everybody watching and listening to who you are and why people should consider you a valid source of information and what you do.

[6] So fill us in about who you are and what you do and why this is a topic of interest to you.

[7] So, you know, I'm an economics professor who studies affirmative action in higher education.

[8] And sort of as a result of that, got the opportunity to be an expert witness in the two Students for Fair Admissions cases that were recently decided in the Supreme Court, one with Harvard and one with UNC.

[9] And I took the cases in part because for someone who studies affirmative action, we've never had the data to really look at it well.

[10] Universities typically hide their data, probably as a result of these lawsuits.

[11] So, you know, there's a large gap in racial preferences between it being a tiebreaker and being what somebody like a Brom Kendi might be in favor of, of equal outcomes.

[12] So understanding exactly how big the preferences are, to me, would move us in a direction of thinking about optimal policy.

[13] Now, as it stands, you know, the way the rulings went, we're not supposed to have affirmative action.

[14] I think universities are probably going to look for ways to get around that.

[15] But the thrill was the ability to actually see Harvard's admissions files.

[16] You know, I got to actually see their full database across six years.

[17] I got to look at the actual applications themselves, look at the reader comments for a subset of these things in, you know, all the alumni interviews.

[18] It was an amazing experience, a frightening experience, but an amazing experience to be able to see all that.

[19] Okay, so let's start.

[20] with two things.

[21] Why don't you outline the cases for us?

[22] You said there were two cases.

[23] And then maybe you could step people through the typical admissions process at, let's say, at Harvard and UNC.

[24] That's going to be similar for many universities.

[25] But everybody watching and listening needs to know how universities do, how they claim they admit, how they actually admit, and how they should admit.

[26] Those are three obviously separate questions.

[27] But let's start with what exactly why exactly were these universities in court to begin with?

[28] So there's actually two different reasons.

[29] On the Harvard side, it had a lot to do with Asian discrimination.

[30] We think about affirmative action, and it really is designed to help African -American students and somewhat Hispanic students.

[31] But Asian -Americans is a population of doing incredibly well academically and also in other areas.

[32] Harvard was a good place to look at the Asian discrimination side of things.

[33] So in the Harvard case, he had both Asian discrimination.

[34] You also had are racial preferences narrowly tailored?

[35] You know, how big are these racial preferences at Harvard?

[36] So those are sort of my two parts of the case.

[37] There was another expert, Rick Callenberg, who covers race -neutral alternatives.

[38] because that's the other thing the Supreme Court has said is you're supposed to look for ways to get diversity without using race explicitly.

[39] On the UNC side, we didn't have the Asian discrimination claim.

[40] It was more on how large of the racial preferences coupled with these race -neutral alternatives.

[41] But then there's another aspect, too, which if you look back at the two Michigan Supreme Court cases, the one on the undergraduate side said, you cannot use a formula.

[42] But on the law school side, you can't use race as part of a formula.

[43] But on the law school side, you could take into account holistically.

[44] I mean, as an economist, and I'm sure for you, too, if I just hide part of the formula, now I'm holistic.

[45] So the question is, you know, how formulaic were the admissions?

[46] And, you know, my models could predict UNC admissions incredibly well.

[47] So that would also sort of speak to, you know, what does it mean, if we don't write down the formula, is it okay?

[48] You know, but, so those are sort of the harder two issues.

[49] If you don't write down the formula, and yet you couldn't derive an equation from analyzing the outcome, all that means is that the admission process is random.

[50] And that seems, I mean, you could go to a random admission process, right?

[51] You could let every comer in.

[52] and then you could fail everybody who doesn't do well in the first two years and let the survivors flourish.

[53] I mean, you could make a case for that.

[54] It's somewhat inefficient because all those people who fail have to go there and fail, and that's not necessarily so easy on them.

[55] But there are certain advantages to that because there will be surprising successes as well.

[56] That isn't generally the direction that we've chosen to go.

[57] And then if you do have a more rigorous policy, so that would be one you could hypothetically model.

[58] Well, then, in principle, in fact, this is actually by law, as far as I understand the law, is that my understanding of the law with regards to hiring and selection, at least, and I don't know if that pertains to academic admissions, is that you have to use, you are required by law to use the most valid and reliable current means of evaluation available that don't produce counterproductive and illegal racial differences.

[59] And so, and no one knows how to do that because, well, because no one knows how to do that.

[60] It isn't obvious how you can do both simultaneous.

[61] In fact, it doesn't look to me like you can, and that's a major conundrum.

[62] So, okay, so back to UNC, so you modeled their equations, and you did the same thing for Harvard, and you found, and you phrased it in these terms, too.

[63] is that for every advantage that's given to one race, let's say, or one category, there's going to be a commensurate disadvantage applied to another.

[64] And that's particularly egregious in the cases of Harvard and also, I believe, the UNC, that's particularly egregious in relationship to Asians.

[65] And how big are the advantages?

[66] And what do you think they signify?

[67] Oh, I think the advantages are enormous.

[68] You know, I went in a lot more optimistic about holistic admissions than I came out.

[69] You know, to me, it really looks like we give very large preferences across the board.

[70] It's not just on race, but also on legacies, whether you're going to be on the sailing team, you know.

[71] Right, right.

[72] Legacy, athletics, and race.

[73] Anything else?

[74] Oh, so they also have children of donors, which, and children of faculty and staff.

[75] The last group isn't that big.

[76] but the children donors, it seems sort of odd because they're supposed to have like need -blind admissions, but then there's a special list where we have children potential donors.

[77] Okay, so let me dive into that momentarily.

[78] So I spent a lot of time delving into the selection literature.

[79] And by a lot of time, I mean like 15 years.

[80] I mean a lot of time.

[81] We developed selection tests for corporations and for academic institutions.

[82] And so, like, I knew the literature, and one of my students did an excellent PhD on selection mechanisms in general and developed an entire battery for selecting students.

[83] And we looked at this initially.

[84] I was an ignorant Canadian.

[85] I didn't know this was a politically charged domain.

[86] I was curious about something very, very practical, which was, well, are there efficient ways of selecting the best candidates for different positions, academic, creative, managerial?

[87] And the answer to that is, Well, yes, and they're very well documented, and they're relatively objective.

[88] And so I started looking at the data on objective testing, personality and also cognitive, let's say.

[89] There are other, you can measure interest, you can measure creative ability.

[90] There are other objective ways of getting at this.

[91] And then I looked at the history of objective testing, and I learned that it was the socialists that brought IQ tests to the UK.

[92] and then they spread from there into the rest of the Western world and the reason for that, and the Army did this as well.

[93] The reason for that was that the hypothesis was that if you used objective tests, that you could identify people of disadvantaged economic background who had the ability to succeed academically and professionally and that would be good for them and fair, but it would also be good for everyone else because why the hell not draw on the full talent pool if you're trying to move people along the educational ladder up the educational ladder.

[94] And so my conclusion from all this, and this was before all this became politicized, was that there was absolutely no better way of serving disadvantaged communities than to stick 100 % to objective tests, not because they didn't produce differential outcomes because they still do, but because any other system you could possibly produce would produce much worse outcomes.

[95] And then I read Adrian Woldridge as well, and Adrian, who did it, he said he was an economist journalist for years, a very, very careful historical researcher.

[96] He showed very clearly, as far as I'm concerned, that the alternatives, the historical alternatives to objective testing have been dynasty and nepotism, not equality of outcome.

[97] So the thing about objective tests to me is, well, first of all, they actually predict they're reliable and valid.

[98] They're better than any other method by a large margin.

[99] And, and this is the crucial and, there's no way that you can do better than that.

[100] Everything else you do will be worse.

[101] Okay, so now we have this mishmash at universities that you just pointed out.

[102] If you're a child of a faculty member, you get preferential access.

[103] That's usually a hiring perk for the faculty members and a major one.

[104] Right.

[105] And it keeps them at private schools because the state school can't do that, but the private elite schools can do that.

[106] Right, right.

[107] So you can see what the rationale is there.

[108] And then children of donors, well, you can also understand the rationale there.

[109] But basically what that means is that rich people can buy preferential access.

[110] Now, you could argue that that's acceptable if one of the things that the rich people are doing is donating like $100 million to establish an entire new research complex.

[111] You could say, well, perhaps that's a price worth paying.

[112] It's not fair at the admissions level.

[113] And then, well, the next one is athletics.

[114] And, you know, I I worked for the U .S. Naval Academy for a while.

[115] That's a whole story in and of itself.

[116] And I found there, and this was quite shocking to me, as again, as an ignorant Canadian, that they had a walloping preference for athletic ability at the Naval Academy.

[117] And that struck me as pretty damn counterproductive given what they were training these people to do.

[118] And then you also mentioned racial preference.

[119] And so there's a variety of ways that these admission systems get gerrymandered.

[120] do you see a solution that's even possible, you know, holistic?

[121] I think that's just complete bloody rubbish.

