Peter Arcidiacono joins us to talk about his work in identifying bias and discrimination in the Harvard admissions process.<\/p>\n
Professor Arcidiacono specializes in research involving applied microeconomics, applied economics, and labor economics. His research primarily focuses on education and discrimination. His work focuses specifically on the exploration of a variety of subjects, such as structural estimation, affirmative action, minimum wages, teen sex, discrimination, higher education, and dynamic discrete choice models, among others. He recently received funding from a National Science Foundation Grant for his project, \u201cCCP Estimation of Dynamic Discrete Choice Models with Unobserved Heterogeneity.\u201d He has also been awarded grants from NICHD for his work entitled, \u201cA Dynamic Model of Teen Sex, Abortion, and Childbearing;\u201d and from the Smith Richardson Foundation for his study, \u201cDoes the River Spill Over? Race and Peer Effects in the College & Beyond\u201d with Jacob Vigdor. Other recent studies of his include, \u201cThe Distributional Effects of Minimum Wage Increases when Both Labor Supply and Labor Demand are Endogenous\u201d with Tom Ahm and Walter Wessles; \u201cExplaining Cross-racial Differences in Teenage Labor Force Participation: Results from a General Equilibrium Search Model\u201d with Alvin Murphy and Omari Swinton; and \u201cThe Effects of Gender Interactions in the Lab and in the Field\u201d in collaboration with Kate Antonovics and Randy Walsh.<\/p>\n","protected":false},"excerpt":{"rendered":"Peter Arcidiacono joins us to talk about his work in identifying bias and discrimination in the Harvard admissions process.","protected":false},"author":13,"featured_media":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","episode_type":"audio","audio_file":"http:\/\/podcasts.la.utexas.edu\/cepa\/wp-content\/uploads\/sites\/21\/2019\/10\/19-10-21-Policy-at-McCombs-Podcast.mp3","podmotor_file_id":"","podmotor_episode_id":"","cover_image":"","cover_image_id":"","duration":"","filesize":"36.62M","filesize_raw":"38399168","date_recorded":"24-10-2019","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":""},"tags":[33,36,20,34,32,17,35,29],"categories":[],"series":[2],"class_list":{"0":"post-241","1":"podcast","2":"type-podcast","3":"status-publish","5":"tag-admissions","6":"tag-arcidiacono","7":"tag-business","8":"tag-discrimination","9":"tag-harvard","10":"tag-mccombs","11":"tag-peter","12":"tag-policy","13":"series-policymccombs","14":"entry"},"acf":{"related_episodes":"","hosts":[{"ID":693,"post_author":"38","post_date":"2020-10-29 17:58:44","post_date_gmt":"2020-10-29 17:58:44","post_content":"\n
Carlos M. Carvalho is an associate professor of statistics at McCombs. Dr. Carvalho received his Ph.D. in Statistics from Duke University in 2006. His research focuses on Bayesian statistics in complex, high-dimensional problems with applications ranging from finance to genetics. Some of his current projects include work on large-scale factor models, graphical models, Bayesian model selection, particle filtering and stochastic volatility models.<\/p>\n\n\n\n
Before moving to Texas Dr. Carvalho was part of the faculty at The University of Chicago Booth School of Business and, in 2009, he was awarded The Donald D. Harrington Fellowship by The University of Texas, Austin.<\/p>\n\n\n\n
Dr. Carvalho is from Rio de Janeiro, Brazil and before coming to the U.S. he received his Bachelor's degree in Economics from IBMEC Business School (Rio de Janeiro) followed by a Masters's degree in Statistics from the Federal University of Rio de Janeiro (UFRJ).<\/p>\n","post_title":"Carlos Carvalho","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"carlos-carvalho","to_ping":"","pinged":"","post_modified":"2020-10-29 17:59:59","post_modified_gmt":"2020-10-29 17:59:59","post_content_filtered":"","post_parent":0,"guid":"http:\/\/podcasts.la.utexas.edu\/cepa\/?post_type=speaker&p=693","menu_order":0,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":580,"post_author":"42","post_date":"2020-07-03 19:53:40","post_date_gmt":"2020-07-03 19:53:40","post_content":"\n
