Post: #26

Inequality is everywhere and life is unfair.

Deal with it

Post: #27

I don't know how some of you guys are so sure that she was joking. I think she was actually being serious. It wouldn't be out of the realm of possibility for an American chick.

Post: #28

(04-07-2015 09:25 PM)Excelsior Wrote:  

(04-07-2015 10:14 AM)Kabal Wrote:  

(04-07-2015 12:35 AM)Excelsior Wrote:  

(04-06-2015 11:19 AM)Kabal Wrote:  If anyone is to feel salty, it's high-achieving Asian Americans, who regularly and systematically get passed over in favor of less qualified white [Excelsior edit], black, and latino students, so universities can get their beloved diversity...

Fixed that for you.

It was correct the first time.

No, it was not. The accurate statement would have noted that high-scoring Asian Americans are passed over in favor of black, latino, AND white students with fewer purely academic qualifications, not just blacks and latinos. This is the reality of the situation.

Yes, it was. The reality of the situation is there is no support for universities, particularly universities like Duke that are associated with high-achieving Asians (i.e. elite universities, like in Espenshade’s paper, where the bulk [57%, from Table 2] of applicants have SATs on the old scale over 1400), funneling acceptances from Asians to whites as part of affirmative action (“diversity” initiatives).

Data from multiple sources, including a little work done by me, suggest that the affirmative action that elite colleges actually employ is somewhere in between a transfer of admissions from Asians to latinos and blacks (with zero effect on whites) to transferring admissions from both Asians and whites to latinos and blacks.

More on this below.

(04-07-2015 09:25 PM)Excelsior Wrote:  The Espenshade and Chung estimation has been proven inaccurate with time. Their estimation predicted that white rates of admission/representation would increase slightly. They were inaccurate: from 1990 to 2005, large declines in white enrollment were seen in all of the states observed in which public post-secondary institutions were prohibited from the consideration of race in admissions (Texas, Florida, and California - the schools observed were UCLA, UC-Berkeley, UCSD, UT-Austin, and the Univ. of Florida). Decreases in the non-hispanic white share of the populations in these states only partially explain this - the reality is that many whites were being pushed out of the running by high-achieving Asian applicants. Of all the schools observed in each of the three aforementioned states (Texas, Florida, California), only UCLA's white population held relatively steady (1% decline from 1990 to 2005).

More specifically, white males saw a particularly dramatic decline at all five of the universities analyzed in the three states. UCLA remained the most stable again (less than 4 percentage points in decline), but every other institution saw declines north of 10% and as high as 12% in their white male populations. White women, by contrast, saw their numbers go up.

Blacks and Hispanics saw substantial declines, as predicted, but so did whites. Asians were massive beneficiaries, as predicted, but not solely at the expense of blacks and latinos. Espenshade and Chung underestimated the impact that the removal of AA would have on White Americans.

If we are to say that the numbers after the prohibition of AA can be taken as a fair proxy for the number of "less qualified" members of other groups occupying spots that would otherwise have gone to Asian-Americans, then we cannot say that there are not a substantial number of whites involved here.

No, the Colburn, Young, and Yellen paper does not “prove” Espenshade and Chung wrong. You came to that conclusion due to your overzealous, and quite frankly, naïve reading of their paper, in conjunction with glaring flaws in their approach and their interpretation of results.

I spot four glaring ones:

1) Their usage of enrollment proportions/shares per race over time to draw inferences, when admission rates at a given time are the crux of the issue.

The important metric in play is admission rates per race, in particular whether or not particular races receive boosts or dampeners on admission rates when academic strength is taken into account. Admission rates per race are just a function of academic strength and racial preferences. If you know which applicants were admitted, academic strength (e.g. SAT scores), and what race they were (data of which Espenshade and Chung had) in a given application cycle (or averaged over multiple cycles, where a cycle is typically the fall of each year), it’s a trivial exercise to estimate what the admissions preferences were per race (which Espenshade and Chung did) for that/those cycle(s). It’s just a logistic regression-based framework.

