In its continuing efforts to keep the public informed about the ongoing admissions litigation, the University of Michigan makes these transcripts of the trial proceedings in Grutter v Bollinger, et al., Civil Action No. 97-75928 (E.D. Mich.), available to the University community and general public. As is often the case with transcription, some words or phrases may be misspelled or simply incorrect. The University makes no representation as to the accuracy of the transcripts.




                                                                     1

             1                    UNITED STATES DISTRICT COURT
                                  EASTERN DISTRICT OF MICHIGAN
             2                         SOUTHERN DIVISION

             3

             4  BARBARA GRUTTER,
                For herself and all others
             5  Similarly situated,

             6                 Plaintiff,

             7       v.                                    Civil Action
                                                           No. 97-CV-75928
             8  LEE BOLLINGER, JEFFREY LEHMAN,
                DENNIS SHIELDS, and REGENTS OF 
             9  THE UNIVERSITY OF MICHIGAN,

            10                 Defendants.
                _________________________________________/
            11

            12                      BENCH TRIAL - VOLUME 13
                                                
            13
                                  MONDAY, FEBRUARY 12TH, 2001
            14

            15               BEFORE THE HONORABLE BERNARD FRIEDMAN
                                  United States District Judge
            16              Theodore Levin United States Courthouse
                             231 West Lafayette Boulevard, Room 238
            17                         Detroit, Michigan

            18                             -   -   -

            19  Appearances:

            20
                           Kirk O. Kolbo, Esq.,
            21             R. Lawrence Purdy, Esq.,

            22   On behalf of the Plaintiff,

            23
                           John Payton, Esq.,
            24             Craig Goldblatt, Esq.,
                           Stuart Delery, Esq.,
            25
                 On behalf of the Defendants Bollinger, et al,










                                                                     2

             1
                                           -   -   -
             2
                 APPEARANCES (Continued):
             3

             4                George B. Washington, Esq.
                              Miranda K. S. Massie, Esq.
             5
                 On behalf of Intervening Defendants.
             6

             7

             8

             9

            10

            11

            12

            13

            14

            15

            16

            17

            18

            19

            20              Joan L. Morgan, Official Court Reporter

            21         Proceedings recorded by mechanical stenography.  
                      Transcript produced by computer-aided transcription.
            22

            23

            24

            25











                                                                     3

             1

             2                           I  N  D  E  X

             3   WITNESS:                                       PAGE:

             4   STEPHEN RAUDENBUSH

             5   Direct Examination by Mr. Delery                 6
                 Cross-Examination by Mr. Kolbo                  24
             6
                 FRANK WU
             7
                 Direct Examination by Ms. Massie                36
             8   Cross-Examination by Mr. Payton                 88
                 Cross-Examination by Mr. Purdy                  99
             9
                 FAITH SMITH
            10
                 Direct Examination by Ms. Massie               153
            11

            12

            13                               E  X  H  I  B  I  T  S

            14                                             RECEIVED

            15  Trial Exhibits Nos. 226, 227                   4
                 Trial Exhibit No. 175                        41
            16   Trial Exhibit No. 171                       178
                 Trial Exhibit Nos. 202-210                  179
            17

            18

            19

            20

            21

            22

            23

            24

            25



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             1

             2             Detroit, Michigan

             3                  Detroit, Michigan

             4                  Monday, February 12th, 2001

             5                  9:40 a.m.

             6                             -   -   -

             7             THE COURT:  I'm sorry I'm late.  I had an

             8   Immigration Swearing In.  I wasn't going to read the names,

             9   but I ended up having to read all the names.  Stephen did it

            10   for me.  He told me on the way back he now knows why on Ellis

            11   Island people's names are changed after he had to read all the

            12   names.  I apologize. I'm sorry I'm late.

            13             Okay, ready to roll?

            14             MR. KOLBO:  Your Honor, just briefly a couple of

            15   things.  We looked at things again this weekend, and decided

            16   that in view of the trial -- in the interest of assuring that

            17   we get finished here this week, we have withdrawn Gail Heriot

            18   as a witness.  I've informed counsel of that last evening so

            19   they are aware of that as well.

            20             THE COURT:  Okay.

            21             MR. KOLBO:  The other thing is, your Honor, we have

            22   taken care of the drawings of Professor Larntz's larger

            23   drawing.  I've shown that to counsel.  I believe there are no

            24   objections to it.  At this time we would offer Exhibit 226 and

            25   227.



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             1             THE COURT:  Both of them are saying yes so we'll

             2   accept them in that form?

             3             MR. KOLBO:  Yes, and I have two copies here.

             4             THE COURT:  Great.  I appreciate it.

             5             MR. KOLBO:  And your Honor, we will -- I think you

             6   indicated you would like someone to take custody of the actual

             7   large drawing and we would be happy to do that.

             8             THE COURT:  That's great.  Perfect.  Okay.

             9             MS. MASSIE:  Good morning, Judge.  Just a couple

            10   scheduling things. In all the shifting that's happened around

            11   today and tomorrow, we have two inefficiencies that I

            12   apologize for.  One is that our two witnesses for today won't

            13   be getting in probably in time to testify until about

            14   something like 11:00 or even 11:15.  I apologize for that.

            15   And the second thing is we don't have any witnesses who can

            16   testify tomorrow afternoon.  As it happened we filled up today

            17   -- anyway I won't go into all the logistics --

            18             THE COURT:  No problem.

            19             MS. MASSIE:  But we should without any question be

            20   done with the testimony by Thursday.

            21             THE COURT:  You have no witnesses this morning?

            22             MS. MASSIE:  This morning we do, but we may have to

            23   take a break after Professor Raudenbush.  In other words,

            24   before our people get here --

            25             THE COURT:  Not a problem.  And then tomorrow



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             1   everybody agrees we won't go at two, or any other time

             2   tomorrow?

             3             MS. MASSIE:  Correct.

             4             THE COURT:  And Wednesday we'll be off.  And then

             5   we'll go Thursday, and we'll finish up with Closing Arguments

             6   Friday?

             7             MS. MASSIE:  Right.

             8             THE COURT:  Good.

             9             MS. MASSIE:  Great.

            10             THE COURT:  It will work out perfect.

            11             Are we going to recall --

            12             MR. DELERY:  Yes, your Honor.  It will be very --

            13             THE COURT:  It can't too much.

            14             MR. DELERY:  It will be brief and expeditious.

            15             The defendants call Professor Stephen Raudenbush.

            16             THE COURT:  I know you've been sworn once but we've

            17   been re-swearing the witnesses.

            18             Do you solemnly swear or affirm to tell the truth in

            19   the matter now pending before this Court?

            20             THE WITNESS:  I do.

            21             THE COURT:  Please have a seat.

            22                S T E P H E N    R A U D E N B U S H ,

            23        being first duly sworn by the Court to tell the truth, was 
examined

            24  and testified upon his oath as follows:

            25                         DIRECT EXAMINATION



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             1  BY MR. DELERY:

             2   Q    Good morning, Professor Raudenbush.

             3   A    Good morning.

             4   Q    You were here on Saturday for Dr. Larntz's rebuttal

             5  testimony; is that right?

             6   A    Yes, I was.

             7   Q    I'd like to talk about the main points that he raised on

             8  Saturday, just on Saturday.  And I think I'm just going to take

             9  them in the order that he raised them on Saturday.  The first

            10  thing he did was present a new chart that compared odd ratios

            11  to probabilities for various baseline probabilities; do you

            12  remember that?

            13   A    Yes, I do.

            14             MR. DELERY:  And, your Honor, this is the last page

            15   of Exhibit 225.

            16  BY MR. DELERY:

            17   Q    Does that chart as you remember it satisfy your

            18  criticisms about the difficulty of interpreting global or

            19  composite odds ratio?

            20   A    No, it doesn't.  As I've testified and as that table

            21  shows the practical meeting of an odds ratio depends on the

            22  baseline probability, and as we know, the baseline

            23  probabilities depend on the grades and test scores of the

            24  students.  What I've also found in my work is that the odds

            25  ratios themselves depend substantially on the grades and test



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             1  scores of the students.  So when both the odds ratios

             2  themselves vary as a function of those things and the meaning

             3  of the odds ratios varies as a function of grades and test

             4  scores it becomes exceedingly difficult to make a practical

             5  interpretation of the global or composite odds ratio.

             6   Q    The second topic or the second issue that Dr. Larntz

             7  addressed on Saturday was the excluded data and he presented

             8  charts, versions of the grids that he had highlighted in

             9  yellow, the cells that included data in his composite odds

            10  ratios calculations and the non highlighted cells or cells that

            11  did not contribute information to that calculation; do you

            12  recall that testimony?

            13   A    Yes, I do.

            14   Q    Now, in part of that discussion Dr. Larntz indicated that

            15  he believed that the amount data, in other words, the number of

            16  applicants in the non highlighted cells, the amount of data

            17  that had been excluded was really irrelevant to interpreting

            18  his results; do you recall that?

            19   A    Yes, I do.

            20   Q    Do you agree with that?

            21   A    I strongly disagree with that.  In fact, I would say that

            22  the amount of excluded data can be more informative than the

            23  odds ratio itself in his analysis.

            24   Q    Why is that?

            25   A    Well, in order to explain why that's true, I'd like to



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             1  present just a simple example if the Court's permission.

             2  Simple.

             3   Q    Would you like to draw it?

             4             THE WITNESS:  Could I?

             5             THE COURT:  Sure.

             6   A    In this example, we have a law school that bases its

             7  admissions decisions on just two factors:  Test scores and

             8  race.  So what I would like to do, I'll just draw a number line

             9  that gives the possible values of test scores.  They start at

            10  one twenty and they go to one eighty.

            11             Now, in this law school, starting at one eighty at

            12   the top, everyone is admitted without regard to race until we

            13   reach a certain point that I'm going to call a cut point.  At

            14   that point we find candidates who are sitting right on the

            15   border of that cut point, some of whom are minority, and some

            16   are majority, and the policy is: Admit all minorities, and

            17   some majorities.  Below that cut point, all candidates

            18   regardless of race are rejected.  So this is the reject area,

            19   and this is the admit area.   