Mario Villarreal-Diaz is CEPA\u2019s Managing Director and Senior Scholar. Mario joins CEPA from the University of Arizona where he was an Associate Professor at the Department of Political Economy and Moral Science and taught in the Philosophy, Politics, Economics, and Law undergraduate major.<\/p>\n","post_title":"Mario Villarreal-Diaz","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"mario-villarreal-diaz","to_ping":"","pinged":"","post_modified":"2020-07-03 19:53:41","post_modified_gmt":"2020-07-03 19:53:41","post_content_filtered":"","post_parent":0,"guid":"http:\/\/podcasts.la.utexas.edu\/cepa\/?post_type=speaker&p=580","menu_order":0,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"}],"guests":[{"ID":593,"post_author":"42","post_date":"2020-07-03 20:06:33","post_date_gmt":"2020-07-03 20:06:33","post_content":"\n
Peter Arcidiacono specializes in research involving applied microeconomics, applied economics, and labor economics. His research primarily focuses on education and discrimination. His work focuses specifically on the exploration of a variety of subjects, such as structural estimation, affirmative action, minimum wages, teen sex, discrimination, higher education, and dynamic discrete choice models, among others. He recently received funding from a National Science Foundation Grant for his project, \u201cCCP Estimation of Dynamic Discrete Choice Models with Unobserved Heterogeneity.\u201d He has also been awarded grants from NICHD for his work entitled, \u201cA Dynamic Model of Teen Sex, Abortion, and Childbearing;\u201d and from the Smith Richardson Foundation for his study, \u201cDoes the River Spill Over? Race and Peer Effects in the College & Beyond\u201d with Jacob Vigdor. Other recent studies of his include, \u201cThe Distributional Effects of Minimum Wage Increases when Both Labor Supply and Labor Demand are Endogenous\u201d with Tom Ahm and Walter Wessles; \u201cExplaining Cross-racial Differences in Teenage Labor Force Participation: Results from a General Equilibrium Search Model\u201d with Alvin Murphy and Omari Swinton; and \u201cThe Effects of Gender Interactions in the Lab and in the Field\u201d in collaboration with Kate Antonovics and Randy Walsh.<\/p>\n","post_title":"Peter Arcidiacono","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"peter-arcidiacono","to_ping":"","pinged":"","post_modified":"2020-07-03 20:06:34","post_modified_gmt":"2020-07-03 20:06:34","post_content_filtered":"","post_parent":0,"guid":"http:\/\/podcasts.la.utexas.edu\/cepa\/?post_type=speaker&p=593","menu_order":0,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"}],"transcript":"
Welcome to the Policy of McCombs podcast, a data driven conversation on the economic
\n\ue5d4
\nissues up today in this series. We invite guests into our studio to provide a highlight
\nof their work presented during a visit to the University of Texas at Austin Policy.
\nEmma Combs is produced by the Center for Enterprise and Policy Analytics at the McCombs School of Business.
\nI am your co-host, Carlos Carvalho, with my colleague Mario Villarreal.
\nOur guest today is Peter r-s.d Iacono, professor of economics at Duke University. Peter joined us
\ntoday to talk about his work in association with the Students for Fair Admissions versus Harvard. A recent high profile
\ncase challenging Harvard’s admissions policies as potentially discriminatory against Asian-Americans.
\nPeter, welcome to Policy McCombs. Thanks, Evan. So let’s start by
\ndescribing generally, I guess, your role on the case as an expert witness in and how would you characterize
\nyour general findings? Well, my role is to take
\nHarvard’s data and analyze it and look to see whether there was discrimination against Asian-Americans.
\nAnd also to sort of measure the size of of racial preferences.
\nSo with that, we have access to incredibly rich data. You know, it’s six years
\nof Harvard’s Harvard’s admissions data. Was that a reason for six years
\nthat I don’t know why they gave us that particular amount? There was harvest.
