Exhibit - Moritz College of Law - Home · Daron Robert Shaw, Ph.D. June 25, 2012 22 1 however, is...

Exhibit 8

Case 1:12-cv-00128-RMC-DST-RLW Document 271-8 Filed 07/02/12 of 171

1

IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

STATE OF TEXAS, ) ) Plaintiff, ) ) VS. ) ) ERIC H. HOLDER, JR. in his ) official capacity as Attorney ) General of the United States, ) ) Defendant, ) ) ERIC KENNIE, et al, ) ) Defendant-Intervenors, ) ) TEXAS STATE CONFERENCE OF ) CASE NO. 1:12-CV-00128 NAACP BRANCHES, ) (RMC-DST-RLW) ) Three-Judge Court Defendant-Intervenors, ) ) TEXAS LEAGUE OF YOUNG VOTERS ) EDUCATION FUND, et al, ) ) Defendant-Intervenors, ) ) TEXAS LEGISLATIVE BLACK ) CAUCUS, et al, ) ) Defendant-Intervenors, ) ) VICTORIA RODRIGUEZ, et al., ) ) Defendant-Intervenors. )

********************************************** ORAL DEPOSITION OF DARON ROBERT SHAW, Ph.D. JUNE 25, 2012 **********************************************

Toll Free: 800.211.DEPOFacsimile: 202.296.8652

Suite 3501425 K Street NW

Washington, DC 20005www.esquiresolutions.com


Daron Robert Shaw, Ph.D. June 25, 2012

15

1 prior to 2000 regarding polling, what else did you work

2 on?

3 A. I'd have to check my vitae to kind of refresh

4 my memory, if you don't mind.

5 Q. Please. Go ahead.

6 A. (Witness reviewing document.) Oh, yes. I

7 worked with a professor named Rudy de la Garza, it was

8 at the University of Texas, on a survey of Latinos,

9 pursuant to the 1996 election. It was a three-state

10 survey, so the survey included the states of California,

11 Florida and Texas. And the point was to estimate Latino

12 opinionation and voting behavior in the '96 election,

13 and the survey involved what we call a validation; that

14 is, we asked people whether or not they had voted, and

15 then went back after we had gathered this data and

16 checked the voting records to ascertain actual turnout

17 rates versus self-reported turnout rates.

18 Q. And what did you find?

19 A. We found that there was an overstatement of

20 turnout on the order of 5 to 10 points, I believe, and

21 there was interesting variation amongst the different

22 Latino groups. So, for instance, Cuban Americans were

23 more likely to have overstated their participation than

24 were Mexican Americans, and even more particularly than

25 Puerto Ricans, for whom the overstatement was almost






16

1 zero.

2 Q. How many different vote validation studies have

3 you done?

4 A. That's the only one I have been the principal

5 investigator on. I've been involved with -- and I

6 believe this was actually mentioned in Professor

7 Ansolabehere's deposition -- consultation for validation

8 of the 2008 national election study. But I was not on

9 the special -- there was actually a committee designed

10 specifically -- or empowered specifically to look into

11 validation techniques, and I communicated, but I was not

12 on that committee. I think that was Steve Duggers and a

13 couple of other professors. But I was involved in the

14 conversations about that study.

15 Q. Now, you had mentioned Steve, and I assume

16 there you were referring to Professor Ansolabehere?

17 A. Professor Steven M. Ansolabehere.

18 Q. So how do you know Professor Ansolabehere?

19 A. Professor Ansolabehere was a professor at the

20 University of California Los Angeles when I was a

21 graduate student there. He was teaching econometric and

22 statistics and methodology courses. In fact, I took, I

23 believe, two classes from Steve Ansolabehere.

24 And during the course of your time at

25 UCLA, if you take a certain number of courses in a






17

1 subfield, and political methodology is a subfield, you

2 get a master's in -- a master's in that area. And I

3 have to check with this, because I never received any

4 paperwork, but I believe I have a master's in social

5 science statistics, and I believe Professor Ansolabehere

6 is actually the supervising professor of that degree.

7 But he was not the chair of my dissertation committee.

8 So I know Professor Ansolabehere pretty well.

9 Q. Do you consider yourself to be a statistician?

10 A. No.

11 Q. Are you, just in general, familiar with

12 Professor Ansolabehere's work?

13 A. Yes, I am.

14 Q. And what is your opinion of the quality of his

15 work?

16 A. I think it's excellent.

17 Q. Let's get back to -- I think that we are up to

18 -- let's go ahead, in terms of some of the political

19 work in polling, and I know that you said that you were,

20 I believe it was the director of election studies for

21 Bush/Cheney 2000; is that correct?

22 A. Correct.

23 Q. And how did you come to have that position?

24 A. I had met Karl Rove, who served as campaign --

25 actually, he was the -- he was not campaign manager,






22

1 however, is when the pollster does the poll, it becomes

2 the property of the campaign, and they turn over the

3 data set, and ask you -- you know, internally the poll,

4 the campaign can do analyses.

5 Where I really did most of my work in 2000

6 was on the statewide polls that were coming in. So for

7 instance, van Lohuizen was in charge of the statewide

8 poll. I think he did almost all of them. And they were

9 doing what we call tracking polls in 12 battleground

10 states throughout the months of September and October.

11 And those would come, the actual data

12 would come to me on a nightly basis. And I would take

13 the state polls, look at the media market breakdowns

14 within the states, and continue to update the cost

15 effectiveness of being in, say, St. Petersburg in

16 Florida versus Miami, based on that information.

17 Q. And when you receive the data from the people

18 who were doing the actual polling, I mean, do they

19 provide you all of the raw data or a summary?

20 A. All of it. So it comes, for instance, in the

21 form of something most people would be familiar with, is

22 almost an Excel spreadsheet. It's actually a different

23 statistical package. So every respondent represents --

24 I'll be careful with hand gestures. Every respondent

25 represents a row of data, every column represents a






23

1 different question or response or characteristic of that

2 respondent. So, you know, John Smith is in row one,

3 his, you know, gender is male, so that's a 1 in Column

4 1. His county is Dade, and that's a 2, et cetera.

5 And so you get the raw data, and the

6 analyst is then free to run whatever particular sorts of

7 analyses he or she chooses to or is asked to do.

8 Q. Okay. So for each particular respondent, you

9 could have a row of data so you could see -- you could

10 prepare certain characteristics, for example, and say,

11 well, how many men also are, you know, say they lean

12 conservative or it's something along those lines?

13 A. Exactly. Yeah, exactly.

14 Q. Okay. Let me just step back a minute.

15 When you were with Market Strategies, what

16 were you actually doing in terms of then taking polls?

17 A. Sure. I think Market Strategies conducted --

18 this is in 1992?

19 Q. I believe that's when you said it was.

20 A. Okay. I would say Market Strategies conducted

21 on the order of 12 to 14 national surveys over the

22 course of the 1992 election cycle. So beginning in

23 December of '91, where there was at least one, perhaps

24 two benchmark polls, that is, large polls, significant

25 numbers of respondents on the order of a thousand to






29

1 Q. And what was the subject of these

2 presentations?

3 A. We were asked to present academic research to

4 the political people. So our task was to let them know

5 what was hot in political science, what political

6 science thought about campaigns and campaigns effects,

7 about the responsiveness of representatives to public

8 opinion; about the effectiveness of specific campaign

9 techniques, direct mail, robo calls, and that sort of

10 thing. And so it was really an opportunity for -- they

11 called us eggheads -- for the eggheads to meet with the,

12 you know, the government wonks. And we did this every

13 year, so...

14 And there was some what I would call

15 cross-pollination. And what I mean by that is: We

16 alerted them to the renaissance of what we call field

17 experiments in political science, and they were very

18 interested in that, and we actually helped design some

19 field experiments that the RNC subsequently ran. And if

20 you're interested at some point, I could describe what

21 field experiments are.

22 Q. Sure. Why don't you explain what a field

23 experiment is because --

24 A. Darn.

25 Q. Yeah. Because I don't know.






30

1 A. A traditional experiment is in the laboratory,

2 and you expose -- you know, for instance, a classic

3 example in political science are television

4 advertisements. And you will have some people in, not

5 tell them why you're having them in. You will have them

6 watch a half-hour news broadcast, and in the half-hour

7 news broadcast, you will embed a political ad. And

8 that's the treatment group. The control group will have

9 the same experience except there will be no political

10 ad. And you test the opinions of people before and

11 after the half-hour news broadcast.

12 And to the extent that the people who have

13 seen the ad have different opinions, that they change in

14 response, particularly compared to the control group,

15 you have an estimate of the effect of that

16 advertisement.

17 The criticism of classic experiments is

18 that they're not realistic. That's not how people watch

19 television. They really can't tell us much about

20 politics. So a field treatment tries to get at this

21 problem that we refer to as external validity. And a

22 classic field experiment would be -- and I'll give you

23 stylized example. You want to find out the impact of a

24 mail piece on voters' propensity to vote. So you would

25 take a voter list, take 5,000 -- randomly select 5,000






31

1 people from the voter list and send them this direct

2 mail piece. Then you would call them up before you send

3 it to them and ask them some political questions, or

4 maybe not, maybe you would just check the vote record

5 afterwards. And you would randomly select another 5,000

6 people who don't get the list, and you would check their

7 records. So presumably, the only difference between

8 this groups is that one group got the direct mail piece.

9 And if you go back after the election and

10 you find out that the ex-ante turnout rate for the

11 treatment group was statistically significantly

12 different from the control group, you could say there

13 seems to be reasonable -- it's reasonable to infer that

14 that was the effect of the mail piece.

15 And this has, again, kind of been a

16 burgeoning area in political science since 1999 or 2000,

17 and the RNC was extremely interested in this. The DNC

18 and the Democrats are also really interested in it as

19 well. And, in fact, you know, both sides, both

20 political parties do a significant amount of field

21 experimentation now. And I don't think they give us

22 credit at this point, but it really was something that

23 started, and I'll give credit where it's due, Don Green

24 and Alan Gerber of Yale University were really the

25 people who drove this.






38

1 And so I joined the Fox team in 2002, and

2 I was responsible for -- I was actually at that point

3 not on the statistical committee. Each network has at

4 least one, maybe two, representatives on the broader

5 statistical committee consulting. I didn't join that

6 until 2006. At that point, I was just on the decision

7 team, so my job was to show up -- you know, it was to

8 comment on the questionnaires, actually, that the exit

9 were based on. We were asked to comment on those, and

10 then Fox had their representative on the larger steering

11 calls, and conveyed our views about the nature of the

12 instruments. And then we were in charge of analyzing

13 and making calls on election night.

14 Q. When you look at and analyze a question as to

15 whether it's a good question, what do you look at?

16 A. I tend to believe that -- not on all issues,

17 but on many issues, people don't have a lot of

18 information, and so I come from a school of thought that

19 suggests that the poll itself is, in some sense -- and I

20 need to be careful -- in some sense, is an artificial

21 situation. You're asking people, you're pulling them

22 out of their homes and you're asking them to tell you

23 their opinion. That's not something that happens very

24 often. I'm of the opinion that you ought to provide

25 information that is going replicate either the actual






39

1 debate that you're interested in engaging, or, in the

2 case of voting behavior, replicate the actual vote

3 choice.

4 So, for instance, when I ask a question

5 about who are you going to vote for, I want to know what

6 the ballot looks like in that state. So, for instance,

7 are you going to vote for President Obama or are you

8 going to vote for Mitt Romney? Well, if the ballot in

9 the state has the president, the name, the full name,

10 the party, and the vice president on the ballot, I want

11 that in the question. Are you going to vote for Barack

12 Obama and Joe Biden, the Democrats, comma, Mitt Romney

13 and whomever the Republican is there. So I'm interested

14 in giving them information that I think is going to

15 reflect what's actually happening.

