<p>Your initial reaction is a Freudian slip; now you are being defensive.;)</p>
<p>I used to duly note that in my mental profile- an anti Asian bias, defensive, outbursts are more genuine etc. I also suspect you of being a pseudo-liberal, but unless I “test” you out as above, it is not fit for my working hypothesis.</p>
<p>This type of mental profiling has made it possible for me to “swim with the sharks” and came out alive (though not unscathed). Margaret Thatcher was wrong when she said study of history is useless. I just demonstrated how powerful historical analysis can be.LOL</p>
<p>I appreciate that you find me consistent. It all comes back to establishing a working hypothesis based on all known empirical data, which means opinions and personal “stories” don’t count. If all knowledge intersects in infinity as I believe, then I know I am at least moving in the right direction. </p>
<p>My opinion is very fluid. If you or anyone else can provide me with empirical data that goes counter to my working hypothesis, I will try to modify my hypothesis to take the new data into account. If that still doesn’t work, I have no qualm scrapping it and rebuild a new one.</p>
<p>Thinking about it, is this why I am not religious?</p>
<p>See Table 3.4 of Espenshade’s presentation (slide #12, page 4 of the PDF file from the initial posting of this thread). Espenshade’s full (all variables included) model of private school admissions, no. 6, finds huge and significant interactions between race and class:</p>
<p>Asian lower-class applicants have 91.5 times higher admissions odds ratio than identical White applicants (610 x 0.15).</p>
<p>Asian working-class applicants have 2.94 times higher admissions odds ratio than identical White applicants of the same economic class (19.62 x 0.15). </p>
<p>All odds-ratios used above are significant at the same three-star (p<0.001) level as the Asian “3-to-1” figure that is being claimed as a statistical proof of discrimination. </p>
<p>This is all to say that your ramblings about “statistical significance” (a concept that you misunderstand and misrepresent), even if they were correct, do not add up to a whit of difference between the two situations. You are left with some explaining to do as to how these supposedly Asian-hating, discriminatory, stereotyping institutions of higher learning become great lovers of Asians at the lower economic ranks. A lot of the stereotypically high-testing, low-EC, science and engineering-oriented Asian applicants that the universities supposedly hate (and that, according to the same theory, the white applicants can’t compete with) are in those lower economic strata — the Asian socioeconomic profile is similar to that of Hispanics. It will be amusing to see how many conspiracies you need to postulate in order to reconcile these two opposite “findings” by Espenshade.</p>
You think criticism of the Chinese government reveals an anti-Asian bias? Whatever, man. You think the suggestion that Asian students disproportionately identify STEM majors reveals anti-Asian bias? Whatever.</p>
<p>I’m perplexed at how quickly the Michigan data were dropped after I showed that they support exactly what I’ve been saying. And if you want to see something really interesting, you might want to drill down a bit more and compare the major choices of Asian males and white males.</p>
<p>I did it myself, because I’m so helpful. At Michigan, there were 372 Asian males; 176 of them were in STEM majors. That’s 47%. There were 1968 white males, with 764 in STEM majors, or 38.8%.</p>
<p>I’m inclined to think “No” if you are relatively ORM (e.g. half-Asian, half-white), but to a lesser degree than if you were fully ORM as long as there are some URM/neutrals mixed in there. Contrarily, I’m inclined to think “Yes” if you are relatively URM (e.g. half-black, half-white), but to a lesser degree than if you were fully URM given that there are some ORM/neutrals mixed in there. If you fall into category 1 (e.g. half-Asian, half-white), at least there is a greater chance that your name hides the fact that you’re relatively ORM (e.g. you may be half-Asian, half-white but your name may be “Charlie Horse” instead of “Chin Ho”). Correct me if I’m wrong.</p>
<p>Hunt - If you are inclined to discuss the Michigan data further, might you pull up the data that I requested, with URM comparisons? Based on your previous Yale data, I have a pet hypothesis. Just so long as you’re being helpful.</p>
<p>I’ve never disputed the general inclination of Asians toward STEM fields. But they should not be penalized for this bias unless the presumably lower admission rate for STEM-inclined Asian applicants is proportional to a higher level of achievement for STEM-inclined white and URM applicants.</p>