\nchoice or the judge against the courts decided it was. I think Harvard’s case to give us
\nno. But beyond that. And so in
\nhow would you describe that your gender, sort of your top line summary of your report
\nand that you presented in court? So I think both
\nmyself and David kardon on the other side, you know, sought to measure the
\ndegree of racial preferences. And that was really not the focus of the of the trial itself. I think
\npeople had come to different conclusions as to how begue racial preferences
\nshould be. But what is interesting about it in this case is this is your first
\nchance to really see how big they are, because typically universities
\nare not going to show this kind of data. So is really a unique opportunity there with the trial
\nprimarily focused on was whether Asian-American
\napplicants were being discriminated against relative to white applicants. And for
\nme, the fiscal arguments for that are pretty over overwhelming.
\nYou know, I find a penalty for Asian-American applicants who
\nare not in one of these special groups and as a glorified those groups who are
\nwell, the shorthand is a l._d._c, which is athletes legacies,
\nchildren of donors and children and faculty and staff. That group represents
\napplicants. So for the vast,
\nvast majority of Asian-American applicants, I’m finding this up a penalty relative
\nto similarly situated white students. That’s sort of above and beyond
\nthe fact that they also lose out because of things like legacy
\nand athlete preferences, preferences for those LDC groups. So just
\nto summarize that, if you put everybody together and if you were to run a regression,
\nlet’s say controlling for lots of different, different characteristics
\nof the applicants, everybody together, it is clear that you see a negative coefficient and
\nimpact something that suggest a negative impact for Asian-Americans regardless
\nover. But on top of it, if you separate now and look just at the students that are being considered
\nin this for the general population, not an athlete’s legacy, dean’s list, etc.,
\nthat bounty is even larger relative to whites. Yes. Now there are ways,
\nas you know, the other side did. You can do some things to make
\nit appear as though the penalty is smaller. But
\nI think a correct treatment of the data shows that a clear penalty. So the data
\nside can ever show that the penalty goes away. For example, they can make it go in significant,
\nI say, by including everyone together,
\nincluding the athletes and legacies and so on, including the personal rating where I think
\nthere’s clear evidence of bias against Asian-Americans. And
\nI think that part of what what’s happening here is that when you include athletes and legacies
\nand such and they actually show this in our paper,
\nacademics just are not as important for legacies and athletes. Asian-Americans
\ndo incredibly well on academics. And so if you do things that make it, if
\nyou add people to the model, which shrinks the importance of academics, right.
\nThen it’s going to say, well, no, we’re not discriminate against Asian-Americans, academics to start as important. Well,
\nthat may be true for a l._d._c applicants, but it’s definitely
\nnot true forever. Else, could you spend a little bit on on on that,
\nbecause that’s one of the most common reactions I’ve seen among various people that say, look,
\nI mean, on in a ratings for our emissions process, we take
\ninto account various dimensions and we weighed them in various ways. And it
\njust happens to be that order applicants are there are non Asians like whites,
\nnamely rank very well in this disproportionate weighting, other
\ndimensions like extracurricular activities or sports
\nor things like that. Could you elaborate a little bit about what is your reaction to that position? I
\nguess maybe useful to talk a little bit about the four categories because they’re very clear here. So let’s fly the four categories that
\nHarvard has in their process. Well, Harvard has lots of categories, but, you know, they have
\nfought for what are called profile radio ratings or grades. And this profile ratings are academic,
\nextracurricular, athletic and personal. Asian-Americans
\nclean up on academic. It is amazing how well they do relative to white applicants,
\nlet alone other groups. They are also the strongest on on the extra curricular
\nrating. So then you’re left to f. I mean, the the other side basically argued that
\nthey’re not as multi-dimensional as white applicants. You get that from
\nthe athletic grading and the personal rating on the personal rating side. I
\nthink that there’s clear evidence of bias against Asian-Americans. And the argument for that
\nis that if you look at the observable characteristics, the things
\nthat we can see that are associated, higher personal ratings. Asian-Americans are stronger on this.
\nAnd there are other groups who receive a massive bump on the personal rating who are weaker on this.