            20             Now, what I would like to do is contrast that law

            21   school with a second law school that also uses just test

            22   scores and race in making admissions decisions.  I'll draw the

            23   same number line.  This law school has a very, very different

            24   policy.  Starting at the top it admits all minority

            25   candidates.  And it maintains that policy until we get down to



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             1   the very, very lowest possible test scores.  So in this area,

             2   admit all minorities, and admit some majorities.

             3             Now, I think we would agree that in both law schools

             4   race is taken into account in admissions.  However, the extent

             5   to which it is taken into account is tremendously different.

             6   It is a very modest extent only at the very border that could

             7   possibly have an effect, whereas in the second law school, law

             8   school number two, it has a much -- it's taken into account a

             9   great deal more because of what we see here, that all

            10   candidates in this very wide range where minorities are

            11   automatically admitted.

            12             Now the question is if we apply Professor Larntz's

            13   methodology can we discern the difference between these two

            14   law schools?  If we apply that methodology what will happen in

            15   the case of law school number one is that all of the data

            16   except at the border --

            17             THE COURT:  But see some of your premises -- in the

            18   first one, it says admit all minorities at that point.  The

            19   second one says all minorities at a different point; isn't

            20   that what you're saying?

            21             THE WITNESS:  In this one here, your Honor?

            22             THE COURT:  Right -- no, that one first.  All

            23   minorities at that point.

            24             THE WITNESS:  Yes, just in that border.  Just in

            25   that little area --



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             1             THE COURT:  The second one says, admit all

             2   minorities throughout the whole --

             3             THE WITNESS:  Except unless the grade --

             4             THE COURT:  The reason -- and I want to hear what

             5   you have to say, but that's not what happened here.  The

             6   University of Michigan takes the position we don't admit all

             7   of the -- all of them.

             8             THE WITNESS:  Right, I agree.

             9             But what I want to show is here's a case where we

            10   have all the relevant information.  There's no missing

            11   information.  We know the test scores, we know the race.  Can

            12   this methodology reveal the extent to which race is taken into

            13   account in this simple situation.  If it can't, how can we

            14   except that methodology to reveal the extent to which it's

            15   taken into account in a much more complex situation --

            16             THE COURT:  Explain it to me because --

            17             THE WITNESS:  So what will happen is -- using

            18   Professor Larntz's methodology, all of the candidates in this

            19   -- where they are all rejected and all of the candidates here,

            20   where all are admitted, will be discarded because they have

            21   the same admissions decision regardless of race.  They provide

            22   in his words, no comparative information. The odds ratio will

            23   be computed simply for this group where there is, in fact, a

            24   difference, where some people are being admitted.  And what he

            25   would find would be an infinite odds ratio in this case.



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             1            Now, when we go down to the second law school, what

             2   would happen is there is only a small fraction of the data

             3   that would actually that would actually be discarded because

             4   here is the small area where everyone is rejected regardless

             5   of race.  Admits and rejects are occurring in this area.  This

             6   would have -- this area, here, would have the "comparative

             7   information" in his words.  We would compute the odds ratio

             8   and we would find an infinite odds ratio.

             9             In both cases, we would find an infinite odds ratio.

            10   What would actually be far more revealing about these cases is

            11   the fraction of information discarded.  The fact that

            12   virtually all of the data is discarded in case number one

            13   reflects the fact that this policy in case number one applies

            14   to very few students.  Race has no effect on these decisions.

            15   It has no effect on these decisions, they're discarded.

            16             THE COURT:  How about -- see -- I understand what

            17   you're saying, but his whole theory was to what extent is race

            18   because the University of Michigan takes a position that it's

            19   very little, you know, it's not a trump card in the words of

            20   Mr. Payton several times.  And so this we know it's not very

            21   little. We know that race is a predominant factor in making

            22   decisions.  So his analysis is different than your analysis.

            23             THE WITNESS:  Well, in these two cases, simplified

            24   as they are, we have all the knowledge we need. Race is taken

            25   into account, I would say, very little in this first school.



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             1   Only if you're at the very border --

             2             THE COURT:  We don't need a statistician to tell us

             3   that because they've already told us that.  One of your

             4   premises is that race is taken into consideration as a major

             5   factor.

             6             THE WITNESS:  Right.  See, here's the way we

             7   evaluate a methodology.  We set up a simple situation where we

             8   know the truth.  We have all the relevant information, and we

             9   evaluate the capacity of the methodology to answer -- to

            10   discover the what we know.

            11             THE COURT:  I'll never be able to discuss it on your

            12   level.  I'm discussing it as a layperson who's never taken a

            13   statistic class.  But I do know that -- just by listening to

            14   Dr. Larntz, and I'm not arguing his position, I'm not saying

            15   it's good or bad, what I'm saying is the premise is different

            16   because he is trying to figure out to what extent is race

            17   taken into consideration.  And in your analysis here we know

            18   to what it's taken into consideration.  So we're not comparing

            19   apples to apples.

            20             THE WITNESS:  Well, what I'm showing you here, what

            21   I'm trying to argue here is that his analysis cannot reveal,

            22   the odds ratio cannot reveal the extent to which race is taken

            23   into account because it can't discriminate between two cases.

            24   In the first case it's taken into account very little.  In the

            25   second case, it's taken into account an enormous amount. And



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             1   in both cases the odds ratios are the same.  And what is

             2   actually far more relevant to the evaluation of these two

             3   cases is the fraction of data that he would discard.

             4             THE COURT:  Okay.

             5  BY MR. DELERY:

             6   Q    How does that, Professor Raudenbush, tie back to the

             7  highlighted grids that Dr. Larntz had here on Saturday?

             8   A    Well, obviously the Michigan case is more complicated,

             9  but in the highlighted grid a large fraction of the cases,

            10  especially a large fraction of the minority cases, were

            11  discarded.

            12             Those are cases where the admissions decision is

            13   being made without respect to race.  The fact that so many

            14   candidates, forty percent, are having decisions made that

            15   don't take into account their race is very relevant to the

            16   issues in this case.

            17   Q    Is the approach that you just took here in terms of

            18  setting out two simplified hypothetical cases using that to

            19  evaluate a methodology, is that a standard practice in your

            20  field?

            21   A    That's the standard practice. To evaluate a methodology

            22  we need to know whether it can recover the distinctions that

            23  are important when we know what the truth is.  If it can't do

            24  it then, you can't discover the reality when we know the

            25  reality and when we have all available information, we can't



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             1  expect that methodology to give us the answer about the extent

             2  o which race is taken into account in a much more complexed

             3  situation where we don't know the information. It's not going

             4  to work better when we have less information.

             5   Q    Why don't you take the stand again, Professor Raudenbush.

             6  And -- I guess just one final question before we move onto the

             7  next topic, and that is, did Dr. Larntz's testimony on Saturday

             8  about the excluded data and the highlighted charts, does that

             9  change your opinions at all concerning the excluded data issues

            10  that you've discussed --

            11   A    No, actually, sitting and thinking about it, actually

            12  during the testimony it made it even more clear to me how

            13  important this excluded data actually is in looking at his

            14  results.

            15   Q    Okay. Let's move now to the third issue from Saturday,

            16  and it's related to the issues of assumptions. On Saturday, Dr.

            17  Larntz said that he thought an analysis that used all of the

            18  data, that didn't exclude any of the data, would have to be

            19  based on a model with more assumptions than his was. Do you

            20  think that's right?

            21   A    It depends strongly on what the broad methodological

            22  goals of the analysis are.  In my analysis where I was

            23  assessing the causal impact of the policy of taking race into

            24  account the issue of discarding data simply didn't arise.  Just

            25  referring back to this case, my methodology would attempt to



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             1  predict the probability of admission for everyone in law

             2  school, number one, based strictly on test scores, and to see

             3  how closely those predictions correspond to what actually

             4  happened in practice, and we would find that they correspond

             5  very closely, where as in the second case, they would not

             6  correspond closely so I would argue that my methodology could

             7  sharply distinguish between these two cases.  The issue of

             8  discarding data just doesn't come up when that's the goal.  We

             9  use standard methods, and we don't need to discard data.

            10   Q    Do you think that Dr. Larntz made fewer assumptions than

            11  you do?

            12   A    Well, I wouldn't necessarily say that he made fewer or

            13  more.  We all have to make assumptions when we do statistical

            14  analyzes.  What we need to do is to be as explicit about what

            15  those assumptions are, to whenever we cann to test the validity

            16  of those assumptions and then to evaluate the possible impact

            17  of those assumptions on our results.  My criticism -- or one of

            18  my criticisms, I should say of Professor Larntz's analysis is

            19  that -- he makes a very strong assumption, namely, that the

            20  same global odds ratio applies to everyone regardless of grades

            21  and test scores.  And I actually did a series of analyzes to

            22  assess that, and I found that assumption not to be tenable.

            23  And I believe, and I think he would disagree that the impact of

            24  that could be important in this case.

            25   Q    On that last point I think Dr. Larntz did say on Saturday



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             1  that he thought that while the assumption might not technically

             2  be true, the assumption of a uniform odds ratio might not be

             3  technically be true, it wasn't important to evaluating his

             4  results; do you disagree with that?

             5   A    Well, I disagree, and I think I could represent why I

             6  disagree if we could just briefly refer to the chart that we

             7  had on Saturday.

             8   Q    Dr. Larntz's chart?

             9   A    Dr. Larntz's chart, yes.

            10   Q    Okay.  This is Exhibit 226.

            11   A    What this chart was really building up -- maybe I need to

            12  get up because I can't see it --

            13             THE COURT:  You may.

            14             MR. DELERY:  Can you see it, your Honor.

            15             THE COURT:  I'm fine.

            16             MR. DELERY:  Okay.  Thanks.

            17   A    Is that the lower bounds of these constant variables for

            18  the odds ratios are large numbers.  And I think that was really

            19  the crucial point.  If that assumption is false, that is, if

            20  the offs ratios vary as a function of where you with respect to

            21  grades and test scores, then for some students and possibly

            22  many students these lower boundaries should be much lower than

            23  these numbers.  And that in a practical sense is probably the

            24  key potential problem.