16 In the case of public opinion, I think

17 that means representing, in most instances, both sides

18 of the debate as fairly as you can. And when I say

19 fairly, I mean give voters what people on that side of

20 the issue are actually saying. That's not always what

21 people always do. That's not always what I do.

22 Sometimes we'll simply ask support or oppose. But I

23 tend to prefer two -- what we call two-sided questions.

24 Some people say this, others say that. And I like to

25 make sure that which side is represented first is






40

1 randomized, so you don't get order effects with respect

2 to the question, because people to listen for the first

3 part, and then tune out.

4 So that's, in a general sense, my approach

5 to asking these questions. I like two-sided questions.

6 I like balanced questions. I like questions that rotate

7 or randomize the different sides of the argument.

8 I tend to also think -- implicit in your

9 question is response options, and I tend to prefer a

10 little more subtlety to the response options; in other

11 words, rather than support or oppose, I prefer strongly

12 support, somewhat support, somewhat oppose, strongly

13 oppose, to give people an opportunity to express

14 gradations of opinion.

15 Q. And why is that?

16 A. My experience has been that most people don't

17 have strong opinions on a lot of issues. And I am

18 interested in, oftentimes, engaging the intensity of

19 opinion. So, for instance, if I find out that 50

20 percent of people support a particular response

21 option -- or back up a little bit -- 70 percent of

22 people support a particular position and 65 percent hold

23 that position strongly, oftentimes, a candidate is

24 interested in knowing that, as opposed to 70 percent

25 support but only, you know, 20 holding the opinion






41

1 strongly. And that can be valuable information for a

2 candidate in terms of support for particular policies.

3 Sometimes you're not interested in knowing that. But

4 coming from a campaign perspective, oftentimes that's

5 important information.

6 Q. After 2004, have you done any work for any

7 campaigns?

8 A. Let me see. I was not involved in 2008. Oh, I

9 should -- yes. Yes, I have. I have a relationship with

10 Chris Turner and Craig Murphy. Chris Turner is -- they

11 are the principals of Murphy Turner & Associates, which

12 is consulting firm here in Texas. They handle mostly

13 state legislative races, and I have polled fairly

14 extensively in state legislative races here in Texas, I

15 believe starting at 2004, up through this cycle. So we

16 have done work in state legislative races, 2004, '6, '8,

17 '10 and '12. And I believe that would be on the order

18 of, let's say, polling in three or four state House

19 races per cycle. And I do that --

20 Q. That's State House, not like Congress of the

21 United States?

22 A. Correct. Correct. So these are for the Texas

23 State House of Representatives. I believe there have

24 been a couple of Texas State Senate races as well in

25 that mix. And I go -- I actually met Chris Turner in






44

1 you worked on any other campaigns or done any polling

2 for any other campaigns other than what you have

3 mentioned?

4 A. Not to my recollection.

5 Q. Well, I think that's good enough.

6 MR. MELLETT: We've going for about an

7 hour now, so I think I'd like to take a break. Five

8 minutes sound good?

9 THE WITNESS: Yes.

10 MR. MELLETT: All right. Off the

11 record.

12 (Recess from 9:34 a.m. to 9:46 a.m.)

13 MR. MELLETT: Back on the record.

14 Q. (By Mr. Mellett) Before the break, we had

15 talked about some of the surveys and polling that you

16 had done for some of the more local races, the State

17 House races. When you are dealing with the surveys

18 there, does somebody -- is -- are you contracting with

19 somebody who actually does the phone survey; how does

20 that work?

21 A. Yes. There are a couple of elements involved.

22 The first is the list provider. And that is to say,

23 unlike, say, a national sample, where we do what we call

24 a random digit dial, that is, you're selecting from some

25 universe of numbers, with most political polling, you're






45

1 doing list-base sampling. That is to say, they're not

2 interested in the broader universe of adults, they're

3 only interest in people who might reasonably be expected

4 to show up and vote. So, you have to have a list

5 provider, someone who has a list of registered voters

6 that's current, updated. And then either I -- or I can

7 contract this out -- will randomly select some subset of

8 names off of that list. So in Texas, you know, we're

9 talking about millions of people on the registered voter

10 list. I have a reasonably current list on my hard drive

11 somewhere but even that I think is probably out date.

12 So you want to get a very current list, you select names

13 off that list, then you send those subset --

14 Q. Let me stop you there. How do you select the

15 name off the list?

16 A. Sure. This is where the simple answer is:

17 There's a computer program that simply uses a random

18 number generator so every record is associated with a

19 number and the computer simply selects numbers

20 randomly. That's the records you pull. So it's a

21 computerized process. And you want some subset. The

22 size of the subset that you're randomly selecting

23 depends upon how many interviews you think you'll need

24 to get. So, for instance, if I'm doing a 400-person

25 poll, I may need to select 10,000 names off that






46

1 list. Those names are then sent to another company that

2 does, what we call, a "phone append" or a "phone

3 lookup." So they will actually try to get real live

4 phone numbers, land line phone numbers, associated with

5 that individual.

6 In the technical reports, when you see

7 something called an append rate, or an append

8 percentage, that's a percentage of cases selected for

9 which you actually got what is supposed to be a correct

10 land line number for that individual. Then, so they'll

11 come back -- so this company will then come back to

12 you -- let's say this, again, I requested 10,000 -- I

13 sent 10,000 records, they'll come back with, let's say,

14 7- or 8,000. That would be wonderful. It usually

15 doesn't come back that high, but 5, 6, 7, 8,000 live

16 numbers associated with that select list and then you

17 will send those numbers to the call center, and the call

18 center will have people -- people who are -- those

19 numbers will be fed into a computer program. And when

20 an individual interviewer sits down in front of his or

21 her screen, all right, there's a larger program that

22 will essentially assign them randomly one of the numbers

23 off of your greater universe of phone numbers that have

24 been selected.

25 All right, so, there's randomization in






47

1 the numbers that you send -- that you select off the

2 list, the numbers are then appended, and then you

3 randomly select from the appended numbers the numbers

4 that you are actually calling. All right?

5 Q. So when, for example, you've been doing these,

6 the polls for the State House races, when do you know if

7 you've got a problem with the poll?

8 A. There are some fairly easy metrics to use that

9 allow you understand whether you have a problem. In

10 most of these districts, from census data and from other

11 data that come from, for instance, the Texas Legislative

12 Council, I have a pretty good understanding of the basic

13 demography of the district I'm working with. By

14 demography, I mean the gender breakdown, typically, the

15 age, the racial profile, the ethnic profile; so when I

16 begin to get interviews back, completed interviews, I

17 can check pretty quickly to see the extent to which my

18 sample population is represented by my poll. It's very

19 rarely the case that your polling population looks

20 identical to your sampling population. And the reason

21 for that isn't any problem with, you know, the sort of

22 statistics of it, the problem is that people -- not all

23 people are equally likely to complete a survey.

24 And so, for instance, it's well known that

25 younger people are harder to reach, more difficult to






48

1 get them to complete a survey than older people. So

2 typically, we overrepresent older people in our surveys.

3 There's a slight gender bias, typically,

4 with these polls. Women are a little more likely to

5 answer the polls than are men.

6 And there is a race and ethnicity bias.

7 Part of that's a reflection of a different age profile.

8 For instance, we have difficulty getting completed

9 Hispanic interviews. Probably that's because it's been

10 a population skewed younger, but part of it is that

11 there are issued with respect to naturalization and

12 language and socioeconomic status sometimes too. It's

13 harder to get people of lower socioeconomic status.

14 So when those issues arise, when you see

15 those differences, we typically weight the survey. That

16 is to say, I know from census information, basic

17 demographics, what my poll should look like and I know

18 what I have. And so what will happen is, you will take

19 people who are underrepresented in your poll and you

20 will inflate their values, their opinions, all right,

21 such that they're greater than some -- if everybody's a

22 1 in your initial survey, they will get some value

23 greater than 1 in the weighted survey. All right?

24 And this is standard practice, you know,

25 if AAPOR, the American Association of Public Opinion






49

1 Research, Pew, have kind of a nice piece out recently

2 that talks about the importance of weighting and

3 achieving representative samples.

4 Q. I'm not sure I understand the concept when

5 you're talking about weighting. I understand the

6 concept of your poll doesn't look like the demographics,

7 so I get that, for example, you know, that you've got

8 twice as many old people as you should.

9 A. Right.

10 Q. Or people you have, you can say 65 as your --

11 that you look at that and say, okay, so there's twice a

12 many. How do you, then, weight? In other words, what

13 if -- let's take, in that example, that, for example,

14 you have twice as many people over 65 as you should --

15 A. Right.

16 Q. -- based on the demographics of that district.

17 A. Right.

18 Q. How then is the weighting done to the -- to the

19 younger part of the population?

20 A. Sure. Forgive me if I actually tell you kind

21 of what a code would look like. For the reason I do is

22 I think it would be illustrative here.

23 Typically, for instance, I'll weight by

24 age, gender and race. And so consider a line of code.

25 This would be the first line of a weighting code: If






50

1 race equals 3, let's say that's Hispanic. If age equals

2 1, let's say that's 18 to 29 year-olds. So young

3 Hispanic. And gender equals 1. So Hispanic, young,

4 male, all right? My weight, you know -- my weight code

5 would be WGT1 equals, and what I would have is the

6 expected number of people in that cell over the actual

7 number that I have in my poll. So let's say I have a

8 thousand-person poll and I should have 10 young,

9 Hispanic males and I have six. The code will be 10 over

10 6. So every individual in the survey is weighted up by

11 that function.

12 Now you go to the bottom end and let's

13 say, you know, race equals 1, age equals 5, gender

14 equals 2, that would correspond, typically, to White,

15 senior female. We tend to overrepresent them in our

16 polls. Let's say I should have, according to

17 demographics specs from the census, 25 and I've got 40.

18 Then the algorithm will be weight equals 25 over 40. So

19 those individuals, their opinions, their responses would

20 be decreased in the aggregate sample by that function.

21 So then, what you get when you weight the survey, then,

22 is an estimation of opinion based on the appropriate

23 representation of these groups throughout the sample.

24 And I think there are some rules of thumb

25 to note. Typically, you're reluctant to weight a group






51

1 up by a function greater than two and a half or 3. So,

2 for instance, if I'm supposed to have 15 young, Latino

3 males and I have 1, weighting by a function of 15 over 1

4 is pretty dicey.

5 Q. So how would you weight that?

6 A. You know, honestly, if I had the time and

7 resources, I would go back and specifically tell the

8 call center we need a quota sample; that is to say, we

9 need to specifically target people in this group and get

10 more interviews.

11 Q. So -- and I guess when you use the word "quota

12 sample," is that -- if you go back when, for example,

13 there is polling that's being done, do you get sort of a

14 partial where they say we've done half our calls and

15 this is what we've got?

16 A. Yes, yes. And so if -- I like our call center,

17 for instance, the one I tend to work with is a group

18 called Sentis Research and we'll get overnight --

19 Q. How do you spell that?

20 A. S-E-N-T-I-S, Sentis Research.

21 Q. Thank you.

22 A. You're welcome.

23 They'll provide overnight, sort of, flash

24 updates about what the sample looks like, what the

25 incidents rates are, that is, you know, the extent to






52

1 which they are actually getting real interviews, or the

2 real people they're supposed to be getting from the call

3 list, and they allow you to make adjustments.