So after solving for preferences for race, one could (like Espenshade and Chung) then estimate the impact of affirmative action on admission rates by setting preferences to zero for everyone, and also estimate no-affirmative action admission proportions by race for that cycle since they know the applicant proportions by race. And from this they saw that, overall, going to no affirmative action would see many more admissions go to Asians, with much fewer going to latinos and blacks, and whites staying mostly flat (slightly up)—for both admission rates, and admission proportions. This may not be the case for each and every school, but it is case for the elite school cohort overall (and hence in line with my comment about high-achieving Asians).

However, enrollment proportions per race are a function of admission proportions per race and yield rates per race. So enrollment proportions obscure information about admission proportions if you don’t know the yield rates by race, which in turn obscures information about admission rates per race if you don’t know the application proportions.

However, this is exactly the situations the authors (Colburn, find themselves in. They track enrollment proportions over time, and want to make inferences about admission rates and racial preferences. But application proportions by race, and yield rates by race change over time, as do the average academic strengths! On a year by year basis these differences may not be huge, but on a longer time frame it certainly could be.

You can proxy the application proportion changes by race via demographic changes by race (as the authors informally did [but not formally by incorporating it into their enrollment results]), but that still leaves taste changes by race unaddressed (University A could fall out of favor with Race Z over time for whatever reason, thus decreasing its application proportions of Race Z, even with no change in the demographic proportions of Race Z).

Data on enrollment proportions by race is easy to find, admission proportions not so much, and admission rates by race harder yet.

It appears that you conflated enrollment and admission proportions, and mirrored the authors in neglecting the importance of application proportions and yield rates.

2) Picking the years 1990, 1995, 2000, 2002, 2004, and 2005 as the analysis years, and focusing drawing conclusions on long term trends. Why would you ever pick just those years, when the UC schools ruled to end affirmative action via Prop 209 in 1996, which went into effect for undergraduates in 1998 (and whatever the equivalent is for UT and UF)? 1997 and 1998 are the most important years to see the effects of ending affirmative action for UCSD, UCLA, and UCB (UC Berkeley).

I will focus more on UC schools, particularly UCLA and UCB, and especially UCB, as we know the effective date of affirmative action for UC schools (I couldn’t find confirmation for UF and UT). Also, UCB (mean SAT of 1375), UCLA (1320), and UCSD (1290) are #1, #2, and #3 amongst those five schools for enrollee SAT scores and Newsweek rankings, with UCB probably in the middle to low end of Espenshade and Chung’s set of elite schools (judging from Espenshade and Chung’s Table 2, and keeping in mind enrollees are on average dumber than admitees), and UCLA low to… not in it. It can likely be agreed that hardly anyone would label UCSD, UT (1260 mean SAT), or UF (1265) as an elite school… with UCLA on the brink.

Similarly, why would you use the 1990 to 2005 change in enrollment rates, or even the 1995 to 2000 change, to draw inferences, when it’s the change from 1997 to 1998 that’s the most important for gauging the effects of ending affirmative action for the UC schools? The effects of ending affirmative action essentially overnight should be immediate, like shutting off your faucet. It shouldn’t slowly bleed over the course of two decades.

Ending affirmative action starting at year a should have little to no effect on admission trends between years a + m and a + n, where m and n are positive integers and n > m.

Again, unfortunately, you followed the authors astray.

3) The “trends” on the graphs don’t even support the authors’ claims. If the increase from 1995-2000 in Asian enrollment proportions (Graph 11) is due to the end of affirmative action for UC schools, why does 1990-1995 have even greater increases for 2/3 UC schools? If ending affirmative action was negative for whites, why does its enrollment proportion increase in 1995 to 2000 for UCLA and hold flat for UCB (Graph 13)?

4) Their graph formatting. In particular, using the “Smoothed Line,” option in Excel and spacing the years out equally on the graph, even though the temporal distance between them is not the same.