            25             THE COURT:  When you say "much lower" could they



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             1   have used that in the figuring?

             2             THE WITNESS:  Well, I have -- in the analysis I did,

             3   I did some inspection.  Yes, there are certainly cases where

             4   these are much, much lower than these.

             5             THE COURT:  When you say "much" give me a relative

             6   figure.

             7             THE WITNESS:  Okay, in one analysis I did, the

             8   average odds ratio was twelve.  But in my analysis I also

             9   estimated how much the odds ratio --

            10             THE COURT:  You used a different methodology.

            11             THE WITNESS:  I used a different methodology.

            12             THE COURT:  Again, comparing apples to oranges.

            13             THE WITNESS:  It only makes one -- it only really

            14   has one really important difference and that is it allows the

            15   odds ratios to vary over the cells of the table just.  It's

            16   still a logistic regression.  It introduces that possibility

            17   that the odds ratio would not be invariant across the cells of

            18   the table.

            19  BY MR. DELERY:

            20   Q    And using that method -- I'm sorry, I'm sure that you

            21  finished --

            22   A    Oh, yeah, so while the odds ratio was twelve, the

            23  standard deviation of the log odds was about one, and that

            24  leads to odds ratios that are much smaller than twelve, even as

            25  small as one and two.



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             1             THE WITNESS:  Now, I didn't highlight that, your

             2   Honor, because as you can tell I'm not really buying into the

             3   idea of using the odds ratio to --

             4             THE COURT:  I understand that.  You made that very

             5   clear.

             6             THE WITNESS:  I just to make sure.  I really was

             7   just doing it evaluate his assumptions.

             8  BY MR. DELERY:

             9   Q    Let's go now, Dr. Raudenbush, to the last of the major

            10  issues from Saturday and that was the stability of the odds

            11  ratios across the years.  On Saturday, Dr. Larntz said that he

            12  thought that your concern about instability across the years

            13  might be due to a computational error that you had made. Do you

            14  remember that?

            15   A    I do remember that.

            16   Q    Was he right?

            17   A    Well, actually on Saturday, he solved a puzzle that has

            18  been in my mind for some time.  As he pointed out the standard

            19  output for a logistic regression analysis includes regression

            20  co-efficient which is in a log metric, a standard error, and

            21  then what we call a Z test which is a test of significance.  I

            22  had been confused by his reports because his reports were a

            23  little bit non standard.  They had an odds ratio, and then

            24  another column that was labeled "standard deviation."

            25             Now, it certainly would be possible to compute for



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             1   each odds ratio a standard error in the metric of the odds

             2   ratio. It would not be conventional and it would not be the

             3   optimal way to proceed, but it could be done.  And I wasn't

             4   sure whether he had used that method or the more standard

             5   method from the results of his report.  So I asked you to

             6   pursue this issue in the deposition of Professor Larntz.  I

             7   mean, this is a very different situation from how we usually

             8   operate.  In our profession we would simply ask each other

             9   these questions, but in an adversarial thing, I have to try to

            10   get you to find out the answer. So I read the deposition, and

            11   my reading of the deposition suggested to me that he was

            12   actually using the odds ratios and the standard errors in that

            13   metric.  And on Saturday, he made it very clear he was not

            14   doing that.  So I was actually under a false -- operating

            15   under a false assumption as to what he was actually doing.

            16             What I was able to do then, now that I could see how

            17   he actually operated in the log odds metric, is to recompute

            18   the stability, a test of stability using a very simple test.

            19   I would be happy to show you how it's computed.  It can be

            20   done on a calculator.  It would take about fifteen minutes,

            21   but -- it wouldn't take fifteen minutes to explain it, but it

            22   would take maybe fifteen minutes on a calculator. It's a very

            23   simple procedure.  I think it would be useful to just tell you

            24   what the result is --

            25   Q    Yes.



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             1   A    It's a Chi square test of homogeneity very commonly used

             2  in this area.  And the Chi square value I computed was 22.9.

             3  The probability associated with that was less than .001.

             4   Q    And that's the P value?

             5   A    That's the P value.  And what that says is that there is

             6  statistically very significant heterogeneity across the years

             7  in the log odds ratios which is rather than the odds ratios

             8  themselves.

             9   Q    From that what do you conclude about your earlier

            10  criticism concerning the instability of the odds ratios?

            11   A    I remained concerned about the instability for the

            12  following reason:  When we look at the process of admissions,

            13  it seems to be stable. When we look at the average

            14  probabilities of admission, they're stable.  The results are

            15  bi-causal analysis, year-to-year, in the exhibits, in my own

            16  testimony.  If you review those you'll see the results are

            17  stabling. We see here quite significant heterogeneity and we

            18  also see very significant heterogeneity across the models that

            19  are also in the exhibit of my testimony.  And what worries me

            20  is when we see heterogeneity in a model, when we don't see it

            21  in more basic summaries of the data is that something is going

            22  on in the methodology that is creating or perhaps identifying

            23  the instability.

            24   Q    Okay.  When you were here last month -- a few weeks ago

            25  -- you talked about something called the standard error or the



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             1  difference between -- through the odds ratios is what I'm

             2  talking about the instability -- and not a test of homogeneity

             3  that you just mentioned.  Why did you use the other one then

             4  and this one then?

             5   A    Well, it's much easier to explain if I have two numbers

             6  asked, are these numbers different than it is to explain the

             7  test of homogeneity, and I thought that would be a useful way

             8  to go.  But the test of homogeneity is the better test because

             9  it doesn't -- Professor Larntz made the point when you select a

            10  big difference from a whole set of possible differences it you

            11  have -- it's hard to get -- you have to be careful to get the

            12  right P value.  And so to simply test the homogeneity across

            13  the six years is a more straightforward statistical way of

            14  doing this although it's more difficult to explain.

            15   Q    And you reached the same bottom line conclusion both ways

            16  is that correct?

            17   A    Yes, I did.

            18   Q    Okay. Well, Professor Raudenbush, I want to ask you just

            19  one final question:  We've heard this testimony back and forth

            20  between you and Dr. Larntz, and my question is:  Based on your

            21  twenty-five years as an educational statistician and having now

            22  heard the rebuttal testimony in your view is there a way to

            23  make a sense of the areas of real dispute you and the

            24  significance of those areas?

            25   A    Well, let me try to summarize the disagreements as I see



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             1  them. We both would agree that there is an association between

             2  race and admissions controlling for test scores and grades.

             3  And that finding would not be surprising given the stated

             4  policy of the law school which does take race into account.  We

             5  would disagree about the extent to which that relationship

             6  varies as a function of grades and test scores and we would

             7  seemingly disagree on how important that variation is.  We

             8  would disagree about the instability of the results that we've

             9  just described or the importance of that.  Those in my view,

            10  however, would be secondary disagreements in my view. The key

            11  disagreement is the one we've discussed earlier.  From a broad

            12  methodological point of view I am convinced that one cannot

            13  compute odds ratios that will reveal the extent to which race

            14  is taken into account in admissions. And I did say that in my

            15  testimony.  I think in statistics we have to do what we can do

            16  and limit what we do to what we really think we can do.  And

            17  what I did -- what I think we can do is give an assessment of

            18  the impact of the policy on those who apply.  What's far more

            19  difficult to do from a statistical point of view than is to

            20  understand the process, the causal process, the process is

            21  cognitive process in the admissions office that generate that

            22  impact. So we can access the impact, but to say what extent

            23  it's taken into account requires what we know more about the

            24  process than we actually know.  And that's really the key

            25  disagreement.



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             1   Q    And in your view do you have any doubt as to what the

             2  correct answer is?

             3   A    Well, I think I've made it clear that I am convinced that

             4  we cannot use the statistical data and certainly not the odds

             5  ratio to reveal in this case the extent to which race is taken

             6  into account, but we can with -- with an amount of uncertainty

             7  -- there is some uncertainty that I have tried to quantified,

             8  we can access the causal impact of the policy.

             9             MR. DELERY:  I no further questions, your Honor.

            10             THE COURT:  Intervenors, any questions?

            11             MS. MASSIE:  No.

            12             THE COURT:  Plaintiff?

            13             MR. KOLBO:  Yes, sir.

            14                            CROSS-EXAMINATION

            15  BY MR. KOLBO:

            16   Q    I just have a few questions.

            17             I'm sure I'll struggle with some of the language

            18   here, but I'll do my best.

            19             Dr. Raudenbush, on the first subject matter with

            20   respect to the drawing that you've got there, am I correct

            21   first of all with respect to number 2, you would agree that

            22   this is a case in which race is taken into an extensive -- to

            23   a great degree?

            24   A    I would.

            25   Q    So it's something that one can ascertain from example



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             1  number 2 even though you had a calculated odd ratio infinity.

             2   A    Yes.

             3   Q    And the second -- or in the first example, it's your

             4  conclusion that this is a case in which race is not taken into

             5  account to a great extent.

             6   A    To a great extent, that's correct.

             7   Q    And your testimony as I understand it, one wouldn't be

             8  able to discern the difference between those two scenarios

             9  because in both cases you get a calculated odds ratio of

            10  infinity; right?

            11   A    Well, we can discern the difference between those cases,

            12  but not using the approach of discarding data and then

            13  calculating an odds ratio. The reason, by the way, that we can

            14  discern the difference in this case is because we have all the

            15  available information. There are only two things that can go

            16  into the admissions decision.

            17   Q    But as I understood your testimony, and correct me if I'm

            18  wrong, one of the problems was looking at odd ratios in that

            19  case is that in both cases you've got infinite calculated odd

            20  ratios; right?