[122] That's just hidden prejudice and discrimination.

[123] Do you see an alternative to the catastrophe of objective evaluation?

[124] Because it's also a catastrophe.

[125] Well, there's a clear alternative, but it won't be pursued.

[126] You know, basically every other system has test -based admissions.

[127] And I think the key to pushing on forward more for test -based admissions, is exactly what you said.

[128] We think about the tests as favoring the rich.

[129] But the other stuff favors the rich even more.

[130] Well, right.

[131] That's exactly it.

[132] You see, athletics.

[133] You know, Harvard actually offers more varsity sports than any school in the country.

[134] You know, when we think about sports as being an equalizer, you're thinking about football and basketball.

[135] When we're talking about sailing, that's an entirely different matter.

[136] So if you get rid of racial, of athletic preferences, white.

[137] go down, African -Americans stay the same, and Asian -Americans' Hispanics go up.

[138] I'm sure that if you took football and basketball out of that, it'd be only whites who are going down.

[139] And that fits in, you know, because Harvard also has an athletic rating as part of their admissions criteria beyond just the athletic preference.

[140] So everybody gets an athletic rating.

[141] And the people who do the best on Harvard's athletic rating are white legacies.

[142] then legacies of other races than white non -legacies.

[143] You know, how does that work?

[144] One, it's the sports that Harvard offers, like sailing and such.

[145] But sports actually favors people who go to small private schools.

[146] So I went to suburban public school.

[147] No way could I make the soccer team.

[148] My kids, they made the soccer team at their school because they don't cut anybody.

[149] You know, those types of things are all work to favor.

[150] people of needs.

[151] Yeah, well, this is the thing.

[152] That's why I want to reiterate that for people who are watching and listening.

[153] Like, if you use an objective selection system that's based on merit, so let's define merit first.

[154] You tell me if you think I've got this wrong.

[155] So here's the definition of merit.

[156] All right.

[157] So in principle, the enterprise you're pursuing has an outcome.

[158] So at university, the outcome would be grades and graduation.

[159] If you go to work, the outcome would be job performance, and that can be evaluated a variety of ways.

[160] If you're an entrepreneur, it would be success at business.

[161] And so that's the outcome.

[162] Now, merit in relationship to that outcome would be the documented relationship between a trait that you might have and that outcome.

[163] And so one of the things you see on the academic front is that one of the biggest predictors of academic success is general cognitive ability.

[164] And the reason for that is, in part, because there's actually no difference between general cognitive ability and academic success, right?

[165] They're the same thing.

[166] Now, it turns out you can measure general cognitive ability with incredible rapidity, very accurately.

[167] And they are the most accurate tests ever designed by social scientists.

[168] They're much more powerful than almost every medical test that we use.

[169] And they're very predictive, not only of academic performance, as evidenced by grades, but also then long -term.

[170] term life performance, and they're even more predictive of speed of learning.

[171] And again, that's because general cognitive ability and speed of learning are the same thing.

[172] So, you know, there is a debate about our society whether or not merit is in itself a, let's say, a racist and prejudicial construction.

[173] But that's an idiot presumption because that's the same statement as what any enterprise is for is not relevant.

[174] And that's completely preposterous because an enterprise exists because it's for whatever it does.

[175] That's its justification.

[176] So you can't get anywhere by claiming there's no such thing as merit.

[177] And you actually can't get anywhere by claiming we can't measure merit because if you accept that, that means we'd have to throw out all of medicine and the social sciences because we can actually measure merit better than we can measure anything else.

[178] And then you add to that, if you don't measure merit, whatever you measure is going to disadvantage the disadvantaged people even more.

[179] And that's the crucial issue as far as I'm concerned.

[180] because it will revert to these invisible forms of prejudice that are always associated with nepotism and dynasty.

[181] So do you think I have any of that wrong?

[182] So I'm in total agreement with you.

[183] I think the point of contention that the universities would say is that their objective function is different.

[184] They want to create the future leaders of society, and maybe that connects all with the cognitive ability, but they're so vague about what the objective function is, that actually getting, pinning them down on that.

[185] and being able to actually measure is tough.

[186] I also know the leadership literature.

[187] Okay, fundamentally it's rubbish.

[188] And the reason for that is that, first of all, there isn't any such thing as leadership.

[189] Like, it's not a unitary phenomenon.

[190] And it's partly because there are different ways of leading people and different circumstances call for different, say, styles of leadership or different abilities.

[191] Now, having said, all that, you can say that in general, people who are highly intelligent, who are conscientious, which means they'll do what they say they'll do, and they stick to the task, and who are somewhat extroverted tend to tilt more towards being approved of leaders because, well, they can figure out how to do things, they'll actually do them, and they can communicate about them enthusiastically.

[192] But if you take that as a base definition of leadership, you're still going to find out that general cognitive ability and conscientiousness predict that, and that is also the same two sets of traits that predict success at universities.

[193] So all that gerrymandering by the universities, that hand -waving about the notion that they can't measure their outcomes, is that that either means they don't know anything about how to measure or that they're just obscuring the situation for their own purposes, whatever they might be.

[194] Well, and that's the thing that drives me most crazy about universities is their unwillingness to use their data.

[195] You know, if you take COVID as a perfect example of this, Notre Dame had a very different COVID policy than the Ivy League schools.

[196] We should know how that worked out.

[197] We should know how the mental health rates were different across those things.

[198] And then so we know how to do it better in the future.

[199] We don't do that.

[200] And, you know, the other thing it's just, I find hilarious, is that a lot of universities have randomized roommates.

[201] That's great for the purposes of studying what the effect of different roommate characteristics have on you and what the match component might look like.

[202] But they don't do that.

[203] They just keep having the randomized roommates.

[204] They don't actually look to see what pairs might actually work and how can we construct policies that might actually help their students.

[205] Well, you know, it's really, it's really sad that universities don't do that because universities spearhead the social sciences research enterprise.

[206] And the fact that they don't capitalize on their own expertise either indicates that the expertise isn't there or that it's untrustworthy or that there are other reasons they don't bother, which is either incompetence or some hidden agenda.

[207] And none of that is excusable.

[208] Oh, it's crazy.

[209] Now, so let's go back to the court case, if you don't mind.

[210] So what magnitude of advantage are we talking about with regards to these different categories?

[211] We have athletics, we have legacy students, we have racial preference.

[212] That was the main three categories apart from children and faculties.

[213] What kind of differential advantage are you looking at, say, on the racial front?

[214] Well, so by far the biggest is the athletic preference.

[215] Oh, that's the biggest one.

[216] Oh, by far.

[217] Yeah.

[218] And part of that you could think is they negotiated ahead of time that they're getting in.

[219] So maybe you don't see the full applicant pool for them.

[220] But the characteristics of admitted athletes.

[221] So, I mean, the athletic admit rate is over 85%.

[222] And the average athletic admit has academic characteristics that are much worse than the average applicant to Harvard.

[223] And the average applicant to Harvard has a very low chance of getting it.

[224] So, you know, we're really talking about massive preferences there.

[225] So could you outline the advantages and disadvantages to the athletic preference?

[226] Because you could say, well, the kids who've been good athletes, they are stellar at something.

[227] So they have a demonstrated track record of, so to speak, track record of accomplishment.

[228] And I think there's something to that.

[229] I think you could infer, although it would be nice to prove, that having developed the ability to be a discipline specialist, a sport might make you a better team player and potentially a better leader.

[230] I don't know of any data pertaining to that.

[231] You might say as well that for a school like Harvard that faces an embarrassment of riches on the applicant front, that using additional criteria of achievement is a useful screening mechanism, why does this athletic preference exist?

[232] Now, you said it favors the rich, too, and that's a very interesting thing to look at.

[233] But why does the athletic selection advantage exist?

[234] And what do you think the pros and cons are?

[235] Well, I think it's a backdoor way in Harvard's case of getting people from rich families.

[236] And I say that primarily because, you know, over 16 % of white admits are recruited athletes.

[237] That's actually way bigger than what you see for African -Americans, Hispanics, or Asian -Americans.

[238] And that's because, you know, they're choosing sports, like sailing, skiing, fencing, all these things that are associated more on the upper end.

[239] But I think you end up with the way, you know, more university governance where you end up with these handouts.

[240] Why isn't it the case?

[241] Why would you have an athletic rating and not a music rating?

[242] You know, it's a very odd thing to me that we have this tie.

[243] So at places like Harvard, they do look at additional forms of attainment.

[244] And you'd know more about this than me. But I used to know the Dean of Admissions at Harvard, and we talked a lot.

[245] And he was a very interesting character.

[246] And, you know, they basically picked kids who were, at that point, that was back in the 90s, they picked kids who generally were stellar academically.

[247] A lot of them were valedictorians or the next best thing.

[248] Then generally, they had to have at least one other relatively, stellar talent.

[249] And that was sometimes athletics, but it could be proficiency in any number of other domains.