The line smoothing increases the appearance of “trends,” and disguises the fact that there’s only six years used as points, with nothing in between them. The equidistant spacing of years that are not equally apart in time adds general fuckery and increases the appearance of trends in 1995-2000. For example, the 5% drop in white enrollment proportions from 1995-2000 for UCSD could easily be mentally misinterpreted as a 5% year-over-year drop by an unsuspecting reader, whereas it’s only a 1% decrease year-over-year on average. This chicanery is like something out of an xkcd joke.

The data of this Colburn, Young, and Yeller paper made no progress on “disproving” Espenshade and Chung’s 2005 paper, despite your wishes.

I did a search online for annual admission data by year by ethnicity, specifically looking for data going back into the 90s. Out of the five, I was able to find UC Berkeley’s. Berkeley works well, because we know exactly when affirmative action took place for UC Berkeley; also, it’s easily the most prestigious school out of a group with UCLA, UF, UT, and UCSD, and thus fits the best with the school profiles in Espenshade and Chung’s paper and my original comment about high-achieving Asians.

The raw results are here courtesy of UC Berkeley, I re-calculated the proportions by ethnicity via removing “Other” and “Not Given” from the denominator. The table and time series graphs are below (note that I have equidistant spacing between years). I put “White” and “Asian” on a secondary axis to give a better sense of the relative changes in proportions.





Results are striking. The end of affirmative action starting in 1998 is associated with a drop in proportion of admissions from 1997 to 1998 of 4.5% and 7.5% for African Americans and latinos, respectively. Conversely, Asian and white proportions rose by 7.4% and 5.1%, respectively. The relative changes are also remarkable. The African American proportion dropped relatively by 61% and the latino one by 45%. The Asian and white proportions rose relatively by 19% and 14%, respectively.

Antonovics and Backe did not split white and Asian for many of their calculations (they found them similar enough to be lumped together, as well as with race other/unknown), but their non-URM (whites + Asians + other/unknown) and URM (black, latino, Native Americans, etc.) admission rate data confirm the pattern illuminated by my admission proportions calculations. Acceptance rates for non-URMs went from 32% to 28% for UC Berkeley, and 38% to 32% for UCLA, in the 1995-1997 regime versus the 1998-2000 regime. However, for URMs, it went from 52% to 25%, and 47% to 25% for UC Berkeley and UCLA, respectively.



I imagine it can be agreed that these sudden, abrupt movements from 1997 to 1998 cannot be explained by changes in application proportions by ethnicity or academic strength by ethnicity, like slow changes over longer time horizons can. Data on admission rates (PM me if you’re curious about the source, there’s banners on the paper not to circulate or cite without direct permission of the author) for UC Berkeley and UCLA corroborates my findings. Admission rates for both whites and Asians at UC Berkeley rose slightly between 1997 and 1998, and admission rates for blacks and latinos plummeted. Similarly at UCLA, white and Asians admission rates held flat from 1997 to 1998, while that of blacks and latinos plummeted (admission rates in general trend down in this period for UCLA).

So that leaves just preferences for groups, i.e. affirmative action, that changed between 1997 and 1998 in moving to zero preferences for any group.

There is simply no evidence here that affirmative action is a net-gain to whites for elite university admissions. In fact, UCLA, and especially Berkeley, suggest the opposite: affirmative action depresses the Asian and, to a lesser extent, white proportions in favor of blacks and latinos for elite university admissions, as implied by the Espenshade and Chung findings. In the case of Berkeley, Epsenshade and Chung would had underestimated the benefit to whites of ending affirmative action, while getting Asians, blacks, and latinos correct directionally and roughly in magnitude. Colburn, Young, and Yellen messed up (or intentionally misled...) big time by neglecting 1997-1998.

(04-07-2015 09:25 PM)Excelsior Wrote:  [Stuyvesant Enrollment Rates]

The Stuyvesant enrollment rate tangent doesn’t tell you very much, because you don’t know what a non-affirmative school will do when it does start employing affirmative action.