            21   A    It's not because they're infinite.  Even if they were

            22  just the same, let's say they were both twenty-three, the fact

            23  that the odds ratio comes out the same in both cases, and could

            24  easily come out the same, shows that the methodology can reveal

            25  the difference between two cases, one in which there's a great



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             1  extent and one in which there is a lesser extent.

             2   Q    But one could also in that scenario, in addition to the

             3  odds ratio analysis, one could also look and see that there is

             4  a difference between these two cases; right, because one would

             5  know that in most cases, under number one, either you have all

             6  admits or all rejects, and the other a very small area where

             7  you have admit all minorities and admit only some majority

             8  students.

             9   A    That would be the crucial piece, would be the amount of

            10  data that were discarded by Professor Larntz which are those

            11  cases in which all are rejected or all are admitted.  That is

            12  actually a much more informative, I'll say, piece of evidence

            13  about these two cases than the odds ratio.

            14   Q    And you can actually discern looking at one or two that

            15  they're different in that respect; correct, in terms of the

            16  amount of data that you call discarded?

            17   A    You would certainly -- yes, that would be a decisive --

            18  in this limited case, where we have all the information, that

            19  by itself would tell us an enormous amount and to what extent.

            20   Q    And the data that we have in this case including the data

            21  that Dr. Larntz submitted graphically we can see very clearly,

            22  can't we, how many cases -- how many applications fall in this

            23  category of admitting all students of all races?

            24   A    We can see -- the problem is that we don't know all of

            25  the factors that are creating those decisions.  If we assumed



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             1  -- if we're willing to assume that grades and test scores are

             2  the only thing that count other than race, we could do the kind

             3  of analysis that I have here. But I don't think any of us would

             4  make that assumption.

             5   Q    But my question is:  By looking at the data as Dr. Larntz

             6  has presented it, and the data that we have here, we can

             7  actually determine what percentage of files are those under

             8  scenario number one in which all students, of all races, are

             9  admitted; true?  We can see what the size of that group is;

            10  true?

            11   A    We can -- you mean conditioning or controlling for grades

            12  and test scores?

            13   Q    Yes.

            14   A    Controlling for grades and test scores we can certainly

            15  assess -- see what cells have all admits or all rejects, that's

            16  right.

            17   Q    We could see how large of a representation that is across

            18  all the grid; correct?

            19   A    Yes, we can.

            20   Q    And we could do the same analysis with respect to the

            21  number of students who are rejected, whether all minorities or

            22  all --

            23   A    Controlling for what we know, again, just grades and test

            24  scores, yes.

            25   Q    Okay.  And would you agree that there is a very



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             1  substantial number of files in the University of Michigan case

             2  in which there are comparative differences, that is, in which

             3  there are some minority students admitted, and some majority

             4  students admitted, less than all of those groups, in which we

             5  can calculate the differences in probabilities?

             6   A    We can calculate the differences in probabilities -- we

             7  can calculate the differences in probabilities I should add for

             8  every, every person who applies in all test scores and grades.

             9  We don't need to discard any different information in order to

            10  calculate the two probabilities -- proportion, I should say.

            11             Where we come in discarding data is when we compute

            12   an odds ratio where -- which prohibits certain calculations

            13   because of the division by zero.

            14   Q    But scenario number one, for example, you've got here,

            15  you don't want to assume any cases, do you, in which there are

            16  less than a hundred percent minority students admitted and less

            17  than a hundred percent of majority students admitted; true?

            18   A    I'm sorry, could you please rephrase that?

            19   Q    Example number one, doesn't account for any situation in

            20  which there is less than a hundred percent minority students

            21  admitted, and less than a hundred percent majority students --

            22   A    Right.  In scenario number up there, everything to the

            23  left of that little bubble, all are rejected regardless of

            24  race.

            25   Q    Right, and you're assuming no students in which the



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             1  grouping is such as: fewer than one hundred percent minority

             2  students admitted, and with comparable grades and test scores,

             3  fewer than all majority students admitted.  You made no

             4  provision for that in example number one.

             5   A    For an occasion in which every minority student is

             6  admitted and every majority student is rejected?

             7   Q    No, no, that's not what I --

             8   A    Sorry.

             9   Q    I'm sorry if I wasn't clear.  You have not provided in

            10  your model number one or model number two, for that matter, for

            11  situations in which less than one hundred percent --

            12   A    Oh, I see --

            13   Q    -- of minority --

            14   A    Right -- excuse me --

            15   Q    Can I just finish?  You have not provided in your model

            16  here for either one or two scenarios in which less than one

            17  hundred percent minority students are admitted.  And for

            18  comparable majority students where less than a hundred percent

            19  of majority students are admitted; true?

            20   A    That assumption follows though exactly from saying there

            21  are only two factors.  If there are only two factors that can

            22  affect the admissions decision, then if it's not test scores,

            23  it can only be race because that's the only other factor.  Now,

            24  I agree that's oversimplified.  But under that oversimplified

            25  assumption, what I'm saying about all minorities admitted in



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             1  the bubble would follow from the assumption.  We can certainly

             2  imagine a situation in which other things were done.  Like, you

             3  could flip coins within that bubble, or you could assign

             4  different probabilities, but I was trying to create a very

             5  simple example.

             6   Q    Well, your example just assumes just test scores and

             7  race; right?

             8   A    Just -- actually, this example simply assumes test scores

             9  and race.

            10   Q    Okay, test scores and race.

            11   A    Right.

            12   Q    But you're assuming no cases in which just looking at

            13  test scores and race, no cases in which less than a hundred

            14  percent minority students are admitted, and less than a hundred

            15  percent majority students are admitted with comparable tests;

            16  true?  You're not even accounting for that in your example.

            17   A    If only -- right.  That logically follows from the

            18  assumption that those two things can count, yes.

            19   Q    And what the odds ratios would tell us here, whether

            20  they're infinite or whether they're less than infinite in these

            21  scenarios it would be telling us something about the groups of

            22  students where there's comparative information; correct?

            23   A    I strongly disagree with the idea that there is a

            24  principle of comparative information that tells which data we

            25  can look at and which data we cannot look at.  The principle of



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             1  comparative information that Professor Larntz described is a

             2  principle only within the methodological framework that he

             3  selected for analyzing these data.

             4   Q    But am I correct that the calculated odd ratios that you

             5  have here in this case, infinite, those calculated odd ratios

             6  relate only to students for which there is comparative

             7  information, whether there are differences; correct?

             8   A    In -- once -- yes, once you have decided to use the odds

             9  ratio, they can't be computed except in the bubbles of the two

            10  cases, right.

            11   Q    That's all I have with respect to that.  A couple of

            12  questions on modeling and assumption.  Do I understand that

            13  your analysis with respect to what you did in this case, you

            14  created -- you devised a model that modeled the entire grid; is

            15  that right?

            16   A    Yeah, let me try to explain.  I did -- sir, my primary

            17  thing that I did was a causal analysis which I've described and

            18  I think we all understand. And then as a secondary activity, I

            19  did some analyses to check certain assumptions that Professor

            20  Larntz was making.  And in that second analysis I did do what

            21  you said, yes.

            22   Q    You modeled the entire grid?

            23   A    That's right.

            24   Q    And did you have to make certain assumptions in modeling

            25  the entire grid?



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             1   A    Yes, I did --

             2   Q    But if you were to do an analysis simply on a

             3  cell-by-cell basis you wouldn't have to make any assumption

             4  based on modeling the entire grid; correct?

             5   A    Oh, you have make -- absolutely, you do have to make

             6  assumptions especially if you come up with a composite odd

             7  ratio, you have to assume that the underlying two odds ratios

             8  are the same for every cell.

             9   Q    Would you agree that the fewer parameters you have means

            10  the more assumptions that will be in the model?

            11   A    The fewer parameters the more assumptions?

            12   Q    Yes.

            13   A    It might be true, but it's not necessarily true what you

            14  say.  The number of assumptions is not strictly a function of

            15  how many parameters are in the model.

            16   Q    Just the last few questions on the last point that was

            17  covered here and that was with respect to the -- your opinions

            18  with respect to instability over years.  You were here

            19  yesterday when Dr. Larntz went through the calculations or the

            20  difference in terms of standard deviations between the 1997 and

            21  2000 year?

            22   A    Yes.

            23   Q    Would you agree that your testimony suggesting that the

            24  standard deviation separating those two numbers -- would you

            25  agree that it would not represent a number by merely eleven --



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             1   A    Yes, now that I understand exactly what he did, I agree

             2  that's true.

             3   Q    You agree with calculation?

             4   A    Yes, the 3.7 was the more relevant number.

             5   Q    And your testimony as I understand it was you simply had

             6  a misunderstanding based on your reading of Dr. Larntz's

             7  deposition?

             8   A    Yes.

             9   Q    Were you produced -- did Mr. Delery produced to you as

            10  I've produced to him, Dr. Larntz's computer output in this

            11  case?

            12   A    Yes, I was.

            13   Q    Did you review it and consider that?

            14   A    I did.  I actually looked very, very carefully through

            15  that output.  Professor Larntz does his own programming.  I

            16  received hundreds and hundreds of pages of output. The

            17  regression output doesn't come in a standard format. What you

            18  see in his output primarily are simply large blocks of numbers.

            19             Now, Professor Larntz, I have no doubt knows exactly

            20   how to translate those numbers into the relevant tables in his

            21   report.  I could not make the translation.  I was not able to

            22   make the translation.

            23   Q    So you didn't see any columns in there for his different

            24  analyses where he had a column for one -- one colum of

            25  regression co-efficient?



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             1   A    There were regression co-efficients.  There were several

             2  -- there were many analyses and there were hundreds of them.

             3   Q    And did you see columns for represented values of

             4  standard error?

             5   A    Yes.

             6   Q    And I am correct it was determined standard deviation --

             7  and I probably get this wrong, and correct me, but you divide

             8  the regression co-efficient by the standard error; is that

             9  right?

            10   A    That would give you what we call a Z test.  It's not

            11  normally labeled standard deviations.

            12   Q    Is it sometimes?

            13   A    I've never seen it labeled that way until this -- until I

            14  saw this report.