[250] But you're saying that the athletic preference far outweighs any of the other criteria that are applied.

[251] That's right, because they don't even have like a field in the data for these other things.

[252] You know, here we have athletic.

[253] You know, we know you get a score for that.

[254] The other things are going to matter.

[255] It might show up through your extracurricular rating or things like that.

[256] But you can see in the court record the conversations that happen between athletic coaches and the admissions in a way that I don't think happens in other areas.

[257] Right.

[258] So athletics is considered separately from extracurricular, and everything else is lumped into that.

[259] That's right.

[260] Right, right.

[261] Yeah, well, you see, that also seems to be very careless, you know, because you'd think if you were going to set up an equation to admit that you do some work in delineating what, other stellar performance features are actually associated with academic success and later, even for your own financial interest, because, I mean, one of the things the Ivy Leagues are trying to do is to pull people in who will become rich enough to become alumni donors.

[262] And they're actually pretty good at that.

[263] And they have the reasons for it.

[264] But you'd think that that would be of sufficient economic interest to actually try to model.

[265] But I think even those athletic preferences, why they had that was not so pure motives as that, but war relating to Jewish discrimination.

[266] You know, I think that's part of why we have the holistic missions in the first place.

[267] Okay, so that's another.

[268] So you think not only the athletics admissions, not only privileged the rich, but they're also a way of tilting the scales against Jewish applicants.

[269] I think that's why they might have, that's right.

[270] And so then we have a, that sort of carries forward to today, you know.

[271] Right.

[272] But it would be the Asians who are more in that position.

[273] now, or is it still Asians and Jews?

[274] The thing is we wouldn't know about Jews today.

[275] And part of that is Harvard actually doesn't download that information.

[276] So on the common application, it actually asks your religion.

[277] Harvard doesn't download that information, in part because of the history of Jewish discrimination.

[278] And I think that's one of the remedies in these cases, is don't download the racial information.

[279] That's not going to totally get rid of discrimination.

[280] They may still discriminate against the Jews based on their last name.

[281] you know, those kinds of things.

[282] But it's not as easy as being able to point to the Jewish box on the application.

[283] Now, on the athletic front again, do you know if, so look, one of the problems at a place like Harvard is that if you let students in who aren't academically prepared, one of two things inevitably happens, three things.

[284] One is, it's not that much fun for the student.

[285] Right.

[286] I mean, I saw when I was at Harvard the consequences of being less intellectually gifted than your peers, right?

[287] And that's not fun.

[288] And especially many of the kids came from places where they were pretty stellar in their local environment.

[289] And then they'd come to a place like Harvard, which is hyper -selected, and they wouldn't be so stellar.

[290] And that was salutary in some ways because it kept ego down, but it was devastating in other ways.

[291] And it's no fun to be selected to a place like Harvard and then to fail.

[292] And if you're not selected on academic grounds, and that would be for general cognitive ability, and you come to a place that's full of people who are hyper -sophisticated cognitively, that's going to be a pretty damn rough go.

[293] And the probability that you're going to fail is quite high and be demoralized, and maybe even end up concluding that you're stupider than you actually are because it's such an artificial competition at a hyper -selected school.

[294] And then the other remedy, of course, is that if you admit people, whose general cognitive ability isn't up to scratch, then you're going to decrease the academic requirements because otherwise everyone who's admitted, who on these somewhat fallacious grounds, let's say, everyone's going to fail, and then it's going to look like your institution is prejudiced.

[295] So do the athletic, do the athletes, how do they do, how do the athletes do in terms of dropout and school success?

[296] So unfortunately, the lawsuit didn't give us outcome data.

[297] But I will say, I don't think dropouts an issue.

[298] I think Harvard always figures out a way to graduate you in ways that might not be true of other universities.

[299] What they graduate you in, you know, you're not going to be getting a computer science degree coming in that way.

[300] Right, right, right.

[301] And that's what's really interesting.

[302] So you'd be slaughtered into one of the disciplines that require a somewhat lesser degree of sheer.

[303] intellectual horsepower.

[304] That's right.

[305] That doesn't build off your previous academic background.

[306] And that's the beauty of this, right?

[307] Because I actually think what's happened over time is that the returns to your college major matter more and more.

[308] And so now you have fields where there's very little demand for the subject.

[309] Having the athletic preferences, those other preferences for the people who would really like to be an econ major, but it's a ton of work.

[310] given their background, then they end up switching into this other field.

[311] Whereas that same person might have been an econ major at a less prestigious school.

[312] They could have cut it there.

[313] Right, right, right.

[314] Well, that's the other thing I think I observed both at Harvard and at the University of Toronto.

[315] Like, if you have a child who could be a star at a state school, but was a third -tier performer at an Ivy League, you're probably better off sending them to the state school.

[316] That was my sense.

[317] Because compared to the general population, they might still be stellar performers.

[318] But if you put them in with people who are hyper -selected, especially when they're young, they're going to draw the erroneous conclusion that they're not particularly talented.

[319] Now, compared to, you know, people who are one in 10 ,000, the person who's one in 100 isn't particularly stellar, but compared to the other 100, they're more than perfectly capable.

[320] So I would say to parents, I don't know what you think about this.

[321] I would say to parents, you know, you should put your kid in a place where they're going to be challenged, but where they're not at the bottom of the pool.

[322] That's right.

[323] And I think that that's more relevant in some majors than others.

[324] So the bottom of the pool, I think, is sort of all relative to the sorting that happens within college.

[325] And there's massive sorting.

[326] Tons of people come in wanting to major in the sciences and such, and then they switch out.

[327] And it's very predictable who switches out.

[328] Those who are relatively lower on the mass side tend to switch.

[329] Yeah, yeah, yeah.

[330] Well, that, okay, so from what I've been able to derive, that's particularly true.

[331] It's like, I think the, the discipline where general cognitive ability horsepower is most necessary is physics and mathematics.

[332] That makes sense.

[333] And then they got, then there's a hierarchy down from that.

[334] And so, now, I guess you could also make the case is that, well, it's not so bad that in universities, there's a range of disciplines to match different levels of general cognitive ability.

[335] But I would still say that at elite schools, that have all those resources, that their resources are best funneled towards those who are most able to benefit from them.

[336] And that's clearly the people who have general, higher general cognitive ability.

[337] And sort of related to that, what also bothers me is they're not honest with their students.

[338] You know, so if you told somebody up front, yes, we're admitting you, giving your initial major interest in your test scores and grades, here's the probability you're going to complete this degree, here's the probability you're going to complete some other degree.

[339] Here's probably you drop out.

[340] Now at least you've given them full information.

[341] You know, to me it takes away a lot of the mismatch argument because individuals can make up their own mind at that point say, well, I'd rather go to Harvard and graduate in some non -science field than go to UNC and graduate in physics if that's sort of the way the trade -off works.

[342] Yeah, well, you could argue that, you know, there's going to be kids that you don't think will do very well on the basis of your testing, who will go there and actually do quite well.

[343] And so it would be okay not to inform them because that way those exceptions can flourish.

[344] But I've thought this through, and this is my conclusion, and you can tell me what you think about this, which is that, yeah, but for every kid like that, you're going to doom like eight kids to failure.

[345] And it seems like an inefficient use of that kid's time and the school's resources to have a failure rate that high.

[346] to have the odd exception.

[347] I mean, and I see this if you're recruiting people for a management position, too.

[348] You might say, well, why not give this person a chance?

[349] You know, maybe they'll succeed.

[350] And the answer is, well, yeah, but probably they won't.

[351] And that's going to be really hard on them.

[352] And not only that, if they turn out not to be able to do the job, it's going to be really hard on everyone that they're supervising and working with.

[353] And setting someone up for failure from compassion, is not advisable as a management strategy.

[354] It's a bad idea.

[355] It's not advisable as an admission strategy as well.

[356] I totally agree.

[357] But I also like being able to tell people, look, it doesn't look like you can cut it because some of the people then can respond by working hard.

[358] For myself, I was a guy who just floated through thinking I had it all together.

[359] Then I got to graduate school and learned humility and learned I had to work a lot harder.

[360] But having somebody tell me, you know, you're not good enough.

[361] For myself, that was actually a push.

[362] You know, I wasn't internally motivated enough.

[363] I needed somebody to prove wrong in order to do well.

[364] Now, I know I'm sort of weird in that way.

[365] Well, yeah, but not, but not like not absurdly weird in that way.

[366] I mean, you see lots of smart kids who have floated by who hit a wall where they're now competing with kids who are just as smart, but like 10 times as disciplined.

[367] And some of them fail and they're bitter as a consequence.

[368] But some of them like pull up their socks and think, oh, my God, looks like I'm actually going to have to work.

[369] And there's nothing about that that isn't good for them, right?

[370] Because then not only, then they're more like Asians, right?

[371] Because the Asian advantage, I looked into the Asian advantage a lot.

[372] and the Asian advantage.