It’s easy to tell the effects of affirmative action when you have the data of applicants of schools that do employ affirmative action—as discussed, you estimate the preferences by race based on actual data, and then see what happens to admission rates by race when you set preferences to zero.

It doesn’t work the other way around, because you don’t know what affirmative action preferences Stuyvesant would employ. They are free to determine it as they wish. This is in contrast to the former situation, like in Espenshade and Chung’s set of elite schools, where you can see the preferences they do employ, and you know the preferences in the no affirmative action scenario—zero! No freedom to determine it as they wish.

Stuyvesant could realistically:
1) “Take” admissions from Asians and whites and “give” them to blacks and latinos
2) “Take” admissions from Asians and “give” them to blacks and latinos, leaving whites alone
3 )“Take” admissions from Asians and “give” them to whites, blacks, and latinos

Espenshade and Chung observed that elite colleges overall do something between 1) and 2) for affirmative action. UC Berkeley and UCLA certainly looked like they were doing 1) pre-1998.

Since we are talking about elite universities and (no) affirmative action, why turn to Stuyvesant High School? We have a better comparison: Caltech.

Let's see if it can tell us something about competitiveness by race as we move further into the right tail.

Caltech is highly selective, and doesn’t practice affirmative action, legacy, or athletics-based admissions. It has the highest average SAT score out of all universities and colleges. It also dominates in patent rates and PhDs per capita metrics. We can say to a first approximation that Caltech represents the most stringent university when it comes to academic admissions.

The more stringent a non-affirmative action university is with academic admissions and no affirmative action, all else equal, the more racially “unbalanced” it should be in terms of enrollment proportions, holding the other variables constant. So Caltech should approximate the most “unbalanced” racially a university (with similar applicant proportions by race, applicant academic relative strength by race, and applicant relative yield rates) could be under no affirmative action, given its academic stringency and lack of affirmative action.

If the gap in academic strength between Asians and whites is large on the right tail, we should see many more Asians at Caltech relative to whites compared to a less rigorous, non-affirmative action school. If it is small, the difference will be less noticeable, perhaps even in an unintuitive direction as application proportions and yield rates drown out the signal. If the gap in academic strength is large between whites and blacks, we should see many more whites at Caltech than blacks relative to the comparison school, etc.

Fortunately, Caltech is also in the same state as our previous two more highly-regarded UC schools. UC Berkeley is not as elite as Caltech, but is similar in its reputation as an Asian, geeky, STEM school—so it should attract a similar applicant pool, albeit not as strong. UCLA is UC’s #2 school, and is closer geographically to Caltech (Pasadena is 10 miles from Los Angeles according to Google). Caltech’s average SAT score for enrollees is 1545, UC Berkeley, 1375, and UCLA 1320. So looking at Table 2 for the SAT score distribution, and keeping in mind that acceptees tend to be smarter on average than enrollees, CalTech would be amongst the best schools in Espenshade and Chung’s data set of elite schools (and best schools in general), UC Berkeley in the middle to lower region, and UCLA in the lower region (and perhaps not at all…). UC Berkeley and UCLA are essentially peer schools compared to CalTech, given how far on the right tail CalTech is, even though UC Berkeley is more prestigious than UCLA in isolation.

In short, CalTech and Berkeley are similar in the Asian, geeky, STEM stereotype, CalTech and UCLA in geographical location, and Berkeley and UCLA relatively similar in student strength.

Similarly, I calculated proportions by race by making the breakdown to be Asian, Black (African American), latino, and white, and adjusting the denominator to sum up to 100%. I left the raw numbers on top to ensure that my re-calculation did not paint a different picture. I got the raw numbers from CollegeData for CalTech and UCLA, and from Berkeley’s website for Berkeley.



We do see materially more Asians on a relative basis as we move from left to right, from UCLA to UCB to Caltech (albeit not much difference between UC Berkeley and Caltech), and materially fewer blacks and latinos. The proportions for blacks and latinos drops by roughly 39% and 48%, relatively speaking, going from UCLA to Caltech. Whites seem to be more than holding their own against Asians, with Caltech having the highest proportion of whites.