4 Often times, an adjustment means you have

5 to, what we call, poll more sample; that is, get

6 additional numbers to make sure that you get the

7 requisite number of completed interviews. But you can

8 make adjustments and sometimes those adjustments will

9 be, "Hey, we're low on Hispanics, we need to do more

10 Hispanic interviews," and we can make those calls on the

11 fly.

12 Q. Do you do quota numbers in the beginning, like,

13 say, for example, you're in a State House race, and so

14 do you say, "You know what, whatever you do, you've got

15 to come back and at least need 10 in this particular

16 category"?

17 A. I have done polls like that before and

18 sometimes the quotas are based on age, gender, and

19 ethnicity, and sometimes they're based on geographic

20 balance; that is to say, we want X number of interviews

21 from Dallas, X number from Tarrant, X number from

22 Harris. And so you're randomly sampling from within

23 that particular strata, but, you know, the technical

24 specs on this are pretty reliable. It's actually fairly

25 common practice.






53

1 But I tend not to quota sample too much,

2 particularly in these political races, because

3 sometimes, in some instances, it's not clear to me that

4 the demography of my target population is as obvious as

5 sometimes people think. In other words, when you're

6 doing political polling, often times you're interested

7 in people who are going to show up and vote. So, for

8 instance in 2008, we kept coming back with more younger

9 people in our surveys than we had in previous election

10 cycles and there was a question about was it appropriate

11 to weight the 2008 polls by turn-out ratios and turn-out

12 specs from 2004.

13 Q. And this was when you're doing polling for

14 what?

15 A. This was actually, we were doing in 2008 for

16 the Texas Tribune. I'm involved with Jim Henson,

17 another professor at University of Texas, and we do

18 polling, a joint-polling project from the University of

19 Texas and the Texas Tribune, and we've been doing it

20 since, I believe 2008, maybe even 2007.

21 And we were finding lots of young people

22 in our polls and there was a very interesting debate

23 about whether we ought to let them occupy the percentage

24 they were occupying in the poll or whether we ought to

25 weight them back to the 2004 specifications. And we






54

1 made a decision just to let it be what it was, which I

2 think was right. Turned out, it ended up being fairly

3 high amongst young people and they were significantly

4 more a part of the Texas electorate than they had been

5 in 2004.

6 Q. Is there -- when you, again, along the same

7 vein dealing with sort of this same aspect of the

8 polling that you were doing for the State House

9 candidates, when you design a particular poll with that,

10 are there certain guide marks or certain aspects that

11 the poll center needs to hit? In other words, do you

12 say this is -- "I want to it look like X?"

13 A. No.

14 Q. Okay.

15 A. They're polling the numbers and then giving us

16 updates and we will make judgments -- we, meaning me

17 usually -- will make judgments about whether we are

18 heavy or light in certain key groups. And then if we

19 decide we want to do something about it, we will call

20 them to communicate. They tend to -- even though we are

21 not necessarily providing them with specs on what the

22 sample should look like, they tend to be pretty aware

23 just from general polling about when they think they

24 have too many seniors, too many females, not enough

25 Hispanics. But they're not responding to specific






55

1 instructions from us.

2 Q. Does the call center, itself, self-correct? Do

3 they look at it and say, "You know, we've got 10

4 seniors, you know, for every one young person?"

5 A. They do not self-correct, they call me, usually

6 at inopportune times. And they want -- they want to

7 bring it to my attention and ask for advice. Sometimes

8 that advice is just "let it go," sometimes it's a

9 midstream adjustment. So they're not self-correcting

10 but they are very attentive and they are certainly not

11 reluctant to call us and let us know when they think

12 there's an issue.

13 Q. So can you give me an example of when they

14 would call you? In other words, what sort of ratios do

15 you get calls? You know, I realize if it's super

16 extreme, of course, they're going to call, but --

17 A. Sure. In this last cycle, this is 2012, we did

18 some polling in Republican primary races and we were

19 getting 65 percent senior, and they brought this to our

20 attention and wanted to know should there be a

21 correction, should they just let it be what it was. And

22 our take was, frankly, that in Republican primary

23 elections -- and these polls were done in February, so

24 as it turns out, months before the actual primary,

25 before people really began to get engaged with the






56

1 process. We thought that was fairly standard that older

2 people would be more likely to express interest in

3 involvement and make it into the sample and complete an

4 interview, so we didn't make an adjustment. But they

5 were very concerned about the absence of people in the

6 18 to 29 year-old demographic.

7 I should also point out that it wasn't

8 that unexpected, given that we were polling people who

9 had a Republican primary vote history, and they tend to

10 skew older as well. You know, there's a -- irrelevant

11 now, but there's a lot of interesting decisions about

12 how you treat younger people in these voter files when

13 you're polling based on previous vote history. Because

14 sometimes they don't have any because they're not

15 interested, sometimes they don't have any because they

16 weren't around. And, you know...

17 Q. So using the same example that you just gave

18 me, when would you look at it and say, for example, that

19 now a 65 percent senior is too much? Give me an example

20 of when would you say that?

21 A. I think in the case of seniors, for instance,

22 let's stay with the example you gave. 65 percent begins

23 to really push it. Again, this is, of course, for a

24 Republican primary electorate sample. If the analog, I

25 think, in a, say, U.S. national survey or a Texas






57

1 statewide survey would be if your senior population is

2 pushing 40 percent, which is considerably higher than it

3 is statewide adult population, considerable higher than

4 the RV, and considerably higher than the demography

5 suggested by the exit polls from 2008. At that point --

6 and I should correct: It's not so much that I'm -- I'm

7 not concerned about the high number in one end, I'm

8 concerned about the other side of the spectrum, low

9 incidence polling in the other end. So I don't mind

10 weighting down. If I have a lot of cases, weighting

11 them down isn't a problem. The problem there, the

12 problem is: Do I have enough cases to weight up at the

13 other end of the spectrum? And so do I have enough 18

14 to 29 year-olds to make reasonable inferences about

15 them, and to be confident that those cases that I'm

16 weighting up are representative of that group, so they

17 are contributing in the correct manner towards the

18 overall population.

19 Q. Let me get back to some of your background. I

20 think we left off in 2006, in terms of what you were

21 doing for Fox News.

22 What have you done for Fox News between

23 2006 and currently?

24 A. I continue to serve on the Decision Team so in

25 each, every two years, I go out and work as a member of






61

1 you use?

2 A. For years I've used Herb Asher's book,

3 A-S-H-E-R, Polling in the Public, which has got to be in

4 it's 8th or 9th edition. I actually kind of prefer a

5 newer text by Bardes and Oldendick that has some

6 interesting stuff on the technical aspects of polling

7 but, I think, is a better book because it includes

8 representation of -- current representations of public

9 opinion, crossed range of issues. So I get more out of

10 that textbook.

11 Q. Do both of those deal with phone surveys?

12 A. Yes.

13 Q. And just in general, can you tell me as maybe

14 as you would your students, what are the various

15 problems you look for in a phone surveys?

16 A. I think, as I tell my students, we -- there are

17 two sorts of errors: There's measurable error and

18 unmeasurable error. The measurable error refers to

19 sample size, how many people you interviewed, and it is

20 sort of measured by the plus or minus margin of error

21 that you get reported.

22 There's also response bias, is the extent

23 to which even if you interview properly, people are more

24 or less likely to respond to your poll. Those are

25 measurable in the sense that, as we discussed earlier, I






62

1 can look at my result and compare it against what I know

2 to be the characteristics of the underlying population

3 and assess the extent to which the poll is off, one way

4 or the other, and then weight.

5 And then there are unmeasurable errors and

6 these are a collection of issues that refer to things

7 like question wording, response options, interviewer

8 effects, order effects.

9 Q. Let me stop you right there, when you say

10 interviewer effects, tell me what you mean?

11 A. Well, as I tell my students, men like to talk

12 to women interviewers, women like to talk to women

13 interviewers. Nobody really likes to talk to male

14 interviewers. We find that in face-to-face interviews,

15 respondents are less likely to express intolerant

16 attitudes. This is -- so there's a large literature on

17 the effects of race in interviewing. There's some with

18 respect to gender interviewing where people are slightly

19 less likely to express attitudes that they see as --

20 "anti-woman" might be too strong, but not necessarily

21 consistent with the pro-female point of view on a

22 certain issue. And so interviewer effects refer to

23 these sorts of differences. And they tend to be fairly

24 small but they're persistent and we're certainly aware

25 of them.






63

1 In the last couple of election cycles, the

2 exit polling has been interesting in that younger

3 interviewers tend to get lower response rates and, in

4 particular, what we're finding is that Republicans seem

5 to be less likely to want to talk to younger exit

6 pollsters. And maybe that's because they have the media

7 card on their chest, I'm not sure. But there are some

8 effects associated.

9 And they're not necessarily partisan

10 effects. For instance in 2008, we found that Obama was

11 consistently over-estimated in the exit poll. And the

12 initial hypothesis was that people were pretending to

13 vote for Obama but they really voted for Hillary, so

14 there was a race explanation. But the evidence looks to

15 be more consistent with the fact that it was simply a

16 response differential. That Obama supporters were

17 really enthusiastic and willing to talk and do an

18 interview, Hillary supporters were enthusiastic, just

19 not quite as enthusiastic. And that small difference

20 resulted in Obama being slightly overestimated in the

21 exit poll. But, again, that's a measurable error

22 because, ultimately, you have a vote against which the

23 search validated.

24 Q. I'm sorry, I had cut you off. You were

25 explaining the types of effects that you can't measure






64

1 and I had stopped you there at interviewer effects.

2 What other effects can't you measure?

3 A. Yeah, the only other one that comes to mind

4 would be -- I may or may not have mentioned this -- was

5 order effects. So for example, if I ask a series of

6 questions about the economy, right now, I'm likely to

7 prime people to get people thinking about the economy.

8 And then if I give them a vote choice question, it's

9 possible that their opinions on the election will be

10 influenced by the series of questions that I asked about

11 the economy. Conversely, if I ask them a ballot

12 question first and they say, "Oh, I'm going to vote for

13 whomever," it's possible they might change their

14 opinions on the economy to be consistent with the fact

15 that they're supporting the incumbent or the challenger.

16 These are unmeasurable because we're not quite sure what

17 the true distribution of opinion is. We simply have

18 some fairly strong evidence on different range of issues

19 that these sorts of things can affect the distribution

20 of opinion.

21 Q. Let me ask you, we haven't touched on, you are

22 the director of the Texas Lyceum Poll. Am I pronouncing

23 Lyceum right?

24 A. Texas Lyceum.

25 Q. And what do you do for that?






70

1 this -- was simply support or oppose. And both Anderson

2 and I argued that it probably ought to have a little

3 more information, and we were particularly interested in

4 the con argument which is the possible effect on the

5 elderly, Hispanics, et cetera. We wanted that

6 represented in the con side of a two-sided question.

7 Q. And so that's something that you added to the

8 poll?

9 A. I believe so, yes.

10 Q. Okay. And have you ever looked at

11 identification in polling, for example, in context of

12 any campaign?

13 A. Not that I'm aware of.

14 Q. So it's not something where they asked to do

15 polling on that particular issue?

16 A. Yeah, no. In the campaigns I've been involved

17 with, in terms of issue instrumentation, most of it is

18 focused, and this is -- I'm summarizing several years

19 worth of polling here -- but economics. And to a

20 slightly lesser degree, immigration issues have been

21 kind of the real focus of the State House race

22 instrumentation I've done.