[373] By the way, the Asian performance advantage in the U .S. disappears by the third generation.

[374] So it turns out the more that Asian kids are like American kids, the less they're like Asians, so to speak.

[375] And Asians have this hyper focus, like Jews, I would say, they have this hyper focus on academic success and academic success as a status marker at home and in the community.

[376] And, and, you know, That's actually, I think, something that in principle might be remediable because it implies that if you can teach people at any given cognitive level to work harder, that is one pathway to genuine success.

[377] But it's also appalling that the Asians get discriminated against because, you know, the ones who are being discriminated against, they're hard workers.

[378] And that's not a good thing to discriminate against.

[379] Being an American, I wanted my kid to do sports.

[380] You know, that was just part of the thing.

[381] And he was uninterested in sports.

[382] And he kept telling me that.

[383] And he kept putting him out there in soccer, basketball, whatever.

[384] And he kept saying, I want to do karate.

[385] Eventually did karate, it was fine.

[386] The kid was just different in that regard.

[387] If he'd been in a society where the norm was to do something else, to do science, I think, you know, that would have been very nice for him socially and so on.

[388] Lender stays in a place like Hungary, they're much more centered.

[389] on math, in America are much more centered on sports.

[390] That sports craze, I think, is actually, you know, it does build some good skills, but I think it's, we're too obsessed, obsessed with it to the detriment of these other things.

[391] And I think Asian American families have sort of figured out not to be obsessed about that, but to be obsessed about other things.

[392] Right, which is another reason why it would be nice to see the equations adjusted so that other forms of excellence, extracurricular excellence, are given their due weight.

[393] Right.

[394] And so why were you called upon to testify specifically?

[395] So I've written a lot of papers on affirmative action and with mixed results.

[396] So I think that there's actually a lot of pressure to say good things about affirmative action.

[397] And I didn't always say good things.

[398] And in fact, in 2011, there was a protest over one of my papers.

[399] It was sort of a very innocuous paper.

[400] We actually used Duke data, and we're looking at persistence in science and economics.

[401] And what you could see is that African -American students came in wanting to major in those subjects at the same rates as white students, but they were leaving at a much higher rate.

[402] So like over 50 % of black males who started in the science, and economics switched out versus 8 % of white males.

[403] Once you control...

[404] Well, the advocates of systemic racism as an explanatory hypothesis would say that the racism is so deep that not only does it discriminate on the admission side, but it also discriminates on the performance side.

[405] And all those things disappeared as soon as you control for academic backgrounds.

[406] You know, you can control, for the test scores, you know, other Duke ratings and such, you start off with these big racial gaps where Asian Americans were most likely to persist in the sciences and African Americans were least likely.

[407] Once you conditioned on differences in academic backgrounds, driven both by affirmative action and what, you know, the educational experiences prior to college, that just disappears.

[408] And I think that's what they didn't like.

[409] Did you control for grades or for SAT scores or for both.

[410] Do you remember?

[411] Controlled for a whole different specifications at different controls, but it goes away fairly quickly.

[412] And you could look at and suggest performance in first year classes and look at the...

[413] And that wipes it.

[414] Right.

[415] So for everybody who's watching and listening, tell me if I get this wrong.

[416] So you could imagine that if you're doing a statistical analysis, you could determine whether race was the predictor or academic ability was the predictor by modeling both of them and seeing which predicted dropout better.

[417] And if it's, if academic ability destroys the ability of race to predict drop out but not the reverse, then you know it's academic ability and not race.

[418] And in principle, unless you assume that the academic ability markers are also contaminated with, what would you call it, systemic racism, then you eradicate the racist argument.

[419] So what the radicals do is they just say everything, systemic racism, and it's virtually impossible to mount an argument against that.

[420] But then we have the other problem, which for all of you who are compassionate, who are listening, you know, it's not compassionate to put people into situations where they disproportionately fail, right?

[421] It allows you to look good on the admission front, but it's not good for the people who are involved, as far as I can tell.

[422] Do you think there's anything about it that's good for the people that are involved?

[423] I think it's tough.

[424] You know, we could actually say more because they asked the reason why you switched your major.

[425] And one of them was the difficulty of the courses or feeling not as prepared for those courses.

[426] And again, you could see that black students were much more likely to say it was because of course difficulty.

[427] and once you controlled for the SAT scores and such, that all went away.

[428] So it really pointed towards these academic measures really mattering for your experience in those classes.

[429] Now, on that systemic racism front, saying, well, look, the test scores are biased.

[430] To me, I think that there's such a disservice because then it sort of says what's happening to prior to college, like in the K through 12, education, it's really not that bad because the test scores are just misrepresenting it.

[431] You know, when reality, the fact that, you know, one percent of black students score above 1390 in the SAT, that's 8 percent for whites and 24 percent for Asian Americans, that's reflecting something that we could fix.

[432] That's where we need to spend our time on, is fixing that.

[433] Okay, so let me make a case for the universities and what they're doing.

[434] So what would rapidly happen if we went to a purely objective evaluation system is that at elite level universities, there would be a disproportionate compared to the population.

[435] There would be a radically disproportionate number of Asians and Jews and a radically disproportionate dearth of black Americans.

[436] That would happen very rapidly.

[437] And the universities are concerned about that.

[438] And now, and it's definitely a very difficult nut to crack.

[439] Right.

[440] And so now it doesn't seem like the appropriate solution to that is to disadvantage.

[441] extremely competent Asians.

[442] And I would say partly because, well, they deserve their shot at the target.

[443] But also, you know, there aren't that many hyper -exceptional people on the cognitive front, right?

[444] And if we're greedy as a society and sensible in that greed, we would say we should set up our institutions to capitalize on every available bit of brain power and persistence.

[445] So it's better socially if we can put the smartest people where they have the greatest opportunities to learn and contribute.

[446] So we're not just hurting the Asians, let's say, and the Jews.

[447] We're also depriving ourselves in principle of what they could offer.

[448] But then we're going to have the problem of this disproportionate racial and ethnic mix in the universities.

[449] And so what, and maybe this isn't a fair question to ask you, because it isn't necessary that you have the solution to this.

[450] It isn't obvious to me that anyone has.

[451] But you were testifying on behalf of, you were making a case that the affirmative action systems as presently constituted are very badly flawed and probably illegally flawed.

[452] But what do you see forward, if anything, as a way out of this conundrum?

[453] So, you know, really I view that I wasn't actually saying it was flawed, someone just saying how big the preferences are.

[454] I hate actually being characterized as an opponent of affirmative action because then it makes it seem like the research is biased.

[455] I'm just trying to show you what the data show.

[456] To me, I think it allows, affirmative action works as a Band -Aid where it covers up all the inequities that are happening prior to college.

[457] And then we don't focus on those things.

[458] Roland Fryer, I think, has done a lot of work on the no -excuse charter schools showing that those are actually pretty effective at closing those achievement gaps.

[459] I think the work sort of shows it doesn't translate as well into college, but it's a start.

[460] Unfortunately, they ran him out of town.

[461] But, you know, he was the most prominent black economists there came from nothing and what I think has happened to him is absolutely horrible.

[462] And he's one of the few actually shows how to close the achievement gap.

[463] Right?

[464] And that was Roland.

[465] Roland.

[466] Roland Friar.

[467] Oh, right.

[468] Yes.

[469] Yes.

[470] Yes.

[471] I've been seriously considering him on, inviting him onto the podcast to discuss precisely.

[472] Oh, he is absolutely amazing.

[473] His story's amazing.

[474] And what's happened to him is criminal.

[475] It's shocking.

[476] It's terrible.

[477] Yeah.

[478] Well, so this issue here, I think you touched on something very crucial, which is that, right, if we pretend that the achievement tests are the problem, that in, enables us to ignore the underlying problems.

[479] Of course, that gets muddy and ugly very quickly, too, because one of the things I would say, perhaps, as I've studied the development of antisocial personality, for example, and other forms of psychopathology that would interfere with educational attainment and lifetime attainment over the long run.

[480] And it's certainly the case, for example, that fatherlessness is a contributing factor in a major way, right, destabilized families.

[481] And so if you don't allow the achievement tests to be the villain, you have to look elsewhere for the villains, and that becomes extraordinarily complex and murky and troublesome.

[482] You know, we tried to prevent antisocial behavior, for example, in Quebec.

[483] And what we learned was that if children are antisocial by the age of four, most of those kids would have been aggressive at the age of two.

[484] most aggressive kids are socialized out of their aggression by the age of four.

[485] If they're not socialized out of their aggression by the age of four, it doesn't look like there's a damn thing you can do about it afterwards, or it's extraordinarily difficult at least.

[486] And so that would mean you have to remediate it at the age of two.

[487] But then if you start producing government programs, let's say, to remediate antisocial behavior before the age of two, you're in people's households, right?

[488] It gets very invasive, right?

[489] So some of these underlying systemic problems, let's say, are extraordinarily difficult to address without falling into a kind of colonial, neo -colonial overreach.