<p>You clearly didn’t understand the argument in context, which is not the first time you have done that. The context was that Elites have a business reason for choosing to prioritize a balanced class on maximum measures of balance, in order to stay competitive in the marketplace (given their market – the kinds of students attracted to them in the first place); to do otherwise will draw students away from them and toward competitors who do offer such balance. By contrast, plenty of schools with far less diverse student bodies nevertheless do not need such mixtures within their student bodies to thrive economically and compete. Their applicants are not going to go elsewhere without such mixture. The less competitive a college is in the overall higher education marketplace, the less need there is to supply varied components of student satisfaction.</p>
<p>…except that they’re penalizing themselves by choosing to compete within a vary narrow field of options in higher education, where the odds of acceptance are low to begin with, even without considerations of racial balance. There’s no particular “right” of any student of any personal background, including minorities (URM’s or ORM’s), to be accepted to a private educational institution. Two things have to be necessary: space to accommodate that student, and competitive qualification according to the institution’s definition of qualification(s). When the number of qualified applicants of any particular segment (including whites) vastly exceeds space, the institution, if it doesn’t want to become culturally homogeneous within one department, has to choose qualified applicants from many segments. Otherwise, the result will discourage those other segments from applying. And that in turn will make the U as a whole less economically viable and will also reduce their applicant pool of talent, which the U always seeks to make as wide as possible. </p>
<p>The way to get absolutely every Asian qualified as a STEM major into a (related) department/college of a particular U is to have fewer qualified Asians applying there, and/or fewer qualified segments of other backgrounds applying.</p>
<p>I think we ought to back up and analyze exactly what kind of “ramblings” we are talking about here.</p>
<p>As I recall it, which you are free to dispute, you attempted to dismiss the 0.33 odds ratio figure through shoddy mathematics and inappropriate counterexamples.</p>
<p>The “shoddy mathematics” was your arguing that the implication of accepting the 0.33 odds ratio as fact is believing that the “true [admissions] rate [of Asians] is around 60 percent.” In post 732, StillGreen demonstrated why that is not the case. To my knowledge, you never responded to that post.</p>
<p>The “inappropriate counterexamples” were your arguing that another implication of accepting the 0.33 odds ratio as fact is believing that scoring in the 1300-1399 range is not as good as scoring in the 1200-1299 range and that taking additional AP exams hurts one’s chances.</p>
<p>As I mentioned, none of these odds ratios is statistically significant at any conventional statistical level. Now, you balk by claiming that I misunderstand and misrepresent statistical significance. In fact, it is the other way around. You cannot cite odds ratios that were not statistically significant to “prove” that a consequence of accepting the 0.33 odds ratio is also accepting these. Espenshade’s presentation does not mention what the null hypothesized values of the odds ratios were, but your assertion that the values were zero is highly unlikely. A more likely null hypothesized value is one; that is, Espenshade was testing to see whether scoring higher or taking more AP exams affected one’s chances. The lack of statistical significance at any conventional level indicates that there was not evidence to conclude that “true” values of those odds ratios were not one; that is, the null hypothesis was not rejected in any of those cases. Terrible, terrible counterexamples.</p>
<p>Much thanks for the clarification. I need no conspiracies, however, as my response is simple: the results come from different models. The 0.33 odds ratio figure indirectly mentioned in the opening post comes from Model 5. Your bad counterexamples of the SAT scores and AP exam likewise came from Model 5. Now, your two new counterexamples come from Model 6. You didn’t disprove anything because I had never cited anything from Model 6. To borrow a phrase from Hunt, you cherry picked the data. You knew that nothing in Model 5 worked out for you, so you switched to Model 6. Bravo, bravo.</p>
<p>As I said, this is a red herring. Nobody is saying that race-neutral admissions will bless Asian applicants with 100% acceptance rates. You created this argument to divert from the true issue, which is race-neutral admissions resulting in higher Asian enrollment, though not so high as to create a “100% Asian” campus.</p>
<p>As written, I would not overly disagree, but there is a difference between making a distinction and making distinctions that matter. </p>