23 Q. Do you vote on the regular basis?

24 A. Yes.

25 Q. Have you ever been a poll worker?






71

1 A. No.

2 Q. A poll watcher?

3 A. No.

4 Q. And then I think we had talked about it, but

5 have you ever volunteered for a campaign in the non-

6 sort of polling sense that we've talked about here?

7 A. No. My wife did ask for a McCain-Palin yard

8 sign in 2008.

9 Q. Let's talk about the -- what has been marked as

10 Exhibit Shaw Number 1.

11 First of all, let me ask: Does the --

12 well, let me ask this, in general: Is that -- regarding

13 your first report, are you aware of any errors or

14 anything in here that would be misleading to the court?

15 A. Yes. There are two things.

16 Q. Okay. Let's -- tell me where they are?

17 A. Sure. Let me go to the specific page

18 here. Let's see now, is Exhibit 1 the initial report or

19 the rebuttal?

20 Q. This is the initial report. I haven't

21 introduce the rebuttal. I'm -- we can talk about that

22 later, but right now I'm just doing the initial report.

23 A. Excellent, okay. Hold on a second, let me find

24 the page. Okay, on Page 18, fourth and final paragraph

25 there.






72

1 Q. Yes?

2 A. All right. So this would be the third

3 sentence, "Out of the 795,955 person list, we randomly

4 selected approximately 60,000 from which to append phone

5 number information." That is not correct. All right.

6 And the appropriate change would be, we selected

7 approximately 150,000 numbers from which 73,284 phone

8 numbers were appended.

9 Q. I see you referencing here a document. Why

10 don't I go ahead and introduce it. I can represent that

11 this is something that was handed to me by counsel.

12 It's entitled "Details of Shaw's Surveys of Texas'

13 At-Risk Population." And then there is another page

14 which is "Comparison of Demographics of Shaw's General

15 Surveys with Relevant Texas populations." And the third

16 page is "Comparison of Shaw's Hispanic and Black Surveys

17 with Demographics of Relevant Texas Populations." And

18 we will mark this as Shaw Exhibit 2.

19 MR. HUGHES: You put all three pages

20 together?

21 MR. MELLETT: I did. I put them all

22 together since you gave them all together in one. I

23 figured we would just make it one exhibit (stapling

24 pages together.)

25 Thank you.






73

1 (Exhibit 2 marked for identification.)

2 Q. (By Mr. Mellett) And so it appeared to me, as

3 you were telling me this information, that you were

4 reading from this first page, that we had mentioned on

5 Exhibit Number 2, the "Details of Shaw's Survey of

6 Texas' At-Risk Population." And if you can, in general,

7 can you describe what the first page of this exhibit is?

8 A. Yes. In reading the deposition of Professor

9 Ansolabehere, he had pointed out that they didn't feel

10 they had -- he didn't feel he had the technical

11 specifications of the poll to make some judgments. And

12 I thought that was an absolutely valid observation, and

13 so we went back and spoke with the group that conducted

14 the initial poll of random selection of numbers from the

15 larger data sets, which is Ross Hunt at Nasica,

16 N-A-S-I-C-A, Consulting, and asked him to specify, you

17 know, to the decimal point, the number of records he

18 pulled, and then the number of records he was able to

19 successfully append or that the company that he used,

20 which is identified as Voice Broadcasting, was able to

21 append phone numbers. We thought that was important

22 information here.

23 So the numbers that you're looking at

24 then, the third column of data represents the initial --

25 the data in the initial report. The second column, I






74

1 guess, the near column of data here, represent the

2 numbers for the rebuttal report. So what you're looking

3 at is the total number of records that were selected

4 randomly in the first row entry, and then the total

5 number of phone numbers that appended.

6 So, for instance, in the case of the Texas

7 Secretary of State's list, 150,000 records were selected

8 out of the 800,000 list; 73,284 phone numbers were

9 appended. And the next number is the append rate. That

10 is the percentage of the time we were able to

11 successfully append the phone number to a record

12 selected. All right.

13 And then the subsequent numbers are

14 actually broken down because we did a general survey for

15 each, and then we did racial or ethic specific samples

16 as well. And so what you'll see, for instance, in the

17 Texas Secretary of State's lists is that 73,284 phone

18 records were identified. And then you'll see in the

19 Total Calls, about 44,500 calls were made for the

20 General list. 27,547 off the Hispanic list. So what

21 you will see is that those numbers there, the 45- and

22 the 27- roughly add up to the 73. So we basically made

23 calls on almost every phone number.

24 At the same time, the 90,000 -- of the

25 150,000 records, 90,000 were polled for the General and






75

1 60,000 were polled for the Hispanic.

2 Q. So if you can explain that: Does that mean

3 that you had a separate pool, and you had one pool that

4 had the 90,000, and you put that aside, and you had a

5 separate pool that was 60,000, and put that aside?

6 A. Yes. The Hispanic -- we wanted to be sure that

7 we were appropriately representing the Hispanic

8 population in this no driver's license list that had

9 initially been put together by the Texas Secretary of

10 State and was referenced in the Department of Justice

11 letter. And so out of the 800,000, we polled 90,000

12 records randomly. We polled 60,000 records from people

13 who had Hispanic surnames. And that adds up to the 150

14 total thousand records selected. And then off of that

15 150,000, we were able to successfully append 73,000

16 phone numbers, and that became the basis for the calls.

17 Q. So in terms of the -- in terms of the records

18 that were randomly selected, how did you -- I guess, why

19 don't we step back.

20 Tell me how -- how you designed the survey

21 regarding your first report?

22 A. Sure. We were presented with a list from the

23 Texas Secretary of State's Office that was referenced by

24 Department of Justice in the letter of people for whom

25 they could not match driver's licenses, who were






76

1 registered voters but had no apparent driver's

2 licenses. So that became our -- the actual number is

3 more line 795,000. And that became our at-risk

4 universe. You know, as best as could be ascertained,

5 those were the people who were potentially at risk

6 because of the SB 14.

7 And we were interested in ascertaining the

8 extent to which those people had access to either

9 driver's license or other forms of identification. So

10 we wanted to sample this population. We thought it was

11 the most effective way to kind of characterize it.

12 Off the 800,000, after some consultation,

13 we decided that we wanted to have a general sample in

14 excess of a thousand people. We wanted a margin of

15 error around plus or minus three points. So we wanted a

16 fairly powerful study.

17 Q. When you say "we," who are you referring to?

18 A. It's essentially myself. I did have a expert

19 consultant working with me who's a research assistant

20 for me at the University of Texas named Joshua Blank.

21 And so it was essentially the two of us who were kind of

22 working together, thinking some of these things through.

23 And we were responding to kind of a

24 general request from the Texas Attorney Generals's

25 Office to answer a question -- one simple question. We






77

1 were asked two questions overall, but the one question

2 we were entertaining here was: What is the likely

3 effect of SB 14 on voting behavior on turnout? The

4 second question was public opinion on SB 14 -- or on

5 voter -- I should say photo identification, generally.

6 Those were the two questions we were asked. And so this

7 survey was an effort to get this first question, "What's

8 the likely impact on turn out?" And this is obviously

9 referenced in the report, so...

10 Q. When you designed the survey, why -- why did

11 you choose the Secretary of State's list of 795,955?

12 A. Sure. The particular question was, "How is it

13 likely to affect people?" And so it seemed reasonable

14 to us that what we wanted to do is to concentrate on

15 people who did not have an official form of ID. And the

16 Texas Secretary of State's Office list was presented to

17 us as the State's best estimate on the best available

18 data of who is on that list. So we decided that we

19 would focus on that element of the population. And that

20 was our, sort of, best judgment. And as Professor

21 Ansolabehere, in his rebuttal report -- or in his

22 initial report provided an alternative list, we turned

23 to that list, again, thinking that we wanted to use the

24 best available list of the potential, as I styled in the

25 report, "at-risk population." So that was our focal






78

1 point, and that's why we focused in the initial report

2 on the Secretary of State's list and then in the

3 subsequent report on Professor Ansolabehere's list.

4 Q. When you selected the list of approximately

5 800,000, were you aware of any limitations of that list

6 when you did your survey?

7 A. We understood the matching criteria that we

8 used. I did not sit down and give any kind of expert

9 consideration to -- in fact, I'm not sure I have

10 relevant expertise to offer on how that list was put

11 together.

12 Q. So you, yourself, did not look at the list of

13 the 800,000 and make an independent judgment of whether

14 or not this would be likely to capture the at-risk

15 population?

16 A. I did not look at the list, no.

17 Q. The -- did you consider a survey of looking at

18 registered voters?

19 A. We did. We chose not to go that route because

20 the second part of this analysis -- or actually I guess

21 it's the first part in the report -- is a review of the

22 political science literature, and what we came away from

23 pretty quickly was that -- what a review of that

24 literature showed and we came away with -- from, pretty

25 quickly was the understanding that a relatively small






79

1 portion of electorate was going to be affected here.

2 That is to say, we're talking about people who do not

3 have identification or potentially don't have other

4 forms of photo ID. And a common criticism that you see

5 in the literature is that studies tend to be

6 underpowered. That is to say, because this tends to be

7 a low incidence or low frequency event that -- and

8 studies are relying on, you know, analyses of a couple

9 hundred people or a thousand people in the survey, but

10 if you include everybody in the population, you're going

11 to get a very, very small subset of people who are

12 affected and you're not going be able say much about

13 them.

14 Now recall, again, from the report, the

15 specific thing we were asked to deal with is this

16 question of racial disparity. And so we thought if we

17 try to interview -- if we interview a thousand people or

18 even 2,000 people, the percentage of people who are not

19 going to have identification is going to be relatively

20 low. And we're really not going to have enough cases to

21 say anything about, you know, racial differences. So it

22 struck us that the better path to pursue was to look at,

23 you know, the official list of people who purportedly do

24 not have driver's license and to examine racial

25 differences and disparities and possession of other ID






80

1 rates within that population.

2 Q. How can you decide, in looking at that initial

3 list of 800,000, that, you know, in terms of completed

4 interviews, that, roughly speaking, a thousand or 1100

5 would be the right number?

6 A. Well, we were actually not open-ended, but we

7 were fairly flexible on what the upper end number would

8 be. We wanted a least a thousand people. And the

9 reason there is, honestly, a combination of the

10 reduction in error versus the cost of additional

11 interviewing. Obviously, you know, there is a cost

12 constraint here.

13 But what happens when -- to the error term

14 associated with a survey, when you get above a thousand,

15 is that you need a significant number of additional

16 interviews to purchase a small reduction in error. So

17 to give a better example, maybe, if you interview a

18 thousand people, the error term is roughly plus or minus

19 3 percentage points. If you interview 2,000 people, the

20 error term is plus or minus 2 percentage points. So you

21 purchase a single point, plus or minus, in precision at

22 the cost of doubling your survey size.

23 And this is always a question, but it -- I

24 think is it is one of the reasons why almost all media

25 surveys, even government surveys, tend to top out at






83

1 Q. Okay. And then, for example, if it went to

2 400, what would be my error?

3 A. It would actually go up to about 6 percentage

4 points, plus or minus 6, yeah.

5 Q. So in -- so at a certain point, that number

6 becomes quite critical; is that right? That you need to

7 have a certain number so that you don't have your error

8 percentage -- standard error so large; is that right?

9 A. Yeah, I think when you start talking about

10 populations, and again, this is -- some of it depends on

11 the distribution of opinion and what you're willing to

12 live with in terms of acceptable error, but, you know,

13 we don't get -- in political science and political

14 consulting, when we start talking about subpopulations

15 of fewer than a hundred people, we get -- we lose a lot

16 of confidence in the sorts of comparisons and inferences

17 that's we're making.