            15   Q    Did you ever make any attempts to take a look at some of

            16  the numbers that showed up on Dr. Larntz's computer output and

            17  see if they corresponded to the standard deviation value as

            18  reported in his report for different years?

            19   A    I did.

            20   Q    And you couldn't find any correlation?

            21   A    Well, as I've said, there were hundreds of pages of

            22  output.  There were many, many regressions.  And he had well

            23  over one hundred predicted variables in every equation.  So

            24  every single regression he did produced hundreds of regression

            25  co-efficients and I -- maybe I didn't spend enough time or do a



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             1  more -- perhaps I could have found those if I spent an enormous

             2  amount of time. But it was very difficult for me to reproduce

             3  what was his reports from the output that he sent me.  I didn't

             4  make the effort.

             5             MR. KOLBO:  I have nothing further, your Honor.

             6             THE COURT:  Thank you.  Anything else?

             7             MR. DELERY:  Nothing further, your Honor.

             8             THE COURT:  Thank you, Doctor.  We appreciate it,

             9   very much.  Sorry to have taken up your weekend.

            10             THE WITNESS:  I'm glad it's over.  Thank you.

            11             THE COURT:  Thank you, very much.

            12             Ms. Massie, it's my understanding your next witness

            13   will be here at eleven?

            14             MS. MASSIE:  If we could make it at 11:15.  I'm

            15   sorry about the delay, but I'm sure we will be able to get

            16   through the two people today.

            17             THE COURT:  Sure.  I understand.  We'll do it.

            18             Okay, we'll stand in recess in the case until 11:00

            19   a.m.

            20            (Court recessed, 10:25 a.m.)

            21            (Court reconvened, 11:45 a.m.)

            22             MR. DELERY:  Your Honor, one housekeeping matter

            23   while we're waiting.  We would like to do the same thing with

            24   Dr. Raudenbush's drawings that we with Dr. Larntz's --

            25             THE COURT:  Yes.



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             1             MR. DELERY:  So we'll mark it as Exhibit 228 for

             2   identification now, and we'll translate it into a small copy

             3   and move it in.

             4             THE COURT:  Perfect.

             5             MR. DELERY:  Okay.  Thank you, your Honor.

             6             MS. MASSIE:  Hi, Judge.  Our next witness is

             7   Professor Frank Wu.

             8             THE COURT:  Okay, Professor Wu.

             9             Good morning.

            10             MR. WU:  Good morning.

            11                           F R A N K     W U ,

            12        being first duly sworn by the Court to tell the truth, was 
examined

            13  and testified upon his oath as follows:

            14                            DIRECT EXAMINATION

            15  BY MS. MASSIE:

            16   Q    Hi, Professor Wu.

            17   A    Good morning.

            18   Q    If you could spell your name for the record, please.

            19   A    Sure. Frank, F-r-a-n-k, Wu, W-u.

            20   Q    Tell us about the teaching you have done or are

            21  contracted to do if you would, sir.

            22   A    Sure.  I'm currently an associate professor of law at

            23  Howard University in Washington, D. C. where I've taught since

            24  1995.  I also serve as the director of our clinical program,

            25  and I supervise students practicing in the D. C. Superior



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             1  Court.  I teach civil procedure, and I teach federal courts on

             2  some of their subject.  I have previous taught as a fellow at

             3  Stanford University.  I've taught civil rights at American

             4  University, in one of its summer sessions.  I would be a

             5  scholar and residence teaching again on Asian American civil

             6  rights at Eeps Spring College in about one month.

             7   Q    I understand you got a JD, a law degree from the

             8  University of Michigan.

             9   A    That's right, class of 1991.

            10   Q    Professor Wu, how long have you been doing academic work

            11  on questions relating to Asian Americans, civil rights, and

            12  social policy?

            13   A    Probably for about fifteen years or so.

            14   Q    And how long have you been doing academic work on

            15  questions related more specifically to Asian Americans and

            16  affirmative action?

            17   A    At least ten years.

            18   Q    That work has involved extensive publications.

            19             MS. MASSIE:  I'd like to move Professor -- well, the

            20   publications are in his CV which I know the Court has, at tab

            21   175 in the exhibits.

            22  BY MS. MASSIE:

            23   Q    You have a book that's about to be published that's a

            24  comprehensive treatment of the question of Asian Americans and

            25  civil rights as I understand it.



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             1   A    That's right.  My book entitled, "Yellow, Civil Rights

             2  Beyond Black and White" is in the catalog basic books scheduled

             3  for publication later this year. It's just about done.  I just

             4  have to revise a few more chapters.

             5   Q    You have numerous chapters in other books on Asian

             6  American and public policy.

             7   A    That's right.

             8   Q    A number of law review articles, articles in the "Asian

             9  American Policy Review.  A law case book which I understand is

            10  not published yet, but it's forthcoming.

            11   A    That's right.  I have a co-authored case book concerning

            12  Asian Americans and civil rights with a focus on the

            13  Japanese-American Internment experience.  It was written with

            14  four other law professors, and we have a contract with Aston

            15  Books, one of the leading case book publishers.  That also

            16  should be out later this year.

            17   Q    A chapter either just published or forthcoming in Asian

            18  American politics?

            19   A    That's right.  I have a chapter, a final chapter, in a

            20  book that was just published by Stanford University Press and

            21  Woodrow Wilson Center, edited by Historian Gordon Chan.  It's

            22  entitled, "Asian Americans and Politics."

            23   Q    And you've recently been appointed by the Washington, D.

            24  C. City Council to serve on the city's Human Rights Commission

            25  and on -- in part so that your expertise on that is of Asian



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             1  American civil rights and social policies will be made

             2  available to the Commission as a whole, is that right?

             3   A    That's right.  I'm the first and only Asian American to

             4  serve on that Board.  I was nominated by the mayor and

             5  confirmed by the City Council.

             6   Q    You've testified before Federal Governmental entities on

             7  questions involving Asian Americans and civil rights, and

             8  specifically, Asian Americans and affirmative action including

             9  the judiciary committee of the House of Representatives and the

            10  United States Civil Rights Commission?

            11   A    That's right.  I've testified before the House in 1995,

            12  and the Civil Rights Commission in I believe 1998.

            13   Q    Admist Is a very long list of public appearances you've

            14  hosted a PBS series entitled "Asian America" for some time?

            15   A    That's right.  I've hosted about thirty episodes of that

            16  series which is syndicated by PBS.

            17   Q    And have also done a number of invited academic

            18  presentations at universities all across the country on a range

            19  of subjects involving Asian Americans civil rights and social

            20  policy?

            21   A    That's right.  I spoke to the University of Texas,

            22  University of Nebraska, Smith College, and a few others that I

            23  can't recall.

            24   Q    Is it fair to say, Professor Wu, that you're one of the

            25  foremost nationally recognized experts on issues of Asian



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             1  Americans civil rights and social policy?

             2   A    Well, at the risk of being immodest, I would say, yes, I

             3  have written very widely, and probably have studied it more

             4  extensively than just about anyone else who looks at these

             5  issues.

             6             THE COURT:  You know, Frank Lloyd Wright -- did you

             7   ever read the story about Frank Lloyd Wright, who testified

             8   for the first time in his life, and they said -- the attorney

             9   said something like, tell us about you in terms of your

            10   ability to architecture and so forth.  And he said, well, I'm

            11   the best architect in the world.  And then he looked over to

            12   the Court and said, I'm under oath, your Honor.

            13             THE WITNESS:  Thank you, your Honor, I'll use that

            14   next time.

            15             THE COURT:  There's a whole book of those kinds of

            16   things that are really interesting.  When we take a break

            17   remind me to tell you about the police officer one which is my

            18   favorite.

            19             MS. MASSIE:  I have a police officer one, too.

            20             THE COURT:  I guess we all could write a book on

            21   police officers.

            22             MS. MASSIE:  With that, I'll offer Professor Wu as

            23   an expert on Asian Americans civil rights and social policy

            24   and also move into evidence his expert report which as I said

            25   is tab 175.



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             1             THE COURT:  Any objection by anyone?

             2             MR. PURDY: No, your Honor.

             3             THE COURT:  He may testify as an expert.

             4             (Trial Exhibit number 175 received into evidence.)

             5  BY MS. MASSIE:

             6   Q    Professor Wu, partly in response to a question that the

             7  Court asked of another witness who was very well qualified, but

             8  somewhat less qualified in this particular area than you, I'd

             9  like to start by asking you to tell us all who are Asian

            10  Americans?

            11   A    Well, the term Asian American" is usually used to refer

            12  to some ten million or more Americans who can trace their

            13  ancestry to Asia, to any more than some two dozen countries in

            14  Asia, or to a Pacific Island.  It includes people of diversed

            15  backgrounds.  Some people, relative newcomers to the United

            16  States, some people who may be third, fourth, or fifth

            17  generation Californian.  People of different ethnicities,

            18  different faiths, different linguistic backgrounds, different

            19  walks of life.  But what they have in common is their Asian

            20  heritage, Asian ancestry.  And that makes them a minority in

            21  the U. S.  According to the 2000 census, it looks like Asian

            22  Americans comprise approximately four percent of the nation's

            23  population.

            24             I think to get a real sense though of who Asian

            25   Americans are it might be best for me to just tell you about a



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             1   few who I know, have known.

             2             My father-in-law, for example, my late

             3   father-in-law, who passed away recently at the age of

             4   seventy-five, was born in Wakayama, in a small fishing village

             5   in Japan in 1905.  At the age of sixteen, Shinsuke Izumi,

             6   that's S-h-i-n-s-u-k-e, I-z-u-m-i, persuaded his parents that

             7   they should let him come to the United States to join his

             8   older sister who already lived here and with her husband ran a

             9   shoe store in Los Angeles.  So he boarded a boat and after a

            10   arduous of many months arrived in the United States where he

            11   enrolled as a relative youngster at a business college in Los

            12  Angeles.

            13             While he was there he felt pressure to have an Anglo

            14   name so he picked the name Edwin, following the dapper of King

            15   Edward who was much in the news.  So Eddie as he was then

            16   known after graduating from college was unable to find work

            17   that suited his qualifications because in Los Angeles, in

            18   California, in the United States at that time, there just

            19   weren't many opportunities for people of Asian descent.  So he

            20   opened a small supermarket, a fruit stand in Hollywood.  And

            21   that was his vocation until World War II broke out.