\nSo that makes you think that racial preferences and penalties are playing a
\nrole in in that personal rating. That leaves the athletic grading,
\nthe athletic ratings. Very interesting. It’s not something that receives as much attention during the trial itself,
\nbut all the information in the reports, it’s part of some papers I’ve written since. And
\nusing the publicly available data, the people we do best on the athletic grading are
\nwhite legacies. And part of that’s due to
\nsome readers gaging this based on how good you are at sports, at Harvard
\noffers. Well, Harvard offers sports like sailing and and so
\non that are privileged, very privileged sports. I’m looking at a list
\nhere that you have in the paper about the sports that Harvard introduced in the past since 1974
\nand is exactly women’s squash, women’s fencing, women’s lacrosse, women’s cross-country women’s sailing, women’s skiing,
\nindoor track and field, women’s soccer, women’s ice hockey. Those are all clearly very
\nprivileged and they’re also very heavy on the female side. I assume just because for title nine.
\nExactly. But that provides them again. I don’t know if you have something in mind,
\nthe effect of gender within the categorization of the sports, that might be something that females
\nare benefiting dramatically as well. Right. We don’t have a lot of information on that in terms of
\nof what was what was reported. I will say that I think that
\nthis athletic grading. It’s surprising that they they score them, score
\nthem on that. I don’t believe that it does. I don’t believe that Stanford has an athletic rating.
\nI don’t know about other institutions. And just again, want one thing to to be very
\nclear front from the paper here that even if you control for the personal ratings,
\nyou still see a negative impact for Asian-Americans
\ncontrolling the 994 non-healthy. Exactly. Once you remove the athlete’s legacy
\nand dean’s list students, which you have to do things that are one that is already discriminating
\nagainst Asian-Americans. And on top of it, you have an extra penalty. Exactly right.
\nSo. OK, so let me actually use this to highlight one thing that you mentioned
\nhere about agents cleaning up on the on the academic standards. One number
\nthat that I’m just going to scroll here and find in the paper that you point
\nout is that you put students, applicants on deciles of of
\nacademic achievement. And if you look at the top decile, how many of the Asian-American
\nstudents are the top decile of academic achieve the top 10 percent best academic students? All right.
\ngeneral group of people applying to Harvard, 70 percent of the Asian-American that apply aren’t within
\nthat group. That’s right. And that’s double what it is for white. Is double what it is for whites
\nand is like nine times what it is for for Hispanics and is 17
\ntimes essentially what it is for African-Americans. So as they’re getting credible quality level of students coming in
\nin the Asian-American pool. That’s right. And so this gives something. And this is where I think
\nAsian-Americans are unfairly stereotype based on that. They they do incredibly well
\nin the academics, but it’s not as though that they’re weak on these other than the other dimensions,
\nwith the exception potentially of the athletic grading where they
\nthey and Hispanics do not do very well on that. And I think that.
\nYeah. I mean, what will we think about the athletic raiding thing? Well, the sports is there ready everybody
\non soccer as Hispanics who do a little better. But no, that’s not what they’re radio on Thursday, the NCAA.
\nLook, I saw well on that. It’s also like whether or not you’re the captain of your sports, right?
\nRight. Show some leadership trait or something like that. That’s right. Right. So, you know, when I went to school,
\nthere was no possibility I would make the soccer team. You know, I’m not particularly
\nathletically gifted. You know, my kids do go to a small private school. Everybody
\nmakes a soccer team if they want to play. So it’s a really favors
\nricher schools. They’re smaller. You know, you can provide people with
\nlots and lots of opportunities. And that’s
\nreally actually one of the surprising things which this paper, the legacy athlete preferences
\nat Harvard and illustrates is that when we think about holistic admissions,
\nyou think about evening, the playing field, that fundamentally you think people can buy off
\nby higher test scores or test prep programs and such. It’s not clear
\nin, you know, at Harvard anyway. Some of these other ratings seem to be more influenced
\nby income than the academics, at least within racial
\ngroups. So, you know, this holistic admissions, even things out across races,
\nbut within races, things like the athletic grading, the personal rating and so on,
\nthose are actually still favoring privilege, still favoring privileged, more so than the
\nthings like the academic rating. Right. Right. Yeah. I think I find it I find it very
\ninteresting about the papers and the ability to through your analysis, for us to see that changing probability
\nof a certain applicant, if you just were to, you know, start from a baseline and and think about change, a couple characteristics
\nthat applicant, whether it’s the income, whether it’s the net income, but but whether it disadvantage or not,
\nthe whether they’re an athlete or not or some degree about the ratings, you could even change change that in the ratings. So
\na number that I heard and you know, we talked a little bit about this. That, let’s say an Asian-American
\nwith a 20, 25 percent chance of admissions. That would be a very high achieving Asian-American,
\nprobably from a middle class that currently has a 25 percent probability of getting in.