18 Q. You know, as you've described this, you've

19 actually described a couple of different things that you

20 were asked to do: One, dealing with the amount of

21 turnout dealing with SB 14. One, dealing with racial

22 disparity. So maybe we should step back here and start

23 with, when were you first contacted about working on an

24 expert report?

25 A. Oh, I'd have to look at my records. I believe






84

1 it was in late April, but I'd have to check on that.

2 Q. Okay. And when you say check your records,

3 what is it that you'd be checking?

4 A. I have an Outlook calendar where I flag

5 meetings and things, so I'd have to go take a look and

6 see when the first scheduled meeting was.

7 Q. Okay. Well, and what I would say with that is,

8 that if you find that that information is incorrect,

9 please let us know.

10 A. Okay. May I note just on a --

11 MR. HUGHES: I'll keep track.

12 THE WITNESS: Thank you.

13 Q. (By Mr. Mellett) The -- and the best, to your

14 recollection, what is it that you were asked to do when

15 you were contacted?

16 A. It's actually in the report, so in fact if I

17 may?

18 Q. Tell me what page I should refer to.

19 A. Sure. In the Overview section which is on Page

20 2.

21 Q. Yes.

22 A. So the first of these questions is: What is

23 likely effect of SB 14 on the ability of citizens of the

24 state, especially racial and ethnic minorities, to vote

25 in elections? The second question is: What are citizen






85

1 attitudes towards voter identification laws?

2 Q. So would you -- so the first part you kind of

3 take as two parts, the one which is the ability of

4 citizens to vote the likely effect of SB 14 on their

5 ability to vote, and then the second part is especially

6 racial and ethnic minorities?

7 A. Yes.

8 Q. Okay. And so, and that was what you were

9 initially requested to do?

10 A. Yes.

11 Q. Okay. And who was it that made this request?

12 A. The Attorney General's Office contacted me, and

13 I don't actually remember the individual who set up the

14 meeting so I'd have to reference my records on that.

15 Q. Okay. The -- and when did you start working on

16 the survey?

17 A. I'd have to, again, check my records. I can

18 give you a rough timeframe and then if --

19 Q. Well, then let's start with the rough

20 timeframe.

21 A. I believe in very early May.

22 Q. Okay. Did you sign a contract?

23 A. Yes, I did.

24 Q. And does the contract set forth the scope of

25 your work?






87

1 because we're getting into discussions between counsel

2 and Professor Shaw that you are -- are protected under

3 Rule 26.

4 And so I'd ask that you be mindful of

5 that, in framing your questions, because you're really

6 only entitled to know stuff that we told him that he's

7 relying on which --

8 MR. MELLETT: Right.

9 MR. HUGHES: -- and I think we've gone far

10 afield of that --

11 MR. MELLETT: Correct. The basis for his

12 opinion.

13 MR. HUGHES: Yes. So why don't we steer

14 our questions in that direction.

15 Q. (By Mr. Mellett) So in terms, though, in terms

16 of -- in what I'm interested in here is, I'm interested

17 in the setup. And we can do it from your perspective.

18 I don't need to involve anybody else as to what you're

19 talking about. But from your perspective, what is it

20 that you needed from outside help in order to be able to

21 conduct a successful phone survey?

22 A. This actually evolved somewhat because I

23 thought that a survey would be an appropriate way to

24 engage the question. I typically only work with two

25 outside entities; that is, I need a call center to






88

1 actually conduct the interviews, and in this case, I

2 said it was evolving in the sense that I wasn't sure

3 what information was available on the Secretary of

4 State's list. And that posed a particular issue because

5 I didn't know whether phone numbers were on the list or

6 not. As it turned out, they were not, which required us

7 to go to Ross Hunt at Nasica to oversee a phone append.

8 So those were the two entities that were involved, Ross

9 Hunt and then Sentis Research.

10 Q. So in terms of that -- obviously, at some point

11 you must have looked at the records from the Secretary

12 of State with this 800,000, correct? Okay?

13 A. You mean, did I actually crack open the data

14 file and look at the 800,000?

15 Q. Correct.

16 A. Okay. No. Ross Hunt -- I asked Ross Hunt,

17 when he pulled the 150,000 records, to run

18 characteristics of the 800,000. Those were going to be

19 important for us when we went to possibly, as it turned

20 out we did, weight the final sample. So he

21 characterized it by polling a number of, you know --

22 characterizing the overall number of Hispanic surnames

23 in the 800,000, the age profile based on the date of

24 birth entry, and I believe that's kind of roughly what

25 he did.






89

1 But you have to remember, an 800,000

2 person file chews up most of your hard drive. I

3 actually have an external hard drive where I store these

4 data sets. And if you tried looking at them with

5 Outlook or any of the canned programs, they're too big.

6 These are massive data sets. You know, the overall

7 Texas one, voter file, is 14 million so. It's actually

8 really difficult just to crack it open and look at, you

9 know, the entry. So Ross conveyed summary information

10 to me on the Texas Secretary of State's file.

11 Q. Okay. And so just so I'm clear, what summary

12 information did you ask him to provide to you about the

13 Secretary of State's 800,000?

14 A. Number of Hispanic surnames -- or percentage of

15 Hispanic surnames and number of Hispanic surnames, and

16 the percentage of people falling into 5 distinct age

17 categories: 18 to 29; 30 to 44; 45 to 54; 55 to 64; and

18 65 and up. And along with that last piece of

19 information came the percentage of people for whom there

20 is no date of birth entry.

21 Q. Did you ask him for any information about

22 socioeconomic status, or I guess, in the survey it's

23 income or anything -- would that --

24 A. Yeah.

25 Q. Would you have anything like that in there?






90

1 A. The Secretary of State's database, to the best

2 of my knowledge, does not contain any of that sort of

3 information.

4 Q. How about sex of the voter?

5 A. I did not ask. You can run off a -- they have

6 a name analyzer that can provide estimates of that. I

7 didn't ask for that because my experience has been those

8 name analyzers are problematic. Names like Robin, you

9 know, Dana, et cetera, et cetera, are difficult to

10 classify. And the gender breakdown off of the at-risk

11 population, we had some assumptions about, given the

12 ethic and age breakdown; that is to say, populations

13 that skew older tend to be more female. Populations

14 that reflect -- that basically reflect the ethnicity in

15 the state tend to breakdown about 53 female, 47 male.

16 So we didn't have strong -- we had some expectation that

17 the at-risk file would skew a little bit female, but I

18 didn't ask him for that information in the initial run.

19 Q. Did you ask him in the subsequent run?

20 A. No, again, because I don't have confidence in

21 analyzing that off the State file.

22 Q. How about where voters were located, did you

23 ask you by region, since I assume that information would

24 be contained?

25 A. It should be available, certainly county, but






91

1 no, we did not ask for that. I did not ask for that.

2 Q. Any particular -- I know -- the reason I asked

3 is, I know that you had mentioned before that sometimes

4 that you would look to make sure you had certain

5 geographic balance --

6 A. Right.

7 Q. -- and that is something that you had mentioned

8 looking at in other polls. Why didn't you look at that

9 here?

10 A. I was more concerned about, frankly, the ethnic

11 breakdown. In other words, most of the problems with

12 geographic distribution tend to be reconciled once you

13 have the correct ethic and racial distribution, you

14 know. So, for instance, in the case of Texas, if I'm

15 missing Hispanics, if I'm underrepresenting Hispanics,

16 once I weight up for Hispanic, I'm going to correct the

17 geographic imbalances. That is, I'm probably

18 underrepresented in San Antonio, in Bexar, in South

19 Texas and other places where Hispanics are. So I was

20 not as concerned about the geographic distribution as I

21 was about the racial and ethic distributions.

22 By the way, I should --

23 Q. Yes, please.

24 A. I'm sorry. I just want to be clear. It's not

25 that I'm not concerned about that, the specific






92

1 question, obviously, was about information I requested

2 in the characterization of the 300,000 records --

3 150,000 records that Ross pulled in the overall file of

4 800,000. So...

5 MR. HUGHES: Mr. Mellett, just to clarify,

6 I think all the information that Professor Shaw just

7 talked about being provided from Mr. Hunt is included in

8 Shaw Deposition Exhibit 2. That's a helpful comment. I

9 don't mean to interrupt your examination.

10 MR. MELLETT: That's quite all right.

11 Thank you, Mr. Hughes.

12 Q. (By Mr. Mellett) In terms of the -- the

13 information -- well, let me ask on Exhibit Number 2, is

14 that on -- because I know that we've got the call

15 information on the first page. What is the second page,

16 if you could -- which it would be at least -- you have

17 the official exhibit, so why don't you read the top of

18 the second page to me?

19 A. "Comparison of Demographics of Shaw's General

20 Surveys with Relevant Texas Populations."

21 Q. Okay. And where did you get this?

22 A. Should I talk about -- it's sort of --

23 Q. Yes, tell me what it is, and --

24 A. Sure, sure. There was another, again, a

25 statement in Professor Ansolabehere's deposition about






93

1 he wasn't sure how certain things were weighted and what

2 we were weighting to, and so it was an effort to provide

3 information about the nature of weighting, which took

4 place in the first survey, and then to allow counsel or

5 anybody to compare the results of the survey to, in the

6 one case, to the Texas Secretary of State's No Driver's

7 License list for registered voters or the Ansolabehere

8 list later on. So what you will see is gender,

9 ethnicity, age, and then some education and income

10 breakdowns for the adult population, which is based on

11 the 2010 American Community Study, the registered voter

12 population, the 2008 electorate voting population as

13 estimated by exit polls. And then, so you can compare

14 those to the nature of the initial no-record list from

15 the Texas Secretary of State, compared to the initial

16 survey that we conducted off that list of 800,000.

17 Right? And then what you see in the weighting is how we

18 weighted the data to more accurately reflect the

19 information we were given about the Texas Secretary of

20 State file. And then, again, same thing with respect to

21 the second survey done off of the Ansolabehere list.

22 Q. So the -- when we see on there Shaw Survey 1,

23 that's the actual --

24 A. Unweighted.

25 Q. Unweighted number?






94

1 A. Correct.

2 Q. And the Shaw Survey 1 with weighting, where it

3 says WGT, is how it was weighted?

4 A. Correct.

5 Q. Okay. And how, for example -- so in terms of

6 the weighting, did you do weighting in all of these

7 categories that have different percentages? So, in

8 other words, did you weight by just ethnicity and age or

9 did you also weight by male-female, by education and by

10 income?

11 A. We weighted by age, race-ethnicity, and

12 gender. And I believe the technical coding is actually

13 providing -- we provided that in the information we sent

14 with the initial report.

15 MR. HUGHES: I'd like to actually make a

16 record on this at some point today, and now is the right

17 time, I think. Everything that -- the explanation of

18 Professor Shaw's analysis is contained in his report and

19 in the -- and further information we provided this

20 morning in the spreadsheets. Some of the questions that

21 you've asked today, Mr. Mellett, suggests that you may

22 be interested in, like, the underlying raw data, which I

23 don't believe we have provided and you have not asked

24 for thus far. I have it with me today. Because of some

25 of the questions I had in Professor Ansolabehere's






96

1 MR. HUGHES: Okay. And we've been going

2 now for a little over an hour, so maybe it's time to

3 take a break and I could do that now.

4 MR. MELLETT: I think it's a perfect time

5 for a break.

6 MR. ROSENBERG: John, when you do that,

7 would you also e-mail to me Exhibit Number 2?