            22             When World War II broke he, along with a hundred and

            23   ten thousand other American citizens and residents of Japanese

            24   were rounded up by their own government and were incarcerated

            25   in internment camps because there is a fear that they would be



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             1   -- be aliens.  That's what they were deemed to be, and that

             2   they would be disloyal and proved to engage in acts of

             3   sabotage or things of that sort.

             4             Well, when he had the opportunity to leave

             5   internment camps to work as an army translator he jumped at

             6   that opportunity.  And from his work as an army translator,

             7   later went on to become topographer for the Defense

             8   Intelligence Mapping Agency where he worked for the rest of

             9   his life.  He is an example of someone who is an Asian

            10   American.

            11             My own father who was born in Mainland China near

            12   Shanghai who then moved to Taiwan as a youngster was offered

            13   an opportunity to go to college in the U. S. And his older

            14   brother had come to the U. S. before him, to Iowa.  So my

            15   father followed his footsteps.  He had a scholarship.  In the

            16   late '50s he moved to snowy cornfields of Iowa City.  And

            17   there because there was segregation and because Chinese

            18   students couldn't find housing some six or seven of them lived

            19   in a one-bedroom apartment with no frig, no real appliances,

            20   and in the winter they would keep their food outside to keep

            21   it fresh, and there was plenty snow which he had never seen

            22   before.

            23             Well, my father who played on an intramural

            24   basketball team while he was in college, a basketball team

            25   called the Orientals who then went on to join Ford Motor



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             1   Company, and to start a family, here in this area, first

             2   living in Dearborn, and who then help found the Detroit

             3   Chinese American Engineers Association.  And who would win,

             4   and was very proud of winning his bridge tournament and his

             5   tennis tournament.  He is an example of an Asian American.

             6             My friend Kaying Yang, that's K-a-y-i-n-g, Y-a-n-g,

             7   an immigrant who arrived in this country as a child, who is of

             8   Hmong, that's H-m-o-n-g, whose family had served the United

             9   States military in it's covert operations in Southeast Asia

            10   and who in recognition of their service were brought over in a

            11   dramatic effort to bring them out after the fall of Saigon who

            12   then moved to Denver where as she told me just a few months

            13   ago as we traveling together where she encountered racial

            14   discrimination, but didn't know what it was, whereas she and

            15   her brother, some of her cousins and other friends went to

            16   school and had kids, called them Chinc and Gook and say they

            17   should go back to where they came from, that they weren't

            18   welcomed, who was spat upon, who had her hair pulled, beaten

            19   up on a daily basis.  Who now having gone to college where she

            20   studied Asian and American studies and learned that there were

            21   other people like her, that her experience was not unique that

            22   she was not alone.  And that there was a name that we give to

            23   this phenomenon and that it was not her fault.  She now runs a

            24   non profit, a leading non profit group in Washington, D. C.

            25   called the Southeast Asian Resource Action Center. She's an



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             1   example of an Asian American.

             2             It's easy though to think that all Asian Americans

             3   are people who have just moved here, who are:  Fresh off the

             4   boat" as people sometimes say.  But Asian Americans also

             5   include people of second, third, fourth and fifth generation

             6   whose ancestors have worked, for example, on the railroad in

             7   the 1880s, whose ancestors were in California before it was a

             8   state, and before it joined the Union, who were in the south,

             9   in the U. S. as part of a fantastic scheme to import Chinese

            10   laborers shortly after 1864, to compete with the recently

            11   freed Black slaves.

            12             There are people who can trance their ancestry back

            13   more than a hundred years from this country, people such as

            14   the Japanese American soldiers, the Nisei, N-i-s-e-i, meaning

            15   the second generation soldiers of the Army 440 Second Unit

            16   that fought in World War II, in the segregated armed forces,

            17   the most highly decorated unit on a per man basis to have

            18   served in the U. S. Army.  A unit which lost eight hundred me

            19   in rescuing the so-called Lost Battalion, that were behind

            20   enemy lines. Those were native-born American citizens who by

            21   birth, by birth right were part of this country, they along

            22   with their families in locked up in internment camps.  They

            23   are also Asian Americans.

            24             By brothers and I, born in the United States are

            25   Asian Americans.  The Hmong, who like Kaying Yang, who are



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             1   younger, were born in Wisconsin, in the Twin Cities or

             2   elsewhere, across the American midwest, after they arrived,

             3   some of whom I've met a year ago when I spoke at Wisconsin, at

             4   its law school, they're also Asian Americans. They're native

             5   born Asian Americans.

             6             So Asian Americans include people of Korean descent,

             7   of Indian descent, of Philippino descent, of Pakistani

             8   descent.  It includes people from Tonga, people from Guam.

             9   And what we have in common is an experience, an experience in

            10   the United States of being called Chinc, and Jap, and Gook, of

            11   being told you should go back to where you came from, of being

            12   asked where are you really from, as if we're going to go back

            13   some place.  Being asked how do you like it in our country,

            14   when are you going home.  Of being told, my, you speak English

            15   so well, which I'm always attempted to rely, why, thank you,

            16   and so do you.  That's the experience that defines what it

            17   means to be Asian American.  It's a set of experiences that

            18   there's no easy definition, and I think it depends on each

            19   particular person, each particular community. But most

            20   sociologists, census would agree that there is a distinct set

            21   of communities that we can properly call Asian American.

            22   Q    Professor Wu, when did the term Asian American -- and

            23  also I'll ask you in a minute about the term Asian Pacific

            24  American -- when did that term come into being if I understand

            25  is an aggregate term reflecting the many national peoples who



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             1  are included within the category?

             2   A    Well, those two terms are roughly synonomous.  They first

             3  came into use in the late 1960s.  There was a time -- certainly

             4  when my parents came where, when they were called Oriental,

             5  which congers up images of exoticism, of the Far East notion of

             6  otherness.  And that's why that term is no longer usually used.

             7  It's favored.  And Asian American was invented.  It was an

             8  effort by people by to claim an identity for themselves, to

             9  proclaim that this is who we are.  We want to use this name

            10  which shows and recognizes our roots as well as our American

            11  status which says not only to ourselves, but to others that we

            12  are here to stay as part of this country.

            13             So Asian American first started to be used as a term

            14   in the late 1960s.  There were student movements in

            15   California.  At San Francisco State University, for example,

            16   that followed the lead, like the Black Power Movement as they

            17   looked at African-American students as they organized, and

            18   protested, and were part of the multi-racial civil rights

            19   movement. And they said, we, too, can do that.  And so at San

            20   Francisco State University in the late 1960s you saw people

            21   suddenly stand up and proclaim that they were in favor of

            22   Yellow power, and they invented the term Asian American.

            23             Now as it happened, the census categories changed in

            24   1970, as they often do, and the census began to offer the

            25   option of checking off Asian American. So you see two



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             1   different strains here in this history that come together that

             2   leaves this term Asian American.

             3             The use of the term Asian Pacific American is meant

             4   to embrace the many different islands from people also come,

             5   that also share this common experience.

             6   Q    With that introduction I'd like to ask you to turn your

             7  attention to questions about anti-Asian, anti-Asian Pacific

             8  American racism.  Can you tell us about the forms of

             9  discrimination that persist against Asian Americans in the

            10  United States?

            11   A    Sure.  I would divided this into different types.  First,

            12  there is the straightforward racial prejudices and

            13  discrimination and bias.  The sort of thing that a consensus

            14  now recognizes is wrong.  And, second, a more a subtle form of

            15  discrimination.  A form of discrimination that may be in some

            16  instances unconscious, or unintentional or even on its surface

            17  not look like bias, but if you examine it a little closer, more

            18  clearly reveals itself.  Let me start though by talking about

            19  the type.

            20             Asian Americans face straightforward, plain old

            21   racial discrimination.  You see that, for example, in the

            22   glass ceiling.  If you look at the federal government's 1995

            23   glass ceiling study, what you find is that in many categories

            24   Asian American individuals who have the same qualifications as

            25   their white peers, the same educational background, working in



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             1   the same types of jobs, earn less money.  So when everything

             2   is controlled for, what you find is there are racial

             3   disparities, disparities that can be explained by nothing

             4   other than racial backgrounds.  So they face the glass ceiling

             5   at the work place where even though they may have a Ph. D.,

             6   they simply can't make as much money.

             7             There's a sociologist, Joyce Tang, who has studied

             8   phenomenon and has taken a look at Asian Americans working in

             9   technical fields.  And she has found that many of the reasons

            10   that people offer turn out to be false.  Sometimes people say,

            11   well, it's probably because all these Asians are coming from

            12   someplace else, maybe they don't have good language skills.

            13   Well, she did a study where controlled for nativity.  She

            14   looked at people born in the U. S. native-born Asian American,

            15   and compared them with native-born Caucasian.  And what she

            16   found was not only did you still see these same disparities,

            17   equally -- well-educated, qualified people, yet mysteriously,

            18   at companies that presumably are not actively discriminating,

            19   at companies that did hire these people, but they're just not

            20   getting promoted, just not getting paid at the same rate.

            21             In fact, in some instances, she found a real oddity,

            22   that Asian Americans who are native born in many instances

            23   make less than whites who are foreign born. So it has nothing

            24   to do with whether or not you're born in the country.  And it

            25   doesn't have to do with language.



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             1             She found that what some people say about Asians not

             2   being interested in management, that turned out to be false as

             3   well. Sometimes you hear people, well, Asians are more

             4   interested in the technical aspects of these things. They want

             5   to be engineers.  They don't want to managers. They don't want

             6   to vice president. They don't want all that hassle stress.