\nIf we were to toggled that, let’s say to a white student, that probability is going to go up.
\nYes. We have to look at the exact number. But to an African-American, we talked about it. What would that probability go? Over 90
\npercent. Over 90 percent. So I should say over 90 percent if they were both
\nnot disadvantaged. The disadvantage, African-Americans.
\nThey don’t get as large of a bump for being African-American as they do if their advantage,
\nwhich is sort of one of the goals of reverse where you expect. Right. Exactly. Yeah. Yeah.
\nAnd that’s that’s the key point here, is that having an admission it’s holistic to level
\nthe playing field is one thing. But when the numbers are that big. That’s I guess, what’s being litigated. That’s what the
\nholistic we need to decide or figure out what holistic means, right? That’s right.
\nOne of the main. Opposing views, too, to the point
\nof view that you just fleshed out. Here is David Cards at UC
\nBerkeley. And I believe that his main objection is that use left
\nout of your model, a group that if you include it, it will change the results
\nof these deaths. How I see the claim like so you meet it recruited athlete athletes,
\nchildren of alumni, children of Harvard faculty and staff members and students on a special list
\nthat includes the children of donors. Those are, of course, kept
\nat a higher rate. So he argued that by removing them, yours,
\nsecurity, the results. What is your answer to that? So
\nthis is something we talked about briefly before, but the idea that including those groups,
\nit changes the relationships at the model shows. So fundamentally something like academics,
\nwe are just not as important for legacies, legacies and athletes and such.
\nThere. There’s another group that neither of us included which are foreign applicants. So
\ntypically, you know, if if you thought it was important, include everybody,
\nthen you should also have to include the the foreign applicant applicants as well.
\nIn economics, you know, we’re really big on worrying about selection and
\nselection. You know, we have papers on twins. That’s not slicing and
\ndicing the data to get to analyzing Swinton’s. What you’re really worried about.
\nWe’re looking at twins and the returns to college that
\nyou’re trying to account for selection by only looking at those at those pairs and by
\nselection. Just be clear, you’re trying to toot, toot, toot to account for the fact that that you’re not getting a random pool
\nof applicants here. You’re getting a pool of applicants that are already that that
\nthey’re different. They’re different. It’s right there. And there’s garley treated in different ways. So,
\nyou know, if you look at the bottom 10 percent of applicants in terms of their academics.
\nBerg, I think virtually no one gets in if they’re a non.
\nl._d._c. But if you’re in a legacy and you’re white
\nduring l._d._c applicants and you’re white, your admission rate is over 6 percent
\nwhen you’re in that bottom 10 percent. That’s higher than the average admission rate for whites and no
\nwhites in that non ABC whites in that bottom decile. Got it.
\nSo, I mean, that tells you the academics operate very differently for these
\nl._d._c applicants than they do for the non LTC applicants. And it’s even
\nmore so for athletes. So for athletes,
\nif you get there, there is one academic rating where only athletes get it.
\nAnd then if you go up to a four in the academic grading, which is actually very,
\nvery bad, their admission rate is almost 80 percent for athletes.
\nSo we’re talking about substantial differences in
\nhow academics matter for the different groups. I have a general
\nquestion that I don’t have one to close it up, October, go ahead. Well,
\nby reading your work, I couldn’t stop thinking about
\nyou. I mean, the admission process is hard nowadays. Right.
\nAnd that relates to a conversation that Cardless and I and other colleagues have had about how
\nthe admissions process. Maybe if it’s not broken. It may be
\nat a difficult point. So what could you tell us about
\nwhat you learn regarding that general aspects of
\nthe admissions process in not only elite universities, but
\nin general lightly? Do you sympathize with the notion that is necessary and desirable
\nto have a well-rounded approach to it? Or would you say, look, I mean, it’s
\nabout academics. Who cares if you play a sport or not?