8 MR. HUGHES: Yes, I will as long as you

9 promise not to hold against me that I'm sure the

10 metadata showed that I'm the one who converted it to a

11 PDF, but it's, you know, it's Professor Shaw, made the

12 spreadsheet, so...

13 MR. ROSENBERG: Yeah, no problem

14 (Recess from 11:01 to 11:11 a.m.)


16 Q. (By Mr. Mellett) I think that we had discussed

17 Exhibit 2, and I think for completeness, it would make

18 sense to go ahead and have you discuss the last page of

19 Exhibit 2 and explain what that is.

20 A. The title is, "Comparison of Shaw's Hispanic

21 and Black Surveys with Demographics of Relevant Texas

22 Populations." As with the previous page, the idea here

23 is to present the demographic characteristics of

24 different populations or subpopulations within Texas, so

25 the adult population of the registered voter in the






97

1 voting population, with the demographic profile of the

2 different surveys. And so we do that in the first

3 couple of data columns.

4 And then you've got Shaw Hispanic Survey

5 1. That was the survey associated with the original

6 report, a survey of 600, and right next to it is Shaw

7 Hispanic Survey Weighted, so you can see what the

8 weighting did within the Hispanic survey. And then the

9 final two entries are the Hispanic and black surveys

10 associated with Ansolabehere's list.

11 Q. Is there -- did you not do any weighting on the

12 general survey off of Ansolabehere's list?

13 A. We did not. The typical criteria or

14 demographic factors and characteristics that you use for

15 weighting are, as I mentioned, gender, race, ethnicity,

16 and age. And until last night, I wasn't able to acquire

17 the age breakdown from the Ansolabehere list of 1.9 or

18 1.5. I believe this is the 1.9 million list. So that

19 was only very recently, as of this morning, provided to

20 us.

21 But maybe more problematic was when we got

22 the survey back, people whom Catalist had identified as

23 African American and Hispanic were self-identifying as

24 some other race or ethnicity at a rate that we weren't

25 quite sure what the characteristics of the Ansolabehere






98

1 population were. So we decided to simply present the

2 unweighted numbers.

3 I should also point out that if you -- if

4 you look at the effect of the weighting on the first

5 survey analysis, the one associated with the initial

6 report, the weighting, obviously, changes the

7 demographic profile, but it didn't much affect the

8 responses that we got across these different questions

9 we were asking, so we didn't feel particularly

10 compelled -- we were very confident, I should say, in

11 weighting the Hispanic and Black and general surveys

12 associated with the Ansolabehere list.

13 Q. So in terms of the reason that none of those

14 surveys were weighted, your concern was, in general,

15 that you just didn't think it would -- you could

16 accurately do it?

17 A. It was that we weren't sure what the

18 characteristics of the underlying population were. If

19 we had known those, we could have done it quite

20 accurately, but we weren't sure.

21 Q. And I guess I'm failing to understand, in terms

22 of the Hispanic survey, why would it be different off of

23 Ansolabehere's list as opposed to what you did the first

24 time in your first survey?

25 A. Well, the first time, it wasn't so much the






99

1 Hispanic list. In the initial survey, we were weighting

2 based on Hispanic surname, which is roughly what

3 Catalist is doing. And so we thought we had a

4 reasonable -- and, in fact, in the Ansolabehere --

5 surveys associated with Ansolabehere list, we found a

6 reasonably high hit rate with respect to the Hispanic

7 population. That is to say, people who Catalist

8 identified and Ansolabehere identified from the Catalist

9 list as being Hispanic, I believe the number -- and this

10 is in the report -- I believe the number was about 87,

11 88, 89 percent self-identified as Hispanic. So they did

12 a reasonably good job there. But with respect to

13 African Americans, it was 67 percent. And because the

14 racial weight requires you to be accurate relevant to

15 the other racial or ethnic groups, if the African

16 American listing was off, we just weren't sure about the

17 overall weights that we would use to weight that

18 population.

19 Q. Let's go back to the first page of Exhibit

20 Number 2.

21 A. Sure.

22 Q. And in terms of the -- in terms of the

23 appending of phone rates, I know this is something that

24 you said that you've done previously in work for other

25 campaigns. What is a typical append rate that you find?






100

1 A. A typical append rate, it varies considerably,

2 depending upon what kind of survey you're doing.

3 Now, append rates are really only relevant

4 for statewide or lower-level races, because in a

5 national survey, you're doing random digit dial.

6 So in a statewide, Texas tends to have

7 tougher append rates than other states, for instance,

8 where I've done some surveys. I've done a couple of

9 surveys in, as I said, California, in Florida. In

10 Missouri I've done some polling, and independent of

11 those I've dealt with in the context of campaigns.

12 Texas's append rate tends to be lower. I

13 would estimate typical append rate is on the order of 65

14 to 70 percent. That is to say, you request, you know,

15 10,000 records -- or you send 10,000 records over, you

16 get 7500 phone numbers.

17 Q. Explain to me how the appending is done, if you

18 know.

19 A. Sure. And this is something that is kind of

20 previewed, or, you know, it's analogous to the

21 conversation that went on in the Ansolabehere deposition

22 with respect to matching, you know, records of any sort.

23 From the Texas Secretary of State's list,

24 I believe we had a first name, last name, date of birth,

25 and address. You turn that over to -- in this case,






101

1 Ross Hunt turned it over to Voice Broadcasting, who has

2 all sorts of, sort of, experience in list expertise, and

3 maybe more appropriately, or more importantly, they have

4 a master list of names, in this case, for Texas. And

5 they will attempt to match people with known phone

6 numbers, landline phone numbers, to people from this

7 list, using those fields of entry. So match on first

8 and last name, match on date of birth, match on address.

9 Now, I do not know the specific protocol

10 they used to do the matching for the append, that is,

11 whether it was first name, last name plus date of birth,

12 or first name, last name plus address. But those are

13 the criteria they used to do the appending. And if they

14 match them, they turn up the number, and that's

15 appended, and that's sent to back to you to send to the

16 call center.

17 MR. MELLETT: John, if I can make a

18 request to know how it was that the append was done, in

19 other words, when they did the matching, to know how it

20 was that they did it, if it was, for example, first

21 name, last name, date of birth or however it was done.

22 MR. HUGHES: Yeah. Well, I can look at

23 that, too.

24 MR. MELLETT: Okay. Thank you.

25 Q. (By Mr. Mellett) So have you worked with Voice






102

1 Broadcasting before?

2 A. I've worked with Ross Hunt on a number of

3 projects, and Ross has used Voice Broadcasting for most

4 of those projects.

5 Q. Did you personally have any discussions or

6 otherwise communicate with anybody at Voice

7 Broadcasting?

8 A. No.

9 Q. So in terms of, as I understand it -- and

10 please correct me if I'm wrong here, because I just want

11 to make sure I've got it how this happened -- is that

12 what you had done, is that you had sent Ross Hunt here

13 -- and we're still talking about the 800,000 list at the

14 a moment. You had sent him this list and said we need

15 records selected, is that what you told him? Or what

16 did you tell him?

17 A. Sure. Let me -- just for the -- to try to be

18 perfectly clear, I never sent Ross a list. This was --

19 you know, the Secretary of State's office sent Ross the

20 list at his request. So, in fact, it might have even

21 gone through Joshua Blank, who is my -- working with me

22 on this project, the consultant. So, it was sent to --

23 overall, this was sent to Ross with instructions to --

24 and we came to an agreement that you would probably need

25 about 150,000 records, given that we were talking with






103

1 a, probably, a harder to reach population by virtue of

2 the fact that they didn't have -- you know, did not have

3 a driver's license, according to state records, that we

4 would probably need to pull extra records to make sure

5 that the phone append yielded a sufficient number of

6 numbers to get an adequate sample. All right.

7 So, the process, then, was the actual list

8 was sent to Ross. Ross randomly selected a set, saved a

9 file with a smaller subset of those names, right? This

10 would be the 150,000. That was sent to Voice

11 Broadcasting, who then did the append and sent that data

12 back to Hunt, who then sent it to the call center where,

13 you know, those people were put into the program, and it

14 was used for the calling.

15 Q. Okay. So just to be clear, you aren't the one

16 that was giving guidance to Ross Hunt on how he should

17 go about doing this?

18 A. Could you clarify that? I mean, I'm confused

19 about it because I certainly didn't say anything about

20 the matching criteria for the phone append or --

21 Q. Right. No. I'm talking about the records

22 selected, that when we select these 150,000 records,

23 that you didn't ask him, you didn't say, "I need you to

24 select 150,000 records"?

25 A. No. Actually, we specified how many interviews






104

1 we wanted, and then in sort of reverse engineering, Ross

2 made a decision about how many records to pull to

3 provide appended phone numbers adequate to get those

4 sample targets.

5 Q. And so what did you say in terms of the number

6 of interviews that you wanted?

7 A. We told him we wanted in excess of a thousand,

8 at least a thousand for the general, and at least 600 --

9 actually, we told him exactly 600 for the Hispanic. So

10 those were the specs.

11 I should add that I believe, initially, we

12 polled a slightly smaller set of records. I believe we

13 asked for additional records after the first or second

14 night of polling, that is, they said, "You're going to

15 need more records to get your targets," and so that's

16 how I believe we got to the total number of 150,000.

17 Q. So they came back to you and said that you're

18 going to need more records pulled?

19 A. They said we do not -- based on how we are

20 interviewing right now, we will not have sample adequate

21 to hit these targets.

22 Q. So, and how many did they have initially?

23 A. That I'm not sure.

24 Q. Okay. So there was a certain number they

25 started with, the number you don't know about --






105

1 A. Right.

2 Q. -- but it ended up being 150,000?

3 A. Exactly. And that number would be close to

4 150, but clearly lower, obviously, so...

5 Q. Okay. So the -- so in terms of, then, the

6 append rate, for example, on the Ansolabehere list, is

7 35 percent as opposed to 50 percent. Does that present

8 any concern for you, the fact that there is a

9 significantly lower append rate?

10 A. Well, I think two points worth making. The

11 direct answer would be no, but it's no in light of two

12 points. The first is: It is a low incidence

13 population, that is, a hard-to-reach population. So I

14 anticipated, based on going back to the first sample,

15 the first night or two of interviewing, you know, we

16 were -- we were sort of the impression that a 30 percent

17 append rate is probably what we'd be getting for a

18 population like this.

19 When we went to the Ansolabehere data, I

20 wasn't clear whether it ought to be a little higher or a

21 little lower, given the additional names, but I thought

22 it would be about 30 percent. So it wasn't unexpected.

23 That's the first point.

24 The second one, which I think is more

25 relevant is, ultimately, the proof is kind of in the






106

1 pudding. When you get the data back and you look at the

2 distribution of the data across these different racial

3 and demographic groups, that's where you can answer

4 questions about whether you think there might have been

5 problems, that certain kinds of populations aren't being

6 represented in your sample.

7 Q. And so -- and that's the information that you

8 presented here in the second one, in terms of the

9 weighting, the percent of, for example, the individuals

10 who -- you know, what their age is, what their ethnicity

11 is?

12 A. Correct.

13 Q. Is that -- okay. And so that -- on that basis,

14 does it allow you to conclude anything about the append

15 rate?

16 A. Could you rephrase that?

17 Q. Well, I guess what I'm trying to figure out is

18 that you said that the data that -- for example, the

19 demographic breakdown -- allows you to, I thought, make

20 some conclusion about the append rate. Is that not what

21 you were saying?