             7   They don't want to rise in the company.

             8             Well, by using extensive surveys, that's simply

             9   false.  Asian Americans working in these technical fields are

            10   just like their white peers.  They do want to be in

            11   management. They'd like to be in charge.  They wouldn't mind

            12   being the vice president, and they're just not offered those

            13   opportunities.

            14             Again, this happens not in every instance but often

            15   enough that structurally, systematically a pattern emerges and

            16   you see it again, and again, and again in rigorous, empirical

            17   research.  That's one example of glass ceiling.

            18             Another example is if you look at housing.  Housing

            19   segregation for Asian Americans exist.  It is not quite as bad

            20   as a housing segregation for African-American, it is housing

            21   segregation. Asian American of the same socio-economic status

            22   as the whites who own houses in neighborhoods where they'd

            23   like to buy can't buy into those neighborhoods quite often.

            24   Asian Americans tend to live in segregated area.  Again -- not

            25   entirely, but you still find a persistent housing segregation.



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             1             You also see hate crimes. We've seen a rise in hate

             2   crimes towards Asian Americans, ranging from the 1982 brutal

             3   beating of Vincent Chin who was killed by two out-of-work auto

             4   workers, who took a baseball bat, a Louisville slugger to his

             5   head and just beat his head until he was senseless and in a

             6   coma and died a few days later. Those out-of-work auto workers

             7   who pursued Vincent Chin from a nightclub where they had all

             8   been, blamed him.  They had called him -- you'll have to

             9   pardon my language, your Honor -- they called him you dirty,

            10   fucking Jap as they were killing him. And that case I think

            11   stands a symbol for many Asian Americans of the sort of

            12   violence that can still occur to someone who is no different

            13   than anyone else other than because of their racial

            14   background.

            15             Those two people who killed Vincent Chin, who

            16   received probation, and a three thousand seven hundred dollar

            17   -- three thousand seven hundred eighty-dollar fine said that

            18   they blamed him because they were out-of-work auto workers,

            19   and they thought it was because of people like him that they

            20   were out of work.

            21             So you see hate crimes.  You see other instances.

            22   We saw in the 1980s and 1990s a gang, a white gang in New

            23   Jersey that attacked South Asian women.  They called

            24   themselves the "Dot Busters" in reference to the popular

            25   movie, "Ghost Busters" and they would assault Asian women,



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             1   basically picked out at random, but selected because of their

             2   ethnic background.

             3             So you see hate crimes. You see these different

             4   forms of racial discrimination that persist to this day.  You

             5   no longer -- and I hope we don't see anything like the

             6   Internment again, we don't see the sort of discrimination

             7   perpetrated by the government itself, but you see widespread

             8   societal discrimination in instances which sometimes are

             9   condoned, are condoned because people think, well, it's

            10   different than other racial discrimination. These are

            11   foreigners, they're not American, they don't have the same

            12   rights.

            13             Now, there is a second type of racial discrimination

            14   though that Asian Americans face.  And it's more subtle, but

            15   in some ways every bit as dangerous.  There is a myth called

            16   the model minority myth.  There's a stereotype of Asian

            17   Americans. I think in order to understand how this stereotype

            18   works, I first have to describe a stereotype.  At first it

            19   might strict people as quite a positive stereotype.  It's the

            20   stereotype of the Asian immigrant who comes here penniless

            21   with nothing more than the shirt on his or her back, but who

            22   by dent of hard work, confusion work, ethnic, good values, by

            23   opening a small business, that they operate seven days a week,

            24   twenty-four hours a days rises, that even though they speak

            25   broken English, though they have a Ph. D. that they can't use,



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             1   and have to work running a drycleaners or a small store, they

             2   nonetheless persevered and succeed.  And then you see their

             3   children become the whiz kids, the proteges who play the

             4   violin at the age of five, and become valedictorian of the

             5   high school, so when the top ten of the graduating class are

             6   read off it's Chang, and Kim, and Betel.  You see these images

             7   of Asian Americans taking over college campuses, winning all

             8   the scholarships, and going off to Harvard or Yale or Stanford

             9   and breaking the curve in calculus or physics.  Starting to

            10   use science experiments at the age of thirteen. They're whiz

            11   kids, geniuses.

            12             You see this positive image of Asian Americans as

            13   the so-called model minority.  We see that in newspaper

            14   articles.  You see it in television programs.  There was a

            15   "New York Times" article that was entitled "Asian Going To the

            16   Head of the Class" for example.  In some of my published work,

            17   I cite dozen of examples through the '80s and '90s of this

            18   very positive glowing image of Asian Americans as super

            19   successful.  "Fortune Magazine" dubbed them the "super

            20   minority."  So it's this notion that somehow that Asian

            21   Americans have triumph.  They represent as another magazine

            22   writer put it, "the triumph of the dream."

            23             You might look at this and say what could possibly

            24   be wrong with this, this is a wonderful celebration of

            25   opportunity.  It shows how well Asian Americans are doing.  I



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             1   guess there are three things wrong with this, and I'd like to

             2   go through them in order.

             3             First, this is a stereotype, it's false.  Second, if

             4   that's not enough this causes the backflash for Asian American

             5   who should be suspicious of any stereotype not matter how

             6   positive because of what it can conceal.  Third and finally,

             7   it often is used as it was when it was first mentioned by the

             8   "New York Times Sunday Magazine" an article by William

             9   Peterson in 1966, to make an explicit comparison between Asian

            10   Americans and African-Americans to say in effect, they made

            11   it, why can't you.

            12             Let me start with the first problem.  The stereotype

            13   is simply as a factual matter wrong.  It is not an accurate

            14   stereotype.  Now, truth be told some Asian Americans have been

            15   successful. They deserve praise. They deserve credit.  I mean

            16   to take nothing away from them.  But if you take a look at

            17   Asian Americans what you find is that Asian Immigration is

            18   selective.  Before 1965, before comprehensive changes to the

            19   laws that were passed in 1965, there were tiny quotas for

            20   Asian ethnic groups.  For example, a total of no more than one

            21   hundred and eighty-five individuals of Japanese descent could

            22   come into the U. S. per year before 1965.  So what you found

            23   before 1965, people who came here tended to be well-to-do, or

            24   had already gone to school and got a great deal of schooling

            25   or both, well-to-do and people who had at least gone to



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             1   college if not had already gotten a master's or Ph. D., tended

             2   to people who represent the cream of the crop of their home

             3   land. This was a phenomenon we all know "brain trained."  They

             4   would come here and get Ph. D.s' and do well.

             5             So when you look at Asian immigrants what you

             6   realize is they're not representative, they're not

             7   representative in Asian.  They represent the luck few, the

             8   ones who had the means to get out, or the talent to get out.

             9             Now, that's important. It's important because it

            10   means that the Asian Americans once they naturalized and

            11   stayed here where their children have advantages.  One of the

            12   way you can predict how well educated a person will become is

            13   to look at how well educated their parents were before them.

            14   In fact, look at how well educated their father was.  That's

            15   one of the most robust social science factors that you can

            16   look at if you want to get, if you just take any person,

            17   you're going to ask what is the likelihood this person will

            18   complete college, or this will get a master's, or a Ph. D.

            19   One of the ways to figure out the answer to that is to ask,

            20   well, what was the last year of schooling their father

            21   completed.

            22             Let me give you a concrete example.  If you look at

            23   South Asians, what you find is according to some studies as

            24   many as two-thirds of them arrived in the United States with

            25   better than a bachelor's, with at least a master's, a Ph. D.



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             1   or an M. D.  So this creates a terrible skewing of our

             2   picture.  That means you're comparing Asian immigrants and

             3   Asian Americans who are doctors when they arrive here against

             4   a general U. S. population that haven't completed college,

             5   that has just slightly on average done more than completed

             6   high school.

             7             So the first reason that this image is false is

             8   because it wrongly suggests that all of the success is due

             9   solely to opportunities in the United States.  And, again,

            10   don't get me wrong.  This is a wonderful country. I am very

            11   pleased that my parents came here, and that I was born here.

            12   It does offer tremendous opportunity, and some people are able

            13   to avail themselves of it, but it would be highly misleading

            14   to suggest that Asian Americans by themselves as a racial

            15   group represent in some way the triumph solely of the system

            16   here.  They represent instead a complicated table of factors

            17   some of which have to do with who we open our doors to, and

            18   who we welcome.  That's one reason it's false.

            19             Another reason it's false is because the most often

            20   cited statistic that you hear is family income.  You sometimes

            21   hear as you did when the 2000 Census came out that Asian

            22   Americans have attained parity.  That average income for a

            23   family of Asian Americans is equal to or greater than the

            24   average income o, f whites. This is extraordinarily misleading

            25   for several reasons.  Let me detail some of them.



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             1             First of all, Asians are geographically

             2   concentrated.  A majority of Asian Americans live in

             3   high-income, high-cost states.  Hawaii, California and New

             4   York constitute those three states, constitutes -- if not a

             5   majority then certainly a plurality of the Asian American

             6   population in the United States.  Well, as it happens, those

             7   three states also have people of all racial backgrounds a

             8   higher than average family income.  There are just not as many

             9   Asian Americans in South Dakota or Alabama so when you look at

            10   Asian American family income it's terribly inflated because of

            11   this geographic skewing.

            12             Asian American family income is also distorted by

            13   the fact that on average, Asian Americans have larger families

            14   with more wage earners.  The typical Asian American family has

            15   two wage earners.  People of color tend to have families with

            16   more wage earners.  I mean, sometimes the Asian American

            17   families with extended families living in one household,

            18   everyone putting their income into a common pot.

            19             Now, clearly, it doesn't make sense to compare a

            20   household where yo have both adults working to make an income

            21   of sixty thousand, let's say, against a household where you

            22   have one wage earner making fifty-nine thousand, and then to

            23   say that the two-earner household at sixty thousand is somehow

            24   better off than the one wage earner household at fifty-nine

            25   thousand.  It may be true, but it's true only in the most



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             1   superficial and misleading sense.