So it appears that for elites universities, as exemplified by Caltech, whites aren’t doing much worse than Asians on the right tail. This concords with Espenshade and Chung’s results, as well as SAT test score data straight from ETS. The Asian-white gap is small compared to the white-latino gap, and especially the white-black gap, and that’s reflected in enrollment proportion differences. As you move from less cognitively elite to more cognitively elite, the three-school comparison does not suggest Asians crowding out whites more, but rather it’s latinos and blacks being pushed out—especially latinos, in California’s case.

(04-07-2015 09:25 PM)Excelsior Wrote:  [Personal Anecdote]
…
[Hurwitz on Legacies]

If one must insist on playing the blame game with regards to this topic, they should take care to at least be accurate about it. To claim that Blacks, Latinos, and Native-Americans are the only beneficiaries of affirmative-action is to perpetuate a myth backed by popular sentiment (which favors the portrayal of Blacks and Latinos as whiny, over-privileged free-loaders who complain too much and receive too much for it) and flat out ignore the statistical and historical reality of the situation. White Americans are getting theirs as well, just as they always have. Blacks and Latinos have no monopoly on admissions based on criteria that are not strictly related to academic qualifications (i.e. test scores), and they never have. Don't get it twisted.

I see you are shifting the goalpost now to legacies and athletes. I’ll play along.

Hurwitz and Espenshade and Chung actually have similar results for legacies. Hurwitz estimated a 45.1% increased probability of acceptances for primary legacies vs. non-legacies. Espenshade, Chung, and Walling estimated in 2004 the odds ratio for legacies vs. non-legacies to be 3.05 (legacies having a 3.05 times greater chance of admission than non-legacies when race, sex, citizenship, and SAT-scores were accounted for). Now back to their 2005 paper where Espenshade and Chung display an observed 21.2% admissions rate for non-legacies: 21.2% * 3.05 – 21.2% ~= 43.5%. Although my calculation is an approximation (after all, probabilities cannot go above 0 or 1), it can be seen that their results are similar. Espenshade and Chung estimate the legacy benefit to be the equivalent of 160 points. Likewise, they estimated the boost recruited athletes received to be 200. The benefits estimated for blacks, latinos, and Asians versus whites were 230, 185, and -50, respectively.

So a student being black versus being white is still a larger advantage than being an athlete or legacy, with latino in the middle of the two—and most whites aren’t legacies or athletes. Table 2 also reveals that legacies would actually see their admittance rates go up with preferences for affirmative action, legacy status, and athlete status removed, since most of the legacies and athletes are white. Most athletes are white, but most whites are not athletes.

Legacies are a small portion of the white applicant pool, and applicant pool in general (as per Hurwitz [6% of all applicants], and Espenshade and Chung [I calculated about 9% of the white pool using the fact that 75.6% of legacies are white in the data set [Page 301]), and legacies have slightly higher test scores on average than non-legacies anyway, as per Hurwitz. Similarly, I calculated about 15% for the proportion of the white pool that is a recruited athlete, with 73.3% being the proportion of athletes that are white (P. 298). So my back-of-the-envelope calculation for the effective benefit to whites is about .15 * 200 + .09 * 160 = 54.4 in SAT points for the athlete and legacy preference, assuming no other races have legacies or athletes (which is not a realistic assumption, so 54.4 is a ceiling), no overlap, and linearity. This is but a fraction of the black and latino preference advantages over whites.