22 A. No, that's correct. And what I would say is

23 that the demography of the unweighted surveys, the raw

24 data, as it were, didn't strike us as being

25 problematic. Slightly more specific, we're very






107

1 concerned about representation of people at the lower

2 end of the socioeconomic scale and about ethnic

3 minorities. And so one of the points of the table is to

4 give you an idea about the percentage of people in the

5 surveys who were high school or less educational

6 attainment, making under $15,000 a year, black or

7 Hispanic.

8 And the point I would raise is not that

9 these are perfect matches for the underlying

10 population. That's not the point. The point is that

11 there are sufficient numbers of people in those groups

12 to feel confident that the fact that the append rate is

13 35 percent for the Ansolabehere survey isn't biasing you

14 so that you're not reaching what we would consider the

15 really hard-to-reach population, some of these really

16 lower end socioeconomic status people.

17 Q. How does the append rate and the lower

18 percentage in the Ansolabehere affect the racial

19 breakdown? In other words, one of the things that

20 you've said is that you've made the comment that, for

21 example, in the Black survey, that only -- you know,

22 that only 68 percent had identified as Black. I guess

23 one of my questions is, that doesn't the append rate --

24 couldn't that have a great effect on it, in terms of

25 phone numbers and what numbers you're able to have






108

1 appended?

2 A. It's possible that if the append rate, that is,

3 the ability of Voice Broadcasting to find a working

4 landline number, that that could be related to other

5 socio and demographic characteristics. That's possible.

6 But what you sort of get -- what you

7 learn, when you look at internals of the survey is that

8 your real concern is that you're going to be missing

9 people who are very mobile, moving around, you know,

10 from place to place, or young people who, you know, have

11 cell phones and don't have a landline, that that's the

12 reason that you're missing them.

13 I wasn't -- you know, what you see in the

14 numbers here, again, sort of referencing this table, is

15 that, you know, in Ansolabehere's list, we have -- if

16 I'm looking at correctly, 18 percent African American,

17 and we ended up with 16 percent African American in the

18 survey. So I felt good about that.

19 The other thing I should point out is that

20 we did the standalone surveys of African Americans and

21 Hispanics to make sure that we had sufficient numbers of

22 African American and Hispanics to ascertain what their

23 opinions are on these things. So we went kind of out of

24 our way to make sure we were getting a large enough

25 sample to say something anything about -- in our case,






109

1 we were really interested in rates of possession of

2 these different forms of identification.

3 So, at the design level, we had some

4 things in there dealing with some of the issues you're

5 talking about, which is the possibility we would

6 underrepresent these groups and wouldn't be able to

7 speak to that. But I do think what the general survey

8 showed is that we did capture, in the particular case of

9 African Americans, we ended up representing them fairly

10 well here. I should say accurately, given the larger

11 population.

12 Q. Okay. But I guess my question goes back to the

13 append rate, is that it seems that -- for example, that

14 68 percent figure that you've got where you have a

15 question about the Catalist data, it seems to me that

16 couldn't that be attributed to the low append rate for

17 the Black population?

18 A. I've read Professor Ansolabehere's testimony,

19 and I think the argument is that it's the case that we

20 were interviewing African Americans from racially

21 heterogeneous neighborhoods, but missing African

22 Americans from racially-homogonous neighborhoods, and

23 that that is a source for error for Catalist.

24 And so by inference, the idea is that the

25 append rate would somehow be related to that, that is,






110

1 you'd be able to find the phone numbers for Blacks in

2 these, let's just say more middle class neighborhoods,

3 more racially-mixed neighborhoods, and that you would

4 overrepresent them, and that since the hit rate for

5 Catalist is lower in those areas, that that's why it

6 looks the way it does.

7 I can speak to that with the data, I

8 think, in the time table, and that is, if you look at

9 the final table here, the demographics of the Black

10 survey, for instance, the number or the percentage of

11 people in the state adult population who are making

12 under $15,000 a year is 14 percent. This is according

13 to the ACS data. But in our survey, African American --

14 28 percent of our African Americans self-report making

15 $15,000 a year or less. So if the question is, you

16 know, are we not getting African Americans in these more

17 downscale communities, in these tougher-to-reach areas,

18 you know, both the education and the income numbers

19 suggest that that's not really our problem.

20 Q. The -- in terms of -- well, let me -- I guess,

21 part of that is, I will say, I've got some additional

22 questions on that, but why don't we wait until I

23 actually introduce that report before we go and do that.

24 You've got me a little bit out of order,

25 but, of course, it was important to get the additional






111

1 information that you have presented here.

2 Why don't we, in terms of -- if we can

3 turn back to the -- well, actually, one of the things I

4 want to do is, if I can go ahead and mark as Shaw

5 Exhibit Number 3. This is the Incidence Report that you

6 had also provided.

7 A. Is this the incidence for the -- for which

8 survey? I want to make sure.

9 Q. I'm sorry. This is for -- it should be with

10 Shaw Number 1. This is your original one as opposed to

11 your incidence report with your --

12 MR. HUGHES: Who's got the stickered copy?


14 Q. (By Mr. Mellett) So let me ask about Exhibit

15 Number 3 here. That -- explain to me what Exhibit

16 Number 3 is.

17 A. Sure. This is a report prepared by Sentis

18 Research, the company that did the calling. And it's a

19 breakdown of the disposition of all the calls that were

20 made in association with the general survey off of the

21 Texas Secretary of State's list of people without

22 driver's licenses who are registered.

23 Q. And so this disposition is, for in each of

24 these categories, it's how after the phone call, it was

25 resolved one of these ways; is that right?






112

1 A. Yes.

2 Q. Okay. And so with that, the -- one of the

3 things that I had a question about, for example, that

4 stuck out to me is under Language Barrier, you actually

5 had more people who couldn't respond to the survey

6 because of language barrier than could complete it. Is

7 that a cause for concern? This is -- if you look at

8 Category number 9 under Language Barrier. This is on

9 the first page.

10 A. Right. Let's see 9 on the first page?

11 Q. Right.

12 A. According to Category 9 on the first page, I

13 have 290 language barriers versus of 600 completes.

14 Q. What are you -- can I see what --

15 A. Was this stapled incorrectly?

16 Q. That may have been stapled incorrectly.

17 A. It's probably -- it's probably the second page

18 should be first.

19 Q. Yes. Correct. Apparently, that was backward,

20 but that's fine, because now you have the official copy,

21 so we will treat it that way.

22 A. Okay.

23 Q. So it's the second page where you're talking

24 about the general. Sorry about that.

25 A. Right.






113

1 Q. All right. So let me go ahead and ask again

2 regarding the second page. Is that a cause for concern,

3 that you have more people who can't respond to the

4 survey because of a language barrier than people who

5 actually completed the survey?

6 A. Right. This is for the general survey.

7 Q. Correct.

8 A. Which did not include a Spanish language

9 instrument or Spanish language interviewers. So what

10 you're getting here, obviously, some number of

11 Hispanics, probably Hispanic and probably some Asian

12 respondents as well, who declined to participate because

13 they're not offered an opportunity to communicate in

14 Spanish.

15 So it is a concern, and it would be a

16 particular concern if there were a belief that within

17 the general survey that the respondents, the Hispanic

18 respondents who could speak English had substantively

19 different attitudes or propensities to vote than the

20 rest of the Hispanic population, which is precisely why

21 we did the Hispanic survey, which is indicated on my

22 first page of Exhibit 2, where we had Spanish language

23 instrumentation and Spanish language interviewers. So,

24 sorry, I should stop there.

25 Q. No, that's fine. And on that first page under






114

1 Language Barrier, where you have 290, why was there

2 still a language barrier?

3 A. Well, you're talking about 290 out of -- let's

4 see, how many total calls made. Recent adults, so close

5 to 11,000 calls. So part of this is Asian respondents

6 who are not able to or not willing to participate. And

7 I should be clear, there's a combination of not willing

8 and not able. There are some people who will say they

9 don't understand because they don't want to do the

10 survey and then --

11 Q. And do you have independent knowledge that

12 that's what that --

13 A. I do not. I do not. That is speculation. It

14 is based on experience, but it is merely speculation

15 with respect to these 290. And then there is some

16 number who were probably Hispanic -- and again, I did

17 not listen in on the interviews -- but did not take

18 seriously the opportunity to participate in Spanish or

19 still used it as a reason to decline to do an interview.

20 Q. So in these disposition reports for this

21 survey, you've got, in terms of page 1, a complete rate

22 of 2.2 percent, and for the second one of 2.5 percent.

23 And how do you respond to the criticisms in the rebuttal

24 reports that this response rate it too low?

25 A. Sure. There are a couple of points to be made






115

1 here. The first is that the comparison of the surveys

2 we're doing here, with the -- for instance, a government

3 survey, which would involve face-to-face interviewing

4 and, you know, months of time in the field, are apples

5 to oranges to an extreme degree. This is a list -- even

6 more generally, this is a list-based sample as opposed

7 to a random digit dial. In a random digit dial,

8 typically, you call a house, you call a number, and you

9 get to a household, and then you ask for an individual

10 in that household. Here we're asking for, you know,

11 usually based on next -- next birthday or some other

12 randomization technique.

13 Q. If I can stop you there. One of the things

14 that I did note, for example, in your -- in the Texas

15 Lyceum Poll in 2009 is that you had touted that fact

16 that you had a response rate of over 38 percent, so,

17 obviously -- so it seems that response rate in that

18 sense, given your touting of it, must be important; is

19 that right?

20 A. Yes. I think response rate is important, but

21 it's an indicator of other things. In other words, a

22 low response rate could indicate that you're having

23 problems creating representative sample.

24 But, so returning to the point, this is a

25 list-based population, which means if we do not get a






116

1 specific individual, you know, the call is terminated.

2 It is, by definition, a difficult-to-reach population.

3 All right. That's who we're interviewing, people who do

4 not have the most, kind of, common form of

5 identification. And the list itself, obviously, has

6 some issues, as has been discussed in both the expert

7 reports and in Professor Ansolabehere's deposition.

8 So I would point out that it is a low

9 response rate. It's not totally unexpected, and I do

10 want to say something about the characterization of

11 response rates, particularly in Professor Marker's

12 rebuttal report. It's not the case that response rates

13 for national surveys average 30 or 40 percent. In fact,

14 there's a Pew study that came out May 15th that show the

15 average response rates for U.S. national surveys

16 conducted by Pew were 9 percent.

17 In fact, in that Pew report, they also go

18 on to point out -- this is sort of a comprehensive

19 study of the representativeness of polls, especially in

20 an era of declining response rates -- that, in fact,

21 response rates don't seem to be highly correlated with

22 the representatives of some of these polls; that is, low

23 response rates seem to produce perfectly reasonable

24 representations in public opinion.

25 Now, they say that there is a problem with






117

1 the low response rates, and that is that you tend to get

2 more attentive, more engaged survey populations than

3 actually exist in reality. But I think that's a long

4 way of saying it's a low response rate, it's not

5 unexpected given this population, and I do think the

6 characterization of response rates in some of the

7 reports that I've read, more specifically Professor

8 Marker's report, are not accurate and not up to date.

9 Q. So in terms of the response rate, I mean, one

10 of the things you had mentioned was that the concern is

11 that you get people who are more engaged with a low

12 response rate. Do you have a concern about that here?

13 A. Initially, we absolutely did. When you get a

14 response rate, as indicated in the incidence reports,

15 you know, two and a half, 3 percent, your initial

16 reaction is that we're going to get people who are more

17 interested, more involved, more engaged in politics, and

18 that could affect, for instance, in this case, the

19 likelihood of voting. But again, the quickest check on

20 that is, since there's a such a high correlation between

21 socioeconomic status and interest and engagement, is to

22 check the education and income numbers, which is what we

23 attempt to do in Exhibit 2. And my concern initially

24 was that we were missing lower-income people. We were

25 missing people who are less educated, and that that






118

1 could be a potential problem.