             2             Now, Asian Americans also tend to be much more

             3   enterpreneural, tend to engage in small businesses endeavors

             4   that are much higher risks. So what you find with Asian

             5   Americans if you just look at the simple question of income,

             6   Asian Americans have not obtained parity. They have obtained

             7   parity only when you ignore the different factors.  When you

             8   look at individual Asian Americans as the 1995 Federal

             9   Government Glass Ceiling Study did, what you find and get is

            10   comparing individual Asian Americans controlling for education

            11   level and occupational field, that Asian Americans make less

            12   money on average than whites. It's unambiguous data so this is

            13   just false in the sense that if you look at the condition of

            14   Asian Americans, most Asian Americans are not the super

            15   minority.

            16             There are also significant ethnic differences, true

            17   that Chinese Americans and Japanese Americans have incomes

            18   that cluster toward the top if you do an ethnic breakdown.

            19   But you also find that Southeast Asians, you find Phillipinos

            20   and you find others clustered toward the bottom. Their

            21   socio-economic status us much more similar to that of

            22   African-Americans than it is of White Americans.  So there are

            23   tremendous ethnic variations as well.

            24             So the stereotype is like most stereotypes, thin and

            25   flimsy and just doesn't stand up to scrutiny.  So no matter



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             1   what you think public policy should be if you simply ask

             2   yourself where are Asian Americans, what is their status, this

             3   notion that Asian Americans have made it and are well-to-do,

             4   is incorrect.

             5             Second, this image leads to backlash. Every part of

             6   the positive stereotype is correlated to the connected

             7   counter-part, and it gets flipped around very easily.  Let me

             8   offer a few examples.  You sometimes here Asian Americans

             9   described as hard-working.  Well, hardworking very quickly

            10   becomes unfair competition.  You sometimes hear Asian

            11   Americans described as good at math and science.  I'm often

            12   told, oh, could you fix my computer.  You must be good with

            13   computers.  Yet, that quickly turns into they're nerdy and

            14   geeky, and can't be lawyers, they can't be managers, they lack

            15   of people's skills.  You sometimes hear Asian Americans

            16   praised for strong families, family values, a nuclear family

            17   that stays together.

            18             Yet that can be turned around.  Asian Americans the

            19   next can be criticized for being too clannish, too ethnic, too

            20   insular, not mixing enough, self- segregating.

            21             Let me give you concrete examples of when these

            22   turnarounds occur.  They tend to occur when there's some sort

            23   of economic crisis.  They did when the Chinese Exclusion Act

            24   was passed in 1882, when the federal government for the first

            25   time started to regulate the borders in a comprehensive



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             1   fashion.  The first set of laws they passed were racial laws,

             2   and they barred Chinese from coming to the United States, and

             3   eventually a work steady created an Asiatic barred zone so

             4   that people so that people of Asian descent could not come to

             5   the United States.  Those Asians who were in the U.S couldn't

             6   naturalize because in order to naturalize you had to be a free

             7   white person. And despite two Supreme Court challenges the

             8   Ozawa case and the Thind case, in 1922, and 1923, in which a

             9   Japanese person and a South Asian argued we are white, those

            10   claims were turned down.

            11             So what you found when the Chinese Exclusion Act was

            12   first being proposed there was the working man's party in

            13   California.  It was an early labor movement led by Dennis

            14   Currney.  And he organized rallies in sandbox.  And his

            15   organizing cry was that Chinese must go. And the central claim

            16   that the white laborers made because at that time San

            17   Francisco was more than one third Asian, and San Francisco was

            18   majority foreign born so that even the people who weren't

            19   Asian, the people where of white ethnics, German, Italian, or

            20   Polish, were foreign born and not native born. They

            21   distinguished though the Asians and they said, the Asians were

            22   competing unfairly, they work too hard.  They said things such

            23   as well, white workers can't just eat a bowl of rice a day.

            24   The Chinese workers are inhuman.  You're going to reduce to

            25   their standard.  If we have the Chinese, we can't have the



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             1   whites in California.  California must be either White or

             2   Yellow. Things like that.

             3             And what you found was that the previous image, the

             4   Asian immigrants as hard-working, that commended them for the

             5   work of railroad where some thirteen thousand were hired and

             6   organized into racial crews to compete against Irish laborers

             7   to see who could lay more track in a day.  That very same

             8   notion that the Chinese laborers would work diligently, work

             9   hard and not complain was turned against them, and then they

            10   were said to compete unfairly.

            11             You see the same thing with this notion of being too

            12   nerdy or too good at math or science and not good with other

            13   skills because that's the excuse most often offered when Asian

            14   Americans ask well, why am I'm not being promoted to

            15   management, why am I not being groomed, why I am not being

            16   trained?  The assumption is that they're only good at math and

            17   science.

            18             You hear stereotypes, you know, in the

            19   1980s -- Brace Ellis, for example, published a novel, "Less

            20   than Zero" where he referred to UCLA which was then becoming

            21   predominantly Asian American, he said, UCLA, those words,

            22   UCLA, stand for United Caucasian Lost Among Asians.  You heard

            23   people refer to MIT as Made in Tiawan.  And these were

            24   comments by white students who said, well we can't compete

            25   these Asian students, they're just too good, they're just too



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             1   nerdy, and too geeky.

             2             Gary Trudeau did a series of "Doonesbury Cartoons"

             3   where he satirized this phenomena.  We saw for example, the

             4   white president, then president of Stanford University tell a

             5   story about how when -- white students sign up for classes in

             6   different technology fields and go to th class and they find

             7   out that there are too many Asian American students, their

             8   only choice is to drop the class because they figure they

             9   won't be able to do any better than to get a C.

            10             So you see example, after example, where every

            11   positive trait is correlated exactly to the negative trait. So

            12   that to be called hard-working as a double edge.

            13             Another reason the model minority myth is dangerous

            14   is because it is explicitly a comparison that's used not to

            15   praise the Asian Americans at all but to insult African

            16   Americans.

            17             In 1966, a sociologist named William Peterson taught

            18   at Berkeley wrote an article, "Success Story, Japanese

            19   American Style."  It was a popular article for the "New York

            20   Times Sunday Magazine."  He later followed it up with a book.

            21   This same old article has been called the most influential

            22   article ever written about Asian Americans.  I think that's an

            23   accurate of this single article.  In it, Dr. Peterson was very

            24   sympathetic.  He talked about the Internment.  He reviewed and

            25   gave a summary of Japanese-Americans in the United States from



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             1   the early part of the century.  He said they had done so well

             2   that they had overcome every obstacle that race could put in

             3   front of them.  Then he said, I'm quoting here, "They examples

             4   stands in contrast to what we might term problem minority."

             5   And you didn't need the author there to nod and wink at you to

             6   see who those problem minorities were because he then went on

             7   to say that the only Japanese Americans who weren't successful

             8   were juvenile delinquents who ran with as he put it, Negro and

             9   Mexican gangs.  So he very clearly set up this contrast

            10   between Asian Americans as the successful minorities and

            11   African Americans as the unsuccessful ones.

            12   Q    Is there anything about the content of stereotype against

            13  Asian Americans that interacts specifically with the practice

            14  of law?

            15   A    Absolutely.  One of the popular stereotype of Asian

            16  Americans is the sort of thing that I used to hear as a child

            17  growing up.  I still hear it now and then.  A personal example,

            18  you sometimes hear people say oh, Asians, you are all so

            19  polite.  I was once at a convention of the AAJA, The Asian

            20  American Journalists.  This was in 1987, in Los Angeles. There

            21  was a guest speaker who had been brought to talk to us.  He

            22  opened up by saying, you know, I'm so pleased to be here, to

            23  speak before all of you Asian Americans because you are all so

            24  polite. And at that moment, everyone in the room hissed him.

            25  To be polite, that seems like a compliment, oh, you're so



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             1  polite.  But that's just something else.  It suggests being

             2  submissive, not aggressive enough for courtroom work. There's a

             3  notion and -- I've been counseled on this.  I was counseled on

             4  it when I was younger and still in law school by people who

             5  thought that maybe an Asian American wanting to do trial work

             6  might not be the best choice.  You might not be able to impress

             7  a judge or a jury.  You might not be able to get clients

             8  because there's this notion, oh, you're so polite, we'd rather

             9  have someone who is going to be gutsy, who is going to in there

            10  and be a fighter.

            11             So these stereotypes certainly do effect people who

            12   want to go into law who happen to be of Asian background.

            13             There is still a notion that Asian Americans are

            14   deficient with verbal skills.  You know one of the reasons I

            15   think I'm told you speak English so well is because there is

            16   the expectation what when I open my mouth I'll confuse my R's

            17   and my L's, that I won't be able to articulate myself and put

            18   together a sentence or a paragraph.

            19             I know when I was thinking about going to law school

            20   my parents told me because they had gleaned from their

            21   workplace, because they had been told, they had been

            22   criticized because they do confuse their R's and the L's that

            23   they lacked the verbal skills and they just weren't going to

            24   get very far, they weren't going to get ahead because they

            25   couldn't communicate.  People just didn't feel as comfortable



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             1   around them.  Even though my parents would practice their

             2   handwriting, and have me correct their grammar, I as an

             3   eight-old-child reading my father's business correspondence,

             4   trying to edit it, to ensure that it had perfect English.

             5   Well, this notion is I think so pervasive that my parents had

             6   troubled with it.  They counseled me you should not become a

             7   lawyer. People aren't going to take you seriously as a lawyer.

             8   That's not what Asians are good at.  And it's not true.

             9   Certainly in Asia there are lawyers, and they're perfectly

            10   good at what they do. It just happens that Asian immigrants

            11   coming to a culture which is foreign to them, speaking a

            12   language with is new to them.

            13   Q    Do those stereotypes of passivity and submissiveness also

            14  have an impact on the fields of politics for Asian Pacific

            15  Americans?

            16   A    Sure. There are far fewer Asian Americans in politics

            17  than you might there would be given how many Asian Americans

            18  there are in Hawaii, in