[490] That's one way of thinking about it.

[491] And they're very persistent.

[492] It's such a shame.

[493] Because, you know, as soon as you would propose something like that, you'd be accused of victim blaming.

[494] You know, but the reality is there's been some great work done in other countries where you go into a place like India and they're talking to the mother there, and the mother's like, so I should be talking to my child?

[495] Like, that wasn't passed on to them, that they should be talking to their child regularly.

[496] That's not judging you that you didn't get that information passed on.

[497] We're saying, how do we fix this problem?

[498] Well, I've also been interested in precursors to literacy.

[499] You know, and if you look at the data, you find that kids from literate homes are exposed to books and a wider range of vocabulary at a differential rate that's staggering by the time the kid is like two and a half.

[500] You know, and it is the case that most poor families, if you interview poor mothers and fathers and you ask them what they want for their children and you put educational achievement into the mix, they will indicate in a fully committed manner that they would like their children to be educated.

[501] But the problem is, is they don't know what the...

[502] say the non -verbal precursors are.

[503] You know, I had friends where I grew up.

[504] I grew up in this little place and way the hell out in the middle of the sticks.

[505] There were no books in the house, like zero.

[506] Right.

[507] And that's way different than growing up in an environment where, like, my kids' children at 18 months old, they're already dragging books around behind them and sitting down and pretending to read them.

[508] They have all that literacy, pre -literate literacy skills are already built in.

[509] they value books.

[510] They know what they are.

[511] They've made friends with them.

[512] They'll ask their parents to read them books.

[513] And, you know, in a family that's very deprived and very poor without a history of literacy, nobody in the family even knows that that's a possibility.

[514] That's right.

[515] And it's such a shame because I think there's now a way of packaging that.

[516] Because what you've revealed is, you know, the parents love the kids.

[517] They love them.

[518] They want to do right by them.

[519] But they're either under -resourced or don't know what those steps are, how do you, if it's presented more that way, maybe we'd get around the victim -blaming into something where you could actually help them.

[520] I worry about that because actually I think one of the, you know, I used to be, think that affirmative action for doctors, that seems like the worst idea of place to have affirmative action.

[521] But there is actually an argument for it in that if you look at whether black patients will follow the instructions given to them by a white doctor versus a black doctor, they're more likely to actually follow the instructions of a black doctor.

[522] So that actually makes the case.

[523] There's two ways to fix that problem.

[524] One would be to somehow rebuild the trust so that when the white doctor gives a script, they find it credible.

[525] Or the short run fix is to get more black doctors so that you have people following the scripts.

[526] somehow that trust needs to be restored so we don't have this, well, we're the white saviors coming in and telling you how to parent your child?

[527] Right.

[528] Well, right, right.

[529] Well, you know, I also looked at the Head Start literature for a long time because that was, Head Start's a very interesting program for those of you who are watching and listening.

[530] It was part of the American War on poverty that started in the early 1960s.

[531] And it was actually a program that was optimistically viewed by conservatives and liberals alike, right?

[532] And because, first of all, you know, who likes poverty?

[533] And the answer is nobody.

[534] So everybody's against poverty that has even an iota of sense.

[535] And so the liberals were happy because there were steps being taken to remediate poverty hypothetically at its source.

[536] And the conservatives were happy because, well, wouldn't it be better if, you know, poor young people were educated?

[537] so they could pick themselves up by their bootstraps and, you know, make their way in the world.

[538] And so everyone was hoping that Head Start would be a success.

[539] And fundamentally, it wasn't.

[540] So, and here's how it wasn't.

[541] The goal was, the theory was that if you got to kids early before school and you gave them an academic boost, that that would not only catch them up to their peers, but it would give them the kind of permanent advantage that would grow across time, right?

[542] because now you're prepared to go to school, you can do better in school, and the advantages with just accrue.

[543] And that was a pretty good theory.

[544] But it turned out not to be true, because what happened, and this has been studied to death, and there's no doubt about this, and people of every political stripe analyze the data, is that the Head Start kids actually did do better in grade one and two and three.

[545] Their grades were higher, they were more likely to attend school, and so on, but all the other kids caught up to them by grade six.

[546] So the cognitive advantage didn't accrue and it didn't multiply.

[547] In fact, it disappeared.

[548] And now, what Head Start did do was more kids graduated who were Head Start alumni and fewer got pregnant in the teenage years and there were fewer criminals in the Head Start groups.

[549] And the reason for that apparently was that some children's environments were so toxic that just taking them out of those environments for some, period of time, allowed them to be more socialized, and because they behaved better, they had better outcomes, but there was no effect whatsoever on cognitive performance.

[550] And that's very disenchanting, because that was a major league program, and people put a lot of time and effort to it.

[551] And there were every reason to hope that there would be some gains on the cognitive ability front that were permanent, but that didn't happen.

[552] So I thought the kids who went to, the Head Start kids who went to better schools, you did see it continue.

[553] But Maybe I'm misremembering, misremembering.

[554] I don't know.

[555] But the kids who went to the bad schools, sort of continued to be, like, you couldn't just stop the investment there.

[556] If they kept going on that track, but I'm not an expert in that literature.

[557] I'm sure you know it much better than me. Well, no, not necessarily.

[558] I don't know if I knew the differentiation at grade six between the kids who, you know, went to better schools and the kids who went to worse schools.

[559] What I did know was that overall, the cognitive advantages that had been accrued, disappeared.

[560] It didn't have, it didn't seem to have a permanent effect on IQ, for example, which was really disheartening, right?

[561] Because now I looked into it even more detail.

[562] Part of the issue was, you know, Head Start was also used as an employment program.

[563] And so it wasn't necessarily obvious that the kids were actually learning anything at Head Start.

[564] They might have been being taken care of reasonably well.

[565] And it's also very difficult to take a group of three or three.

[566] and teach them anything in an hour and a half because they're three.

[567] And, you know, you have to give them juice and you have to give them food and you have to stop them from tearing each other into bits and like, and then you have to be trained enough to actually educate them.

[568] And so it isn't obvious that Head Start was set up optimally as a cognitive retraining program.

[569] But but then it's very expensive to set up an optimal cognitive retraining program.

[570] So that's also a major league problem.

[571] So let's go back to the judgment.

[572] So what exactly did the Supreme Court determine and what have the reactions of the universities been and what are the consequences of the decision?

[573] So, you know, the Supreme Court, I mean, there was some sense of vindication because I really felt like the lower court rulings abused the statistical evidence.

[574] Now, I think the statistics played a role in all this, but, you know, there are other aspects besides just the statistical side.

[575] I think it's very clear, you know, that Harvard kept harping on me over and over again about the idea that, well, we only use race to help you, not to hurt you.

[576] But it's a zero -sum game.

[577] So, you know, a penalty for one group is equivalent to a bump for the other group.

[578] You know, we could always write it, write it that way.

[579] And, you know, I think Roberts sort of summed up the decision well by saying the solution to eliminating discriminations to eliminate all of it.

[580] You know, so you're not supposed to use race directly in admissions.

[581] Now, they left this bit of a loophole in terms of being able to talk about your experiences of precious and such.

[582] And, you know, I think that could be a good.

[583] good thing, but if it just gets abused the way I expect that it might.

[584] Yeah, it will.

[585] Then we've got a problem.

[586] My hope.

[587] Okay, so they eradicated, so they said straightforwardly that you are not to use race as a determining factor.

[588] That's right.

[589] That's right.

[590] Race can enter in only through your experiences.

[591] What that means for what college admissions places actually do is going to be interesting.

[592] I mean, I think what California did, you know, we had Prop 16.

[593] Prop 16 tried to put racial preferences back in place.

[594] It got voted down in California by wide margins, despite Trump being on the ballot.

[595] And the reaction of the UC system was we're going to no longer require the SAT because we want to figure out a way, you know, I think that, the idea of a university throwing away data, data seems just...

[596] Especially the SAT.

[597] It's just...

[598] It's not...

[599] It's just beyond comprehension.

[600] It's to take...

[601] The SAT for all of its flaws is a pretty damn good test of general cognitive ability.

[602] And that's a great predictor of the potential for academic success.

[603] And it's also an equalizer across schools, which is crucial, right, when you're trying to contrast rich kids from great schools with poor kids from dismal schools.

[604] You know, at least the poor kids from the Dismal School with a great SAT can get into university and likely succeed.

[605] You throw that out, man. What are you left with?

[606] I don't know how they...

[607] I don't know how they...

[608] Yeah, I don't know how the UC admissions could possibly make decisions.

[609] Like, if you're going to use the high school grades, grades are all relative to whatever high school...

[610] Yeah, right.

[611] You know, you're attending.

[612] This is, again, where if you use the data, you could actually show and build that trust with the data.

[613] So, you know, if the SAT is biased in favor of the rich and it's over -predicting the performance of the rich, then we could correct that, you know, but you show exactly how it affects it.