<p>Obviously the Ivies couldn’t take all the high school class valedictorians even if they limit that subset further to those with social skills and superior ECs. So, I’m not buying the premise that there are not a boatload of equally qualified/high qualified candidates (not to mention international candidates on top of that). Certainly I’m separating these from the “slam dunk” admits you mention. After that, I’d suggest that everyone falls into the category of ‘hit or miss’ or a decline. And let’s keep in mind that declines make it to the waitlist simply as to not to offend alums that write checks. </p>
<p>So, Dartmouth subjectively rates and color codes things. It certainly is a process but is it effective? For discussion purposes, Candidate A and B have all the same terrific classes, grades and test scores. Neither candidate has a major hook that makes their application a “slam dunk.” Candidate A has terrific and diverse ECs and Candidate B works 25 hours per week as a janitor in a school, no other ECs but adds that he likes to read books that interest him. Who is Dartmouth going to select?</p>
<p>Au contraire. You miss my point. I never claimed that you said that (“100%”) was the goal, or that K said that was the goal, either. I’m saying that’s a good goal!: to get everyone who is qualified to be accepted. Unfortunately, neither the mathematics nor the economics of the situation support that indeed lofty goal. Just getting “a few more” of any particular segment accepted does not seem to square with the concept of “justice” and “equality” that many of you argue for here. “Higher” enrollment still means that many qualified are left out. In a “pure” (ideal) sense, college admissions is not universally “fair.” (And I’ve never denied that!) </p>
<p>It is always my goal to get all my students – of whatever background – into the highest level of education they seek and are capable of doing, which is why I encourage both reaches and non-reaches, so that they will get admitted to that highest possible level. To do that, I have to apply some mathematics to the effort.</p>
<p>OK, my apologies, but I just want this to be absolutely clear: I’ve never argued in favor of the goal you are speaking of. That’s a goal that you and only you have referred to. I don’t support race-neutral admissions because I think it will “get everyone who is qualified to be accepted [to a particular elite university].” I support it because I believe race is not a relevant factor for participation in any aspect of university life and because evidence shows that race-neutral admissions benefits Asians. I add, however, that out of principle, I would support it even if it reduced Asian enrollment.</p>
<p>Ultimately, the problems facing this discussion are threefold: (1) lack of information, (2) differing fundamental philosophies, and (3) a belief held by some that “I don’t buy it” is as strong a rebuttal as “Here is research by X that casts doubt on research by Y.”</p>
<p>The first problem highlights once again why Jian Li’s civil rights complaint is so important. Hopefully, it can shed light by adding much needed information to a conversation that is partially based on accepting at face value whatever public relations personnel say.</p>
<p>The second problem is also important. At heart, whether one supports racial preferences depends on which philosophy one subscribes to. Some agree with Justice Blackmun that “…in order to treat some persons equally, we must treat them differently.” Others agree with Chief Justice Roberts that “[t]he way to stop discrimination on the basis of race is to stop discriminating on the basis of race.” People who believe in the former tend to think the latter is oversimplified, and people who believe in the latter tend to think the former contradicts itself. It’s a value judgment.</p>
<p>The third is actually a bit bizarre. I am shocked that so many well-educated people seem to believe that “I think the research you listed is lousy” is as convincing as providing research that finds contrary evidence. It’s not. At best, it’s skepticism, but at worst, it’s hubris.</p>
It’s my hypothesis that potential STEM majors iin general, across races, are likely to have, on average, better stats than people looking at other majors. I don’t really have any proof of this, though.</p>
<p>
Of course not. But remember the size of the disparity from Espenshade. A sizable chunk of it, if not all of it, could be explained by this factor. When you add it some of the other “diversity” factors that probably disadvantage Asians (such as geographical diversity), even more of it might be explained.</p>
<p>And here’s another thing to chew on. Look again at the Michigan data: <a href=“Office of Budget and Planning”>Office of Budget and Planning. Except for African Americans, the number of males and females in each ethnic group is pretty balanced. Is that being done deliberately by the college? What impact, if any, does that have on what we’re talking about? Consider the following: If Asian males are more focused on STEM majors than Asian females, is the number of Asian females being artificially restricted so they won’t outnumber Asian males?</p>
<p><a href=“3”>quote=fabrizio</a> a belief held by some that “I don’t buy it” is as strong a rebuttal as “Here is research by X that casts doubt on research by Y.”