We have further evidence (from Duke!) that, on average, the admissions boost from legacies, athletes, and affirmative action together to blacks is larger than that of whites. Arcidiacono, Aucejo, and Spenner observed that black Duke students change majors over the course of their college careers to less rigorous ones more often, and adjusted for type of major and/or course selection, get lower grades/GPAs. But this is because black students have lower SAT scores (Table 1). A regression that includes SAT scores makes many of these differences go away (Specification 2 in Tables 14, 15, 16). Average SAT scores were 1416, 1275, 1347, and 1457 for white, black, latino, and Asian students, respectively, with standard deviations of 105, 105, 103, 94, respectively. Duke is but one school, but notice how that lines up reasonably well with Espenshade and Chung's calculations for racial preferences in SAT points for elite schools overall. It can be estimated that 91% of black Duke students had SAT scores under the white mean (NORMDIST((1416-1275)/105,0,1,1) in Excel). Furthermore, adjusting for course grading and course selection, blacks had much lower class rankings throughout their tenure at Duke than did white students:




Unfortunately, the authors did not include the corresponding figures involving Asians and latinos.

If the admissions boost to blacks, on average, via the summation of affirmative action, legacies, and athletes, were not substantially greater than that of whites, we would not see these performance differences. But we do. Duke provides further evidence of the black net admissions boost per capita via preferences, whether racial, athletic, or legacy-related, being far greater than that of whites. Duke's racial preferences for blacks are reflected in worse black academic performance.

So from Hurtwitz, Espenshade and Chung, and Arcidiacono, Aucejo, and Spenner, it is quite evident that the average black student gets much more of an overall preferences boost than does the average white student in admissions.

But what about aggregate effects, since there are a lot more white students than black students? Even if the average white preference is less than that of the black preference when factoring in affirmative action, legacies, and athletes, the total effect of legacies and athletes could be greater than that of affirmative action since there are lot more whites in general than blacks (if you gave each woman in a room $2 and each man $1, the average effect is greater for woman, but if there’s one woman and ten men, then the aggregate effect is greater for men).

Espenshade and Chung took into account legacies and athletes (Table 2). With no legacy benefits, no athlete benefits, and no affirmative action, the estimated Asian proportion of acceptances goes up from 23.7 % to 33.3%, whites slightly down from 51.4% to 50.8%, blacks down from 9.0% to 3.3%, and latinos 7.9% to 3.8%. So the aggregate effect of removing all these preferences would look to have a small effect on whites (0.6% decline in proportion of acceptances) but a large one on blacks (5.7% decline) and latinos (4.1% decline), and a large gain for Asians (9.6% increase). And as we see from my first post, most of this is driven by the removal of racial preferences. And furthermore, the effects of all preferences together still looks like a transfer of acceptances from Asians to blacks and latinos on net, with whites near zero movement.

So in conclusion, the white benefit, on a per capita or aggregate basis, from the sum of legacies, athletes, and affirmative action (the last of which looks insignificantly different than zero [my original remark]), pales in comparison to that received by blacks and latinos via affirmative action. No matter how much you mood affiliate and make cunty remarks like “don’t get it twisted” (oh, the irony…), you can’t hamster wheel the data and numbers away.

For elite college admissions, there is no evidence for white Americans as a whole “getting theirs,” in terms of affirmative action and overall preferences received.

I don’t like writing long posts (nor reading them…) but this topic is interesting, with lots of low hanging fruit to pick-off (since people don’t realize how much available data there is on this, and how to interpret them).

Post: #29

What all those Affirmative action stats tell us is that it does not pay to follow the rules and try to get by purely on your own merits or hard work in the U.S.

In order to succeed you must game the system and society.

Conventional hard work is not really rewarded in these multicultural havens especially when it comes to women, economic success, and power.

It's all about the hustle and just confirms another red pill truth.

Post: #30

Kabal - I like your takedown of the college admission data, but what is your opinion on the underperformance of Asian students AFTER getting admitted at those elite colleges? There seem to be some studies out which address the issue - my perception is that it is a combination of cheating on tests on some Asians (especially widespread if SAT tests were done by foreign students), lack of real interest in the field being mainly pushed by their family to study.

Now I am not discounting the work-ethic of most of the Asian population, but somehow their motivations seem to be a bit off long-term.

Post: #31

This should serve as kind of a wakeup call to some career track obsessed asian ambition bots. It's far better to go the entrepeneurial route or figure out an alternative way to make that money in a more fulfilling and productive way.