[614] Well, we could point this out with the SAT, too.

[615] So this has been done on the racial front, because if the SAT was prejudiced against black test takers, it would underpredict their performance.

[616] And it doesn't.

[617] It doesn't.

[618] Right.

[619] And that's a killer statistic, right?

[620] I mean, it's quite the shock because now you could say the only way to get around that on the systemic racism front is to say, as we alluded to earlier, that the performance criteria are just as prejudiced as the admission criteria.

[621] But they would have to be exactly as prejudice, which seems, right, right, right, right, right, which seems, you know, extraordinarily, extraordinarily unlikely.

[622] And you just roll it forward to the next stage every time.

[623] to say, well, then the next place is exactly the same level of racism as a previous state.

[624] You know, it's crazy.

[625] Well, I've, you know, the conclusion I came to, and this was a painful conclusion in some ways, it wasn't necessarily in accord with my moral sentiments, let's say, is that we simply can't do better than actual race and ethnicity -blind, objective tests of predictive merit.

[626] And those should be established, those should be applied uniformly.

[627] and because that's the best solution, even though it still has its flaws.

[628] Now, I still have no idea what the consequence of that would be given that the elite schools would rapidly fill up with Asians.

[629] Maybe the consequence would be that the other relatively underperforming ethnic groups, including whites, would pull up their socks.

[630] You know, that's a possibility and say, well, those people are obviously doing something that we're doing right that we're not doing.

[631] That was my reaction.

[632] And I was looking at the numbers thinking, I want to know what they're doing, you know, because it's, it's incredible.

[633] Yeah, right, right.

[634] There's a lesson to be learned there in principle.

[635] Knowing what those best practices are would be incredibly helpful.

[636] And I don't, I don't have a good sense of it.

[637] Yeah.

[638] So what has been the consequence for you of being involved in this line of research?

[639] You said there were protests about your work in 2011.

[640] I guess you were lucky it was 2011 and not 2016, because it didn't take you out and might have later.

[641] So what has been people wondering how I survived, you know?

[642] Yeah, well, I'm curious about that, exactly.

[643] Yeah, yeah.

[644] And, you know, that whole experience really prepared me to take the case.

[645] It was actually one of the most spiritual moments, you know, in my life.

[646] Because when people are protesting, you know, it just made me realize how much I care what other people think about me. You know, somebody writes an article from some satellite state school and an Ethnic Studies Department in the state of Washington calling me a racist.

[647] That really hurt at the time.

[648] Yeah, yeah.

[649] It's really hard on people.

[650] You bet.

[651] And so it was, you know, a week or two of, like, no sleep.

[652] And then I woke up one morning.

[653] I viewed it by grace was free and felt like I was able to love the people who were coming after me and saying, okay, you know, I think they're misinterpreing what I'm saying.

[654] I'm going to give them the benefit of the doubt and explain what I actually mean.

[655] And I think that that, I don't know whether that's been what's, I'm sure the horrible stuff could still happen to me. But, you know, if somebody gives, I can take a punch and respond in love.

[656] And I feel like that might be seen as wimping out, but I don't feel like that might be seen as wimping out.

[657] like I'm compromising on the truth.

[658] You know, I'll try to go as far as I can to meet them where they're at without compromising on what I know, what I know to be true.

[659] And I think it makes a difference, you know, I do, you know, I try to treat people well in my interpersonal relationships.

[660] Right, right, right, right.

[661] And that...

[662] So you're not, you're not adding being generally dislikable to the raft of sins that might be utilized, let's say, to take you down.

[663] So far.

[664] That's right.

[665] So far.

[666] Yes, so far.

[667] Right.

[668] No kidding.

[669] No kidding.

[670] But I've been amazed.

[671] Maybe this podcast will change all this, but I've gotten zero hate mail since the Supreme Court decision.

[672] Okay.

[673] So you made reference earlier to the fact that this Supreme Court decision overturned a number of lower court decisions.

[674] And it's also the case that so obviously the lower courts were persuaded by evidence that wasn't the same.

[675] that as the evidence you were bringing forward.

[676] And it's also the case that at the Supreme Court itself, there are other experts with a pedigree as credible as yours, let's say, who don't agree about the interpretation of the data.

[677] So if you had to make a case against what you were offering as a witness, how would you make the case and how did the people who were brought in as experts make the case?

[678] And what were they claiming?

[679] So actually, I would say they have a much higher pedigree than I do.

[680] David Card was one of them.

[681] And soon after the case, he actually won a Nobel Prize.

[682] He was the one of the Harvard case.

[683] And Carolyn Hoxby at Stanford was my counterpart in the UNC case.

[684] Well, it was interesting to say, I had the benefit of working on both cases so I could be reasonably consistent across the two.

[685] they actually attacked me from other sides.

[686] So Card's opinion was that I needed to control for more things.

[687] And in particular, the personal rating was an example.

[688] And I actually estimated models of the personal rating showing the Asian bias.

[689] But the way he would argue it would be we need to take sort of hard resort for it, that this is not a biased measure.

[690] So that was one aspect to it.

[691] The other aspect to it is...

[692] Right, but you showed it was a biased measure.

[693] So I don't understand his claim exactly.

[694] So your claim, if I get it right, is that the prejudice against Asians, so to speak, was making itself manifest as invisible variables within the so -called personal or personality rating.

[695] Now, there are objective ways of measuring personality, which we could also point out, which are quite valid, right?

[696] So Harvard could take that route, and they don't.

[697] They do a subjective evaluation, but your point was that, well, that was hiding a substantive anti -Asian bias.

[698] So how did your opponents muster an argument against that?

[699] So it's very convoluted how you do that, because you don't actually look at a model of the personal rating.

[700] Any model of personal rating shows that Asian Americans suggest as well, sorry, on the observables associated with the personal rating, Asian Americans have observables that are just as strong as whites or stronger, and yet get worse personal ratings.

[701] Often with discrimination things, you're worried that, oh, every time I add a variable, the discrimination goes down.

[702] What if I keep adding variables, it may go away?

[703] That's the amazing thing about this case, is with Asian Americans, you put in more variables, it often goes up, you know, the discrimination, because they're stronger on those measures.

[704] So in order to get there, it's pretty convoluted.

[705] The first thing you have to do is take those special groups, the athletes, the legacies, the children, and you have to say that the discrimination has to be happening against Asian applicants that are there as well.

[706] And actually, that turns out not to be the case.

[707] So 98 % of Asian American applicants, are not athletes, legacies, children, and donors.

[708] The 2 % that are, they're not being discriminated against.

[709] There's not evidence of that.

[710] I think that makes perfect sense.

[711] Okay, so it's not precisely Asian discrimination or if it is, it's not pervasive enough to cut across all categories.

[712] That's right.

[713] And I would say the same thing on affirmative action.

[714] So Zion Williamson was an amazing Duke basketball player.

[715] He didn't benefit from racial affirmative action.

[716] He benefited because he was an amazing dude basketball player.

[717] You know, when you're talking about those things, that's just not relevant.

[718] You know, for a long time, they would talk about discrimination against black quarterbacks.

[719] We shouldn't be able to say, we're not discriminating against linemen, so therefore we're not discriminating against black quarterbacks.

[720] That doesn't make any sense.

[721] So he basically said, no, all you can say is that the discrimination is universally pervasive.

[722] You could say that some forms of discrimination will trump others.

[723] That's right.

[724] We discriminate against the Asian Americans who don't have those connections to Harvard through the legacy and the recruited athlete process.

[725] So that was sort of how that case sort of worked.

[726] And much of the focus in the Harvard trial was all about the Asian American discrimination.

[727] I actually don't think David Cardin, and I had very different things to say about the racial preferences.

[728] I would say that it quadruples their chance of getting admitted, according to Card's results.

[729] It would triple the chance of being admitted for black applicants.

[730] What was interesting in the UNC case is things operated very differently.

[731] In Harvard, I wrote a report, then Card saw my report and built off of that.

[732] In the UNC case, we wrote simultaneous reports, and then did that two more times.

[733] So our starting places were completely different.

[734] And the other expert basically took the position that we can't really model Harvard's UNC's admissions because it's holistic, you know, and that model sort of of admissions failed to predict the decisions well.

[735] Now, I think that the criteria that she used to evaluate that was nonsensical, and that if we started with me writing the first report, we wouldn't have got to that position.

[736] But in this case, you can just keep doubling down, doubling down.

[737] I mean, as an example, you know, her criteria was based on what's called the pseudo -R -squared.

[738] These are non -linear models.

[739] So in R -squared, in a linear model, sort of tells you how much of the variation the data is explained.

[740] When you have a pseudo -R -squared, it doesn't really work that way in quite the same way.

[741] So one of the comments that was made was a pseudo -r -squared of 0 .5 means that we get half the admissions decisions correct.

[742] Well, that, of course, is nonsense, right?

[743] Because by flipping a coin, I could get half the decisions.

