Which for all we know could just be correlation, not causation. Especially since they are considering so few variables. Second, showing a relationship right up to 2400 doesn’t mean the marginal utility doesn’t drop as you go up the scale. In fact, that would make sense given that the SAT is a scaled scoring system.
As far as anecdotal evidence, you can look no further than Mr. Jian Li. If the marginal utility of great scores didn’t decrease, there would be little chance that he’d be rejected by 5 schools given that his scores were far higher than the average person admitted. Furthermore, this flies in the face of all the evidence we have available to us, and the public statements of many schools.
Lastly, and this really needed to be saved for last. We have the words of the author himself. Basically saying exactly what I said. To quote him:
Wow, I wish someone had said those things before. Although I am sure that now you’ll tell me he doesn’t know his own research.
Not invalid, less reliable. You keep hanging your hat on this statistic when at the very most, it gives up a snap shot of what was happening to applicants at 3 elite schools in 1997. To assume that this applies generally, or is still happening today is not justifiable. This was one study. I don’t think you should pretend like it couldn’t possibly be wrong.
Actually, it is math. More importantly, social science and math are not mutually exclusive. That said, I find it odd that two academics came to two different conclusions based on the data, yet you can’t imagine anything else questionable about the study.
No, all of it is not. Many would not deign to draw such conclusions without analyzing more than one year’s worth of data. How comfortable would you be trusting meteorologists who only looked at the past year’s data in their predictions? Honestly, it’s just ridiculous that you can’t admit how flimsy the evidence you are presenting is. It doesn’t necessarily mean you are wrong, just that your study is really, really unconvincing.
No, I am saying that one study, using one year’s data, from three (or 8 according to the interview) schools, with a handful of metrics, does not result in a convincing conclusion. Put it this way. If their model works so well, why don’t they sell it. It costs hundreds of dollars to apply to all these schools. If Espenshade could tell a student like Li who applied to 9 school with any kind of confidence where he was gonna be admitted, he could make a killing. Moreover, if such a model can be created by any scientist, why hasn’t someone done that by now? People make millions predicting the weather, why hasn’t anyone sold admissions models if it can easily be predicted?
They do what by year? What do they do by race? Admit people?
If that is your position, then you seem to be at odd with Kidder and the data. He is saying that the post-AA rates of Asians at law schools trails that of the post race-blind rates of Asians at the undergraduate level, and that that disparity is because of negative action. So are you saying there is/was negative action against Asians at law schools or not?
Secondly, you didn’t answer my question about how comparing CA college to CA law schools presumably subject to the same race-blind restrictions would help in isolating the effect of negative action.
Huh? You realize Espenshade is for AA, right? I don’t think he is trying to gather support to repeal anything. Second, isn’t that the entire point Kidder is making that that the projections Espenshade made didn’t pan out at the law school level? Since Kidder assumes there is no negative action, the modest gains by Asians in law school once AA was ended, compared to the significant gains after they went race-blind at the undergrad level is evidence that there was negative action, no?
Well, seeing as all these schools are getting money from the government, and they are likely doing something illegal, meaning that there would be plenty of plaintiffs, I am sure some enterprising lawyer could make it financially advantageous to a whistle blower.
What are you referring to?
Which doesn’t mean much. Applications should theoretically track the number of prospective candidates. Since there are far more Whites out there, you would expect they would apply more often absent some other explanation or factor.
Multiple studies examining multiple years of data. Insiders commenting on the process. What would it take to convince you it isn’t happening?
First, you need to acknowledge the basis of his argument is that negative action pales in comparison to the affect of AA on Asians. Second, I disagree with your parsing of the lawsuit. He is alleging that affirmative action is being used to help under-represented minorities at his expense. By using Espenshade’s data, he argues that since 5 of every 6 spots that went to minorities would go to Asians, he would have gotten in absent those policies.
This is a dumb lawsuit for a few reasons. First, the court already ruled racial preference could be used in non “mechanistic” ways to promote diversity. Given that standard, it is plainly obvious that in a relatively zero-sum situation, being Asian, as opposed to Native American (for example) lowers his chances. That is obvious, and not worthy of a lawsuit. Second, his argument has to hinge on the academic discrepancies between those admitted, specifically under-represented minorities, and him. He would say, race must be a factor given that my score crush their scores. But, that argument holds against other Asians as well as those possibly admitted as a result of AA. It’s hard to argue you were rejected because you were Asian, and that less qualified minorities got in in your place when other Asians also did. He would also need to demonstrate that those metrics he is arguing are relevant are the basis of admissions decisions.
You say peer-reviewed like that means it’s factually accurate and beyond reproach. The point of linking to the testimony of people who KNOW the guy is that they could testify to his motives and to the context of the situation. Given that so many of the people, who have a far better perspective of the situation than either of us, think he’s a sore loser, I don’t know why you are so convinced he is a martyr.
Yes, they disagree.
That was worded awkwardly. I meant before and after AA.
Then why would that refute anything Espenshade said? The argument, as far I can see, wasn’t that once AA ended, Asians would take all those spots. It was that given the scoring disparities and other specifics of the elite universities we studied, at the undergraduate level, Asians would be poised to take most of those spots. Please feel free to correct me if you think this is wrong.