\nWe grabbed the best students, educate them. You’ve the scales and send them to the
\nlabor market. And that’s our job, right? Like, oh, none at all. We need to to
\nmaintain a level of diversity and then well-rounded citizens. So therefore, the admissions
\nprocess should take that into account because that’s where raw material. And in your idea. What will
\nI get that I’m asking you if you could reformed admissions process at Harvard and other places,
\nwhy would you do it? It’s funny because I think I did get criticized for putting
\nweight, so much weight on the academics. I don’t really feel like I did my reports. I think my
\nreports used a lot of the academic stuff to motivate. Well, given how strong
\nAsians are doing on apalling on academics. What is that?
\nWhat do they have to look like on the rest of this to justify what they’re low admit rates?
\nBut I came out of this process much less
\nconvinced of the value of the holistic admissions. I think
\nactually, if you’re going to have racial preferences, I think something formulaic could actually be better
\nthan than what we’ve got here. I think it’s too prone to corruption.
\nI mean, you see it with the varsity blues scandal, of course. So those types of things,
\nyou know, I find that this disconcerting. You know, there’s so much noise,
\nnoise in the process as a result of different people having different perspectives on these
\nfiles. And, you know, I read the files, I read a few thousand testified
\nabout one of them and. That’s what makes it harder to detach
\nfrom the case, not the affirmative action side, which people can have different perspectives on. But on
\nthe Asian-American discrimination side, you know, the finally testified on
\nI think showed clear. Clear discrimination. We are U.T. Here have
\na 10 percent rule where if you finish in top 10 percent of your any high school public high school in the state
\nof Texas, you’re guaranteed a spot at a public university in Texas. I think any
\nof your choice and then there’s a matching process to try to. Because too many might want to come to teach a certain
\nmajor and so on. That, of course, has a ratio in better racial component to it
\nbecause because the high schools are not deterred. There are different racial compositions,
\nbut that I like the idea of a clear rule. Nobody’s messing with it. It just like,
\nyou know, you might disagree with it. The level, whether there’s some reforms to that rule. But it’s a very clear rule. Everybody
\nknows what the game is for that. Now, that’s for 75 percent of our students, 25 percent
\nof our students come from something that is holistic and has been litigator, although the Supreme Court and that’s what the holistic
\nword comes from his foes. Now, I think they come from Michigan. Right. That was the first decision was against Michigan.
\nYeah, Michigan. The formulaic approach was ruled unconstitutional.
\nDo you have let’s say that the other part to it, which I think would in my mind solve some
\nof these issues, too, is transparency. You know, so thinking about this legacy admissions
\nand such. You know, people always knew that we have legacy preferences, but we don’t
\nknow the extent. Well, now we kind of do how we do. And now
\nI think that’s a more honest approach. Is that okay? Lay the cards out. I
\nunderstand how things work. I haven’t seen much of a of a reaction in terms of of you to
\nfrom Harvard or even from critics saying that this is. I mean, some but very small, I think on
\nyou have focused on the racial component of this, not so much on the like. I can believe hard, but does that
\nso openly and so strongly. And, you know, any calls for reforming that inside Harvard
\nfrom there, even from their boards and so on? I haven’t I haven’t I haven’t seen any any of that yet.
\nThere’s a question, too, too, to sort of wrap up a little bit and and go back to the paper.
\nYou do some exercises here of thinking, okay, what would happen to the Harvard class if they were to drop?
\nUsing basically their formula of admissions made their model of ratings and so on. If they were to
\ndrop the use of race, legacy and athletes on it and I’m assuming all you
\nin here, are you dropping also Dean’s preference and. No, no, I didn’t do that.
\nYou have completed the stuff that was that was in the public. OK. OK. So. So if they
\nwere to do that. The total number of whites in the Harvard class
\nwould be about the same. I think you’re saying here would go from forty eight hundred to forty nine hundred in a given
\nyear. That’s right. But it would be different, like different whites. Exactly. But it just thinks it is racial prospectuses
\nand athletes. Right. Right. Much, much fewer like a seasoned athlete.