[744] Right, right, right.

[745] Right.

[746] Correct.

[747] You really need to be looking at accuracy.

[748] And if you look at accuracy, you know, the models would predict the correct decision over 90 % of the time.

[749] So it's a, it was a very funny experience.

[750] In the UNC case, they basically thought I didn't control for enough things.

[751] Sorry, that I controlled for too many things.

[752] In the Harvard case, they said I didn't control for enough things.

[753] It wasn't coherent.

[754] Okay, so why do you think, okay, so okay, fair enough.

[755] So why do you think that your arguments, so to speak, or the side of the cases that you were testifying on behalf of, why do you think that that carried the day at the Supreme Court level and not in relationship to the lower courts?

[756] And what do you think of, I mean, one of the response patterns, especially from the radical types, is that, well, you know, the Supreme Court is stacked with reprehensible.

[757] sensible conservatives, and of course, that's how they voted.

[758] And that was why the anti -affirmative action, say, pro -merit, that's another way of looking at its side, carried the day.

[759] What's your sense of that?

[760] I think that, you know, I certainly came out of those cases a bit cynical about the role of the statistics here.

[761] You know, both judges at the lower court could have called in a third expert to say, you know, which one of us is right.

[762] But that would have limited their ability to rule how they wanted to rule.

[763] So it's funny how that works, right, where we say, well, it's a conservative court.

[764] They're going to rule however they want to rule.

[765] Based on the statistical evidence, I feel quite strongly that that was what happened at the lower court case.

[766] And then you're left with a really bad record, you know, in terms of what was admitted as evidence.

[767] And do you think, well, do you think your, do you think that your political affiliation, how do you control for the potential consequences of your political affiliation, which I don't know, by the way, how do you control for the potential consequences of your political affiliation or viewpoint on the outcome of the studies that you've been running and the testimony that you provide?

[768] Like, how do you, how do you protect yourself against your own bias?

[769] Well, I'm very cautious on this front, partly because of that protest, you know, so my burden of proof is, you know, I know I can get in big trouble, so I've got to be very careful how I'm going to be talking about these things and set a very high bar for coming to particular conclusions.

[770] I mean, I feel this way sort of in general, like...

[771] Right, the cost is high.

[772] That's right.

[773] So the evidence needs to be much better in that regard.

[774] Yeah, yeah, yeah.

[775] But my intent was always to get peer -reviewed papers out of this.

[776] So I've published five peer -reviewed publications in good economics journals out of the case.

[777] And on Asian -American discrimination, on racial preferences.

[778] I want to elaborate on that for a second, too, because for everyone who's watching and listening, is like the social science domain is overwhelmingly tilted politically towards the left.

[779] That may be less true for economics than it is for psychology, but it's true across the social sciences.

[780] And so what that means is that if you publish a paper with so -called conservative implications in a decent peer -reviewed journal, the probability that it's robust is extremely high because if there are any reasons to thwart its progress forward, those reasons will make themselves manifest.

[781] I think that's right on.

[782] And you could really see it in my view with, you know, I published one paper on legacy and athlete preferences and another paper on Asian American Discrimination.

[783] The same commentator will trash the Asian American Discrimination one and laud the legacy and athlete one, and it's the same model.

[784] Right, right.

[785] Right.

[786] Right.

[787] Right.

[788] Right.

[789] Yeah.

[790] And that was what was actually studying.

[791] Harvard, the evidence against Harvard was so damning.

[792] They had their own internal research team that had estimated models of Harvard's admissions.

[793] And they found a big penalty against Asian Americans.

[794] And Harvard's like, oh, well, we don't know what to do with that.

[795] But in that same model, they found that they were giving a bump to low -income students.

[796] And they knew that that was true.

[797] It's the same model.

[798] You can't interpret it one way when you get the result you like and another way when you get the result you don't like.

[799] You know, it doesn't make any sense.

[800] And if anything, based upon the strength of the applicants, you should disbelieve the low -income result, not the Asian -American result, because all the observable factors are pointing to Asian -Americans being stronger.

[801] They're probably stronger of the unobservable ones as well.

[802] Right, right.

[803] Okay, okay.

[804] So you protect yourself against bias, first of all, just by fear.

[805] Exactly.

[806] Which is actually a good way of...

[807] Well, it's a good issue.

[808] I used to tell my students, look, guys, you don't publish...

[809] unreproducible data, right, to further your career.

[810] Well, why?

[811] Well, do you want to study something that doesn't exist for the rest of your life?

[812] Like, that's stupid.

[813] Don't do that.

[814] And you're going to be motivated to do it because it's hard to admit that a research project was a failure.

[815] You're going to try to scrape something out of it, so you have to be careful.

[816] But then the, and so that's another, you know, use of fear.

[817] It's like, be careful because you'll convince yourself with something that isn't true and waste your life.

[818] That's stupid.

[819] but your situation is, well, if you say anything even vaguely untoward or inaccurate, you're going to get slaughtered for it.

[820] And then that's a fair, that's a fair protection.

[821] And then also, well, if you have to publish these in peer -reviewed journals, you're going to hit the ideological vanguard and have to argue your way through it.

[822] And if you can do that, well, obviously the data has to be so credible that it can't be dismissed by people with an ideological bent.

[823] Okay, so that's good.

[824] So Harvard and the UNC and UNC were hit hard by this ruling, practically.

[825] And I would say morally, too, they got walloped.

[826] How have they reacted and how have other universities reacted?

[827] Well, the public reaction is to send out emails, how disappointed they are, and the Supreme Court decision, how they're going to be to abide it, but our commitment to diversity is unchanged.

[828] So I think that they're going to try to figure out legal ways or illegal ways or they're not going to get caught to somehow put the preferences back in.

[829] Right, right, right.

[830] Well, does that open them up on the liability front now?

[831] I mean, they've been told in no uncertain terms that they can't do this anymore.

[832] It's not, this is pretty black and white.

[833] So it seems to me that if Harvard continues to gerrymander their admissions processes, that they're setting themselves up for a pretty walloping fall.

[834] I don't know what that would mean on the liability front, for example.

[835] I mean, there was a class action suit at one point, right?

[836] Yeah, but it really wasn't about getting damages so much as changing the system.

[837] But I think Harvard would have a very hard time because they just went through a whole trial thing saying that we need to explicitly consider race in order to get these levels of diversity.

[838] if they somehow kept the same levels of diversity now then when they're supposed to not being explicitly considering race then it shows they must be cheating somehow in order to get there so you almost have to see a drop or the whole record in their case was off right right okay okay now how do you think that universities should select in the aftermath of this decision?

[839] Well, I think they should select just based on test scores.

[840] But even within test scores...

[841] Just with objective tests.

[842] Yeah.

[843] I mean, the problem is, is that the SAT for a place like Harvard doesn't test at a high enough level.

[844] We actually need to go.

[845] The tests like to get in the college in Chile are at a much higher level than what we have in the U .S. Right.

[846] So they should refine them and make them more demanding so they can discriminate.

[847] So listen, for everybody, watching and listening, you know, imagine that you get people who score 95th percentile on the SAT and people who score 99th percentile.

[848] And you might think, well, you know, what the hell's the difference?

[849] And the difference is this.

[850] If you score at the 95th percentile, you're the smartest person in a room full of 20 people.

[851] And if you score at the 99th percentile, you're the smartest person in a room full of 100 people.

[852] And then the difference is just as big from 99 to 99 .9 .9, it's one in 100 versus one in a thousand and so forth all the way up the scale.

[853] And there's no indication that I can see in the psychometric literature that that ever stops being relevant.

[854] And so it is important to differentiate at that upper end.

[855] You know, and so, I mean, we've put together models to predict academic performance, and you can predict academic performance quite accurately with general cognitive ability and trait conscientiousness.

[856] and then low neuroticism helps and if you're looking to expand on the creative front, you could look at measures of creative ability and there are good measures and you can look at performance and you can make a formal model where you specify exactly what weight you put on all of those variables and you can easily test that against actual university performance which is what you had recommended earlier.

[857] Yeah, I mean, clearly for math you want to put more weight.

[858] on your math background, maybe less so in English.

[859] That's not taking into account at all.

[860] But I think those tests right now are too easy.

[861] That distinction at that top level could be like, I just made a stupid mistake.

[862] That's too bad.

[863] You really want to test much deeper.

[864] You bet, you bet.

[865] Yeah, okay, okay.

[866] Now, we just outlined how university should select.

[867] This is how businesses should select, too, by the way.

[868] And there's huge economic advantage in doing that, by the way.

[869] Like if you don't have to increase your ability to select top people very much to benefit in a staggering manner from the consequence of that improvement, I tried to convince corporations of this for like 15 years.

[870] I went on the road to sell to corporations, which turned out to be absolutely 100 % impossible.

[871] That's when I first ran into HR departments, by the way, and that was back in, you know, the early 2000s.