What is definitely not fulfilling is slaving away to get some ivy league degree in order to get fucked over and not even get paid properly for the effort.

Everyone else is basically piggybacking off the hardest working suckers and academic robots who are firmly entrenched in this mindset.

Start your own business and that way your hard work is for your own benefit.

On top of that you can do whatever you want, then you can extend your middle finger to shitheels in U.S. society that would otherwise be getting a free ride at your expense.

I'm not going to lie there is schaudenfreude in knowing that I can sit back with a glass of wine in the middle of the day in the Philippines and still make money while some tool is busting his ass trying to impress the boss and play office race/gender/dicksuck politics so they can get another career progress biscuit in their dog bowl.

That ivy league degree is as meaningful as the toilet paper you wipe your ass with when it comes down to that simple life reality.

Post: #32

Was she trying to "force" them? hmmm

"The individual has always had to struggle to keep from being overwhelmed by the tribe. To be your own man is a hard business. If you try it, you'll be lonely often, and sometimes frightened. But no price is too high to pay for the privilege of owning yourself." - Rudyard Kipling

Post: #33

(04-11-2015 09:56 AM)Beyond Borders Wrote:  Was she trying to "force" them? hmmm

Good thing she didn't try to pull this in California.

No means no.

Post: #34

(04-11-2015 01:59 AM)Kabal Wrote:  I see you are shifting the goalpost now to legacies and athletes.

Not really. I do not believe the consideration of legacy and athlete admissions to be at all out of line with the original statement you made to begin this discussion:

(04-06-2015 11:19 AM)Kabal Wrote:  If anyone is to feel salty, it's high-achieving Asian Americans, who regularly and systematically get passed over in favor of less qualified black and latino students, so universities can get their beloved diversity--where students are various shades of brown, and vote Democrat.

I read this statement to refer to the negative impact that admissions systematically based on criteria that are not strictly related to academic qualifications have on Asian-Americans, and why they should be upset about that. The fundamental issue here relates to "less qualified" students taking the place of those high-achieving and more deserving Asian-American applicants.

If you are going to have a discussion about affirmative action in relation to its supposedly deleterious impact on applicants with the most "merit" (while using test scores as the sole determination of a given applicant's merit, as we are in this instance), then you must necessarily touch on other "non-merit" based systematic preferences as well, as they to relate to the fundamental concern here: the systematic admission of "less qualified" applicants on the basis of criteria that are not strictly academic ahead of high-achieving, higher-scoring Asian Americans.

If Asian-Americans are to feel "salty" about their being passed over for Blacks and Latinos with less "merit" on the basis of Affirmative Action, then they must necessarily feel the same way with regard to those who get in ahead of them on the basis of other "non-merit" based preferences.

Quote:But what about aggregate effects, since there are a lot more white students than black students? Even if the average white preference is less than that of the black preference when factoring in affirmative action, legacies, and athletes, the total effect of legacies and athletes could be greater than that of affirmative action since there are lot more whites in general than blacks (if you gave each woman in a room $2 and each man $1, the average effect is greater for woman, but if there’s one woman and ten men, then the aggregate effect is greater for men).

Espenshade and Chung took into account legacies and athletes (Table 2). With no legacy benefits, no athlete benefits, and no affirmative action, the estimated Asian proportion of acceptances goes up from 23.7 % to 33.3%, whites slightly down from 51.4% to 50.8%, blacks down from 9.0% to 3.3%, and latinos 7.9% to 3.8%. So the aggregate effect of removing all these preferences would look to have a small effect on whites (0.6% decline in proportion of acceptances) but a large one on blacks (5.7% decline) and latinos (4.1% decline), and a large gain for Asians (9.6% increase).

In short, you are saying here that Blacks and Latinos have no monopoly on admissions based on criteria that are not strictly related to academic qualifications (i.e. test scores), and that it is indeed the case that whites would be among those displaced by high scoring Asian-Americans in the event of the total elimination of these not-strictly-academic criteria.