[/quote]
Seems like Espenshade himself may not buy it.</p>
<p>Your point being? The type of argument you’re using reminds me of the creationist ploy, “Darwin himself recanted on his deathbed!” It doesn’t matter what the researcher’s opinion is; what matters are the findings. It has been five years since Espenshade first published on this topic, and four years since his highly controversial finding of “a loss equivalent to 50 SAT points” for Asian applicants. Many people have dismissed his research with a “I don’t buy it” for a simple reason: they are utterly unable to produce any research that provides contrary evidence.</p>
<p>And even then, if you want to quote him, present both sides.</p>
<p>
</p>
<p>In this thread, some have argued that it does not matter that there are no papers providing contrary evidence because the standards for publication in social science are supposedly “low.” Such a statement, however, is self-defeating; if the standards are so low, why haven’t these people published papers highlighting the so-called “obvious” flaws of Espenshade’s research?</p>
<p>Edit</p>
<p>Let’s take a look at Dr. Richard Sander’s “mismatch hypothesis” and compare it to Espenshade and Chung’s research. Sander’s paper has, in fact, been the subject of numerous responses that have tried to explain why his hypothesis is wrong. In turn, Sander has addressed these criticisms.</p>
<p>Where are the responses to Espenshade and Chung’s research?</p>
<p>Here’s a more complete summary of the Michigan information. Below, by category are number of students, number of STEM majors, and percentage. Again, I made my own determination of what was or was not a STEM major. (i.e., oceanography yes, psychology no.) Reasonable minds can disagree on the categories.</p>
<p>It seems to me that the unknowns are numerous enough to skew the results if their distribution is different from the identified distribution. Also, how do the internationals figure into this. If, for example, there was a higher percentage of Asians in that group than Asian-Americans in the citizen group, what would that mean? It could be that the school is, in fact, controlling the number of Asians, and is counting international Asians toward the total. On the other hand, this group is the most focused on STEM majors, and thus would put more pressure on Asian-Americans if they are competing for those STEM slots more than other groups are.</p>
<p>It’s not that Espenshade’s research is flawed, but rather that the results allow for more than one interpretation. That’s what Espenshade himself is saying in the quote mokusatsu put up. Nobody is saying that Espenshade made a mistake, and that there really was no disparity between Asian stats and admissions; the dispute here is what the cause of the disparity is. Espenshade’s results don’t tell you that. It’s obviously pretty difficult to get the kind of data that Espenshade got, much less more detailed data on interview and essay evaluations, etc. In the Duke mismatch study, it doesn’t appear that they corrected for intended major choice, or for other factors that could impact admissions. So even there, it’s really hard to know what you are comparing. And that was only for one school, Duke, which may or may not be representative of the schools we are talking about. The less data there are, the more hypothesis are likely to be available to explain the results. That’s why more data are needed.</p>
If all knowledge intersects in infinity as I believe, then I know I am at least moving in the right direction. </p>
</p>