[872] But we talked about how the university should select in the aftermath of the decision, the lurking question is how will they i saw uc davis for example at the medical school they're trying to produce an adversity quotient which i think is just an absolutely catastrophically dreadful idea i mean i can understand why they're doing it but god that's a dismal contest right to match your misery against someone else's and to try to rank order you know who had the hardest lot I mean, that's a, well, and it's so prone to the political side, man. It's so prone to the political side, like the adversity I experience at a pro -life rally where people are harassing me, I don't think that's going to sell.

[873] You know, fundamentally, it introduces ideological conformity, which I think a real outstanding question is, does somebody like a roll in Friar bring more or less diversity.

[874] You know, he's not a progressive.

[875] Black, not a progressive.

[876] To me, that in some sense brings more diversity.

[877] We don't want it to be the case that the conservatives are all white, you know?

[878] But that's not really how I think it's seen.

[879] I think it's just going to end up being...

[880] Yeah, well, the thing, I think the whole diversity, Shibileth, is a front for posers to attain status they don't deserve fundamentally.

[881] because I don't think you can do better than merit to find the way we already defined merit, which is you're a meritorious candidate if you're the features you bring to the position match the desired outcome of performance in the position.

[882] And fundamentally, as we also pointed out earlier, you're actually bound by law to do that, especially if you're an employer.

[883] Now, the law is tricky because it contains self -contradictory aspects.

[884] It's a one counter example for that.

[885] There's a guy at Bassett -Safar University of Michigan.

[886] He does amazing work in my mind.

[887] And he's a Muslim from Pakistan.

[888] And he's able to go to these madrasas, these fundamentalist schools, and interview them and get data.

[889] To me, that's actually, that's the kind of diversity that I think is good in the sense actually is opening up these new areas of research that there's no way the Madrasa would ever give me data.

[890] So there might be some, but it's a limited scope for getting certain questions answered that you might not fully answer.

[891] You could argue that as a form of competence, like if you were going to hire someone and the person said, look, one of the things I bring to this position is that I have access to an ethnic group, say, or an anthropological group that another candidate won't have.

[892] I mean, and I do think that that is actually a measure of merit and could be put under that rubric.

[893] Yeah, and the key is not to have that measure of merit just be because I'm a particular race, right?

[894] Because that's effectively how it's argued now, is that by your race that gives you that, you do merit it because you've got a unique insight into that community.

[895] Right, right.

[896] Well, and that's also a strange, that's also a strange claim, too, right?

[897] Is that merely because you have a very, what would you say, low -resolution feature that you're somehow an emblem and standard barrier for that group.

[898] You know, like, I've never thought of myself as a representative of the white community.

[899] You know, it's preposterous because, well, first of all, it's preposterous because we know as researchers into individual differences that the differences within any given ethnic or racial group are much larger than the differences between groups, which is actually the canonical non -racist statement, within group variants, trumps between group variants.

[900] It even does that between men and women in almost all domains.

[901] In fact, I don't know of a single domain where that's not true.

[902] Even in interest where men and women differ most widely, the difference is one standard deviation.

[903] There's still way more variance within the group than there is between the groups.

[904] So how do you think the universities will respond?

[905] We said how they should respond.

[906] Well, how will they respond?

[907] Well, I'm hoping it will be a heterogeneous response.

[908] I think some schools will go the UC route and get rid of the test scores and they'll do other things like diversity statements and such.

[909] I'm hoping that other schools will focus more on addressing some of the pipeline issues.

[910] I think you will see a big movement against legacy admissions.

[911] I was surprised at actually how quickly that happened.

[912] So I think that sort of stuff is going to go.

[913] To me, what I'm really pushing for is for them to use their data to be able to say, look, I can tell you that you're going to really succeed here.

[914] And we've set up our program so that you can succeed here because the competition for those students is going to be fierce.

[915] Well, right.

[916] So what a university could do, hypothetically, imagine that they say, set up actually rigorous objective testing models.

[917] So a university could say to a given candidate, your probability of succeeding in this discipline here is X percent.

[918] And so that would mean that qualified students could look at a range of universities and they could say, for example, if they were slightly lower performing on the academic front, what were interested in sciences, they could pick a university where they had, say, a 70 % chance of graduating.

[919] And so then they'd know that if they were, they could pick the university that was the most challenging that would give them some reasonable opportunity of success.

[920] Right, that'd be a good deal, right?

[921] Because there's a very wide range of universities.

[922] And objective testing could establish that across time.

[923] And you could see that happening in a state like Florida, you know, where the governor set, you know, some of the red states could move towards that model for their state system at least.

[924] So that's where I think the best path forward is I think there are other ways too the whole tie to all this in terms of racial preferences was losing your government funding obviously on the admissions front you're sort of stuck there but if you look at how these the way we're paying college athletes now you could easily have a separate organization that was sort of we're giving scholarships to black students who attend Duke you know they're not tied with the government funding and you can see it like a huge competition emerging for that where things happen more on the financial aid side not associated with the university so there's no scope to saying that it's illegal because the organization's not taking government funding.

[925] Right, right, right.

[926] You see any downside to that?

[927] I'd have to think more about that.

[928] I mean, to me, that's the market work.

[929] There's not, they're not obvious.

[930] Yeah, yeah, yeah, yeah.

[931] There's no downsides that leap obviously to mind.

[932] So now, is there anything else that we're running out of time here on the YouTube side?

[933] I'm going to flip over to the Daily Wire side for everyone watching and listening and talk to Peter a bit more about how his interest in this domain and economics in general made itself manifest so you could, you're welcome to join us there if you're inclined to.

[934] Is there anything else that we didn't cover today in relationship to the Supreme Court decision and in relationship to affirmative action and its complexities?

[935] Oh, I know what I, I know what we conclude with perhaps.

[936] You've spent a lot of time studying affirmative action.

[937] Do you have, what would you say in relationship to its putative advantages?

[938] Has it, has there been any manner in which affirmative action has actually been a policy success?

[939] Well, it certainly has increased the share of minority students at top schools.

[940] And I think those, when...

[941] As applicants or graduates?

[942] Even as graduates, because I think in places like Harvard now, they will graduate, great you.

[943] They will graduate you.

[944] So that's always been sort of a gamble, right?

[945] That by, yes, there might be these costs associated with it, but by getting them to Harvard, great things are going to happen later on in society, you know?

[946] And that's, you know, they'll be the Supreme Court justices.

[947] to get to those very top of the top positions, that would be the argument.

[948] To me, that's a little snobbish, but I understand the argument.

[949] And do you think there's any merit to that argument?

[950] I mean, see, the counter argument would be giving less qualified people a pedigree that indicates their qualifications and then putting them in ever more important situations that they're not qualified for is not a net good, right?

[951] That's a rough argument to make.

[952] And I wouldn't necessarily say I'm making that argument, but that is the counter argument.

[953] That's right.

[954] So on the one hand, our Supreme Court is more diverse because of affirmative action.

[955] On the other hand, I think that that has, you know, Clarence Thomas would say that's done a serious disservice because of being viewed that way.

[956] And you don't know.

[957] and that's the problem, right?

[958] Yeah, well, that's one of the really ugly things about affirmative action as far as I'm concerned is that the question is then begged and that's not good and that's particularly hard on people who are truly qualified, right?

[959] Because what a bloody catastrophe that is to have to face that additional level of doubt.

[960] Like, who are you really?

[961] Jesus, brutal, brutal, brutal.

[962] I mean, you take something like Glenn Lowry who I think you've had on.

[963] He's one of the most brilliant people have ever met, you know.

[964] I think he's just fantastic.

[965] And yet he had to endure all of that, you know.

[966] Yeah.

[967] Yeah, that isn't something you'd wish on your worst enemy, that's for sure, to have your genuine competence in question.

[968] Yeah.

[969] All right, well, I guess we should wrap up on this side.

[970] So as I said, to everyone watching and listening, I'm going to talk to Peter at some additional length on the Daily Wire Plus platform.

[971] about the development of his career and his interests.

[972] And so if you want to join us there, then you'd be more than welcome to do so.

[973] It's not a bad time to funnel some support the Daily Wire Way, by the way, because YouTube, for example, has been pretty assiduously at war with the Daily Wire contributors over the last month.

[974] Three of my podcasts have been taken down, and I suspect there's more in the pipeline that will suffer the same fate.

[975] And that's not good.

[976] and the other people who are using YouTube on the Daily Wire side have been hit harder than me by quite a substantial margin.

[977] So if you're ever thinking about subscribing to the Daily Wire platform, this isn't such a bad time to do it, let's say, on the moral front.

[978] In any case, you can give that some consideration.

[979] Thank you to the film crew here in Manhattan today for making this a pleasant experience and technically feasible.

[980] And to the Daily Wire Plus for facilitating the conversation.

[981] Peter, thank you very much for talking about.

[982] talking to me today and for um very much enjoying well your efforts on the research front you bet man good good to see you chow everybody till next time