Thus, this statement...

Quote:If anyone is to feel salty, it's high-achieving Asian Americans, who regularly and systematically get passed over in favor of less qualified white [Excelsior edit], black, and latino students, so universities can get their beloved diversity...

...is accurate. Estimates indicate that Asians are being passed over for "less qualified" (in a strict test-related sense) blacks, latinos, and whites. Blacks and latinos possess no monopoly on admissions that aren't based strictly on academic criteria.

Looks like we agree here after all.

I should note, however, one possible limitation with regards to the E & C estimates: the sources of the data. The three "private, selective research universities" from which the numbers in their estimate are drawn are not revealed, but they were taken from the list of schools that were involved with the 1998 Bowen and Bok dataset (which can be found here).

The E & C estimate focuses exclusively on those three "private, selective research universities". Given the limited number of such universities in the Bowen and Bok dataset, the estimates must have been drawn from any 3 of the following:

Columbia University
Duke University
Emory University
Northwestern University
Princeton University
Rice University
Stanford University
Tufts University
Tulane University
University of Pennsylvania
Vanderbilt University
Yale University

If E & C were to undertake a broader analysis including a more expansive list of private research universities as well as a number of smaller, elite liberal arts colleges, it is plausible that their numbers regarding the negative impact of the deletion of legacy and athlete preferences on white applicants would go up.

There is some evidence to support this:

Quote:Of the top thirty national universities in the rankings, three—the University of California at Berkeley, the University of California at Los Angeles, and Vanderbilt University—reported that they do not consider alumni/alumnae relations in admission decisions. Vanderbilt officials subsequently told the author that they do consider legacy status. Princeton and Notre Dame characterized legacy status as “important,” and the University of Virginia as “very important.” Of the top thirty liberal arts colleges, only Davidson reported not considering alumni/alumnae status.

Top national research universities may tend to weigh legacy admissions less heavily than top liberal arts colleges, and are more likely overall to disregard such admissions altogether.

If there is indeed a tendency for smaller, elite liberal arts schools to show a higher preference for legacies (as I suspect there might be), then there could be reason to posit that the E & C estimates above underplay the actual impact of legacy preferences on white admissions and that the negative impact of the elimination of legacy preferences on white admissions could be higher than the E & C estimate.

Furthermore, schools differ in their preference for athletes. Elite liberal arts colleges (ex: Williams, Middlebury, Hamilton, Bowdoin, Amherst, etc) tend to have a larger proportion of white athletes (and much whiter student bodies in general) than do larger research institutions like Duke, Northwestern, and Vanderbilt. Were these schools to be factored into the E & C estimate (alongside the larger private research universities that currently are the sole source of data for the estimate), it is plausible that the impact on white admissions in relation to the elimination of athlete preferences would increase.

These are mere theories, however (I've not located any peer-reviewed study in which the effects posited are explicitly stated), so take them as you will.

Quote:[b]So in conclusion, the white benefit, on a per capita or aggregate basis, from the sum of legacies, athletes, and affirmative action (the last of which looks insignificantly different than zero [my original remark]), pales in comparison to that received by blacks and latinos via affirmative action.

...but is still present according to the estimates we do have, indicating that my claim regarding the notion that whites are among the "less qualified" applicants taking seats way from high-achieving Asian Americans is accurate.

Quote:No matter how much you mood affiliate and make cunty remarks like “don’t get it twisted” (oh, the irony…), you can’t hamster wheel the data and numbers away.

Quote:For elite college admissions, there is no evidence for white Americans as a whole “getting theirs,” in terms of affirmative action and overall preferences received.

No, not as a whole, but there is evidence for those with more affluence and/or legacy "getting theirs" ahead of many high-achieving Asian-Americans. It is clear that the ranks of "less qualified" students coming in ahead of high achieving Asian-Americans on the basis of criteria that are not strictly academic are not exclusively black and latino - there are whites among them as well, perhaps as many in the aggregate as there are URMs.