\nThe number of Asian Americans that would get in, we’ll go from 23:00 to thirty five
\nhundred. That’s right. That’s a huge, enormous bump. Meanwhile, the other two components will be enormous
\ndecrease for African-Americans for 200 to 400, 13:00 to 400 and Hispanics 13:00
\nfor 2 4 4 4, 4, 4. Not for whites. A different mix of whites is, as you say, but fit for
\nthe other groups. And I think that the delta that you see here in Asians, it’s that’s the part. That’s
\nthat’s that’s it. That’s exactly the the focus of the case. Right. And how justifiable
\nis that? That’s right. Those are I mean, I encourage all listeners due to this
\npaper. This paper is public. You can find it through and I will post a link to it. And
\nin our Web site as well. But the analysis and all the information is papers, I think gives
\nus an incredible insight on on what goes on in the topics at the
\ntop institution of of of of higher education, our country and perhaps in the world.
\nOne more question that I had something I haven’t thought about. I didn’t realize that a foreign applicants were not here. Foreign
\napplicants are, my guess, heavily Asian to Harvard.
\nYou know, we didn’t really do much with that. It wouldn’t surprise me because, you know, it might this
\npenalty might not be a Asian-American penalty after all. Maybe actually it just straight up Asian penalty
\nonce you put the 14 Asian applicants to it. Yeah. And, you know, I don’t know whether
\nthat’s part of the reason that we see an Asian-American penalty.
\nYou know, whether foreign applications have something to do with it, I don’t know. But we focused
\non the domestic. And so to that end as well, when I look at the number of percentage of of
\nAsians, I think in Harvard over the past many, many years, that
\nhas been that’s domestic. No, that’s interesting. That’s not actually overall. All right. All right. And
\nthat number has hovered around 20 percent pretty steadily for a long time until
\nvery recently. After the luck to it, one might say, came to play that they kicked up a little bit. We went up to 23
\npercent, I think had this last minute classes is definitely
\nmore Asian-American. And one of the things that Harvard
\ndid the summer before the trial was change a reader reader guidelines. Interesting.
\nAnd one of the biggest changes is in the past there was no
\nguidance as to how to use race in these ratings, no written guidance.
\nAnd now they make it clear that race is not to influence the personal rating. And in
\ntheir description of the personal rating, they talk about things that would be associated Asian-American stereotypes
\nas things that we. That shouldn’t penalize
\npeople. Well, that’s I guess that’s a good thing that there’s some reforms or
\nnot reforms as surreally belike they are trying to be more transparent about it. And even if
\nit’s a result of the existence of this case, if it even though the plaintiffs here did not then not win the first round
\nand might provide more, more transparency for things moving forward for sure. Peter, thanks
\nfor joining us. Apolicy McCombs. Thanks for having me. Before we wrap up, you
\ncan get more information in our medium page. Thanks for listening to Policy McCombs.
\nSee you next time.<\/p>\n"},"episode_featured_image":false,"episode_player_image":"https:\/\/podcasts.la.utexas.edu\/cepa\/wp-content\/uploads\/sites\/21\/2021\/05\/SC_PolicyMcCombs_Art-scaled.jpg","download_link":"https:\/\/podcasts.la.utexas.edu\/cepa\/podcast-download\/241\/peter-arcidiacono-on-harvard-admissions-bias.mp3","player_link":"https:\/\/podcasts.la.utexas.edu\/cepa\/podcast-player\/241\/peter-arcidiacono-on-harvard-admissions-bias.mp3","audio_player":null,"episode_data":{"playerMode":"light","subscribeUrls":{"apple_podcasts":{"key":"apple_podcasts","url":"","label":"Apple Podcasts","class":"apple_podcasts","icon":"apple-podcasts.png"},"google_play":{"key":"google_play","url":"","label":"Google Play","class":"google_play","icon":"google-play.png"},"google_podcasts":{"key":"google_podcasts","url":"","label":"Google Podcasts","class":"google_podcasts","icon":"google-podcasts.png"},"spotify":{"key":"spotify","url":"","label":"Spotify","class":"spotify","icon":"spotify.png"},"itunes":{"key":"itunes","url":"","label":"iTunes","class":"itunes","icon":"itunes.png"}},"rssFeedUrl":"https:\/\/podcasts.la.utexas.edu\/cepa\/feed\/podcast\/policymccombs","embedCode":"
Peter Arcidiacono on Harvard Admissions Bias<\/a><\/blockquote>