2 By the way, that's a problem for polling

3 generally. It's not -- certainly not specific to this

4 poll. And by those criteria, the poll seems to be a

5 pretty sound representation of the populations that

6 we're interested in engaging here.

7 Q. So there wasn't anything in that poll that

8 the -- this is the first report that you did -- that

9 gave you cause for concern, particularly given the low

10 response rate?

11 A. Let me check the demographics, and hopefully,

12 it sort of jars my memory on this.

13 There were two things that stood out to

14 me: The high rate of seniors in the unweighted survey,

15 and then the relatively lower percentage of Hispanics.

16 Now, the reason that we were -- actually,

17 the low incidence of Hispanics didn't surprise me too

18 much, given that we know Hispanics are a more difficult-

19 to-reach population, and in the general survey, there

20 was no Spanish language instrumentation. So, we

21 actually felt very good that we had included a Spanish

22 language instrument and standalone poll, given that.

23 The question of seniors and whether they

24 were overrepresented was really -- was an interesting

25 one. We expected this population to skew older, that






119

1 is, if you're talking about a population that does not

2 possess driver's licenses, our assumption was is that a

3 lot of those people could be seniors who allowed their

4 licenses to expire, who were no longer driving, or were

5 behind on identification for other reasons, but we

6 weren't sure about these numbers. All right.

7 So now we did have the comparison points

8 with the Texas Secretary of State's Office's list, and

9 so you'll see in the demos, that when we went to the

10 weighted data, our concern was that the younger people

11 that we did get were representative of the younger

12 people on the list. And that's something that I still

13 think concerns me a little bit. I'm not -- I'm not

14 entirely confident. I would say this, by the way, with

15 probably about 90 percent of the polls I do, I'm not

16 entirely confident about the specific representation of

17 this 18- to 29-year-old cohort.

18 Q. Well, what about -- let me refer you to Page 2,

19 where on the Shaw Survey 1 Unweighted, where 30 to 44,

20 you've got 3 percent. Does that concern you?

21 A. I'm sorry. Say that once again.

22 MR. HUGHES: Page --

23 Q. (By Mr. Mellett) I'm sorry. Page 2. Exhibit

24 2. Page 2. So Shaw's Survey 1.

25 A. Right.






120

1 Q. And you go to 30 to 44, and you see where it

2 says 3?

3 A. Yes.

4 Q. Does that concern you?

5 A. It doesn't surprise me. And I recall looking

6 at the -- so 3 percentage points out of a survey of 1200

7 translates to, you know, roughly 40 individuals.

8 So when we did the weighting, I believe

9 that, you know, the Texas Secretary of State's numbers

10 are 200 -- or 22, which translates to, you know, roughly

11 230 individuals, right? So I'd have to check with the

12 weighting algorithm. I'm not entirely sure whether when

13 we weighted, we didn't collapse the 18 to 29 category

14 with the 30 to 44 category and weight that group up, or

15 whether we treated the 18- to 29 year old the 30 to 44

16 group separately.

17 Q. Okay.

18 A. So the question is, yes, the numbers are low

19 and they're concerning, because you are extrapolating

20 from a relatively low population base. But I would also

21 say, as opposed to a 18- to 29-year-old cohort, which

22 you can argue, is relatively distinct politically, that

23 is, it's young people, there's not as much about the 30-

24 to 44-year-old cohort that's distinct. In other words,

25 it's sort of an arbitrary cut point in some ways.






121

1 And so the fact that there's not a ton of

2 people in there doesn't particularly surprise me, given,

3 you know, that's actually a group that is more likely to

4 have ID possession rates, and I'm kind of less

5 particularly interested in what's going on with that

6 group. I'm not -- I'm not entirely concerned that they

7 have any -- that there are any sort of problems in

8 reaching that group or there are distinct attitudes

9 there. So I'm not entirely sure that we weighted them

10 separately or whether they were collapsed.

11 Q. And what's -- I guess what's the basis for your

12 assertion that the 30 to 44 group in this subset would

13 have higher levels of ID? Is it based on that response

14 of that 3 percent?

15 A. Well, it's actually that if you look at their

16 presence in the overall population, they occupy 30, 33,

17 35 percent of -- whether you're talking about adult

18 versus registered versus voting, they are 22 percent of

19 this list, so they're obviously not as prominent a part

20 of this group as they are of other groups. But you're

21 right, you know, when you start trickling down 3 points.

22 Now, you see that we weighted them -- I

23 must have weighted, actually, by -- I'd like to correct

24 myself. I must have weighted -- actually, that's not

25 true. I may or may not have weighted by these four age






122

1 groups here. As I said, I'm equivocating because I'm

2 not quite sure what the weighting algorithm was with

3 respect to the age distinctions. But we weighted them

4 up to 20 percent. So what -- so what we're talking

5 about is taking a group that's, you know, 35 or 40

6 people, and they end up being 200 people in the weighted

7 sample. And the question is: Are the 40 that we got

8 representative of that group. And the fact that they

9 were tough to get always gives you pause about whether

10 you got the right people. As I said, the only thing you

11 can do is kind of look at the demographic structure of

12 that group, and there was nothing particularly odd about

13 them. That is, the gender breakdown was okay. The race

14 breakdown was okay. But it's, again, you're talking

15 about 40 people, so...

16 Q. Earlier, a couple of hours ago, when we were

17 talking about this, I mean, you had provided me an

18 example of where you said you'd have concerns if you had

19 a senior group that was 65 percent or more, because you

20 would be real concerned that the lower levels wouldn't

21 have significant enough numbers. This doesn't present

22 that same concern we talked about earlier?

23 A. Right. Well, if you recall in that

24 conversation, the reference point was the Republican

25 primary -- or a general election electorate in which we






124

1 A. That's correct. That's correct.

2 Q. Any other concerns that you have about that

3 first survey that you did?

4 A. None that I can think of off the top of my

5 head. But I'm a worrier, so I probably did. I just

6 can't think of them right now.

7 Q. Okay. How about -- how about the disabled

8 population; was the disabled population overrepresented?

9 A. This is an interesting point that came up in

10 Professor Ansolabehere's deposition, and I want to -- I

11 don't think it's a correction, but added information to

12 the table in the initial report, which I think is

13 Exhibit 1, I believe. Ah, here. I say it's not

14 correction, so this would be on Table 8, which is

15 Page 21.

16 Q. Okay.

17 A. All right. So we're looking at the row entries

18 that are pointed to, it would be the next to last, and

19 then the third from last row entries, in which we're

20 reporting the results of the sample here --

21 Q. Correct.

22 A. -- with respect to U.S. Social Security.

23 Now, Professor Ansolabehere said, I can't

24 believe that, you know, 69 percent say that they qualify

25 for an absentee ballot. All right. I don't believe he






125

1 read the specs on the poll. If you turn to Page 46, and

2 you look at Question 11 --

3 Q. Uh-huh.

4 A. -- you'll see that the specs ask if none of Q4

5 through Q10 equals 1. This question was only asked of

6 people who did not have other forms of ID. And so the

7 numbers that you're seeing here on the table represent

8 numbers out of a very small universe, right? So this is

9 out of people who did not -- I'm sorry -- of people who

10 did not have one of these other forms of ID, 44 percent

11 said they -- a full and weighted sample, said they

12 qualified for an absentee ballot. That number, I looked

13 up last night, is about 58 people.

14 Q. So do we have that on the data set? That's

15 what I want to know.

16 A. It's on data set.

17 Q. Okay. So we will be able to follow ourselves

18 now and be able to --

19 A. Absolutely. Absolutely. And I say it's not a

20 correction in the sense that, that this is the correct

21 number, but only a small number of people in the sample

22 were asked the question, so I understand where the

23 confusion comes from. It comes from, it's not asked of

24 the full 1238. It's only asked of the 58 who did not

25 have other forms of ID.






126

1 Q. And then likewise, that's the same for the

2 veteran affairs question?

3 A. Correct.

4 Q. Okay.

5 A. I should point out, in the rebuttal report,

6 which talks about the second survey that we did off

7 Ansolabehere's, everybody was asked, all people in the

8 sample were asked the same question here. So in the

9 next report, the caveat disappears. That's amongst

10 everybody.

11 Q. Okay. So is there a reason you did it one way

12 in the first report and a different way in the second

13 report?

14 A. The first time, it was -- since we were

15 interested in, sort of, the cumulative possession rates,

16 that this was only going to be asked -- again, it was

17 only going to be asked of people who didn't have these

18 other forms of ID. We didn't think it necessary to ask

19 of people who claimed some other form of ID. But then

20 we decided that was mistake, and we should ask it of

21 everybody in the second go round.

22 Q. Maybe you can educate me here. In terms of

23 SB 14, what does SB 14 say regarding whether or not

24 disabled persons have to present an ID?

25 A. My understanding of SB 14 is that if you






130

1 provided here. One is the 5 percent -- I'm sorry -- the

2 6 percent or 8 percent, depending whether you're using

3 weighted or unweighted, and then if you choose to

4 include disability or senior status as further reducing

5 the possibility of being affected, then it drops to 4

6 percent to 6 percent.

7 So I guess, would I characterize the

8 difference between 6 percent and 3 percent, or with the

9 weighted data, 8 to 6 percent as significant or

10 important, well, I think it's all important, but I think

11 it's part of a broader picture. I'm not sure the

12 characterization of eligibility based disability status

13 for seniors is really critical to the overall point.

14 Q. Let me ask your understanding: If you are 65

15 and you go in to a polling place to vote, do you have

16 to present ID?

17 MR. HUGHES: Are you asking under SB?

18 Q. (By Mr. Mellett) Under SB 14. I'm sorry. Yes.

19 Thank you. Not under the law as it currently stands.

20 A. Right. My understanding, under SB 14, is that

21 you would be asked to provide photo identification.

22 Q. And again, under SB 14, if you are somebody who

23 is disabled and you go in to a polling place, will you

24 be asked to provide photo identification?

25 A. That is my understanding, yes.






131

1 Q. And in order to be able to vote, even if you're

2 disabled, you will have to present identification; isn't

3 that right?

4 A. At the polls on election day --

5 MR. HUGHES: Hold on. I'm going to object

6 to the characterization of SB 14. Now you can answer.

7 A. Okay. Can you restate the question again?

8 Q. (By Mr. Mellett) The question is, is that if

9 you are disabled and you go in to vote at a polling

10 place on an election day, that my question to you is:

11 First, do you, under SB 14, need to present photo

12 identification?

13 A. My understanding is that you would.

14 Q. Okay. And so if you are disabled and you go in

15 to the polling place on election day under SB 14 and you

16 don't have photo ID, you would not be allowed to vote;

17 is that correct?

18 MR. HUGHES: Object to the

19 characterization of SB 14. It speaks for itself.

20 A. My understanding is that if you do not have

21 photo ID, you would be allowed to cast a provisional

22 ballot, I believe.

23 Q. (By Mr. Mellett) So that they have a

24 provisional ballot and then --

25 A. I believe --






138

1 A. Oh, wait, excuse me. That's not correct,

2 because the survey conducted February 11th through the

3 17th of 2011, that was, in fact, the last legislative

4 session, if memory serves, and this would be on Page 32.

5 Q. Correct. Right. It's been going on a while.

6 A. Oh, I know.

7 Q. Okay. So, in fact, that was for the current

8 legislative session. So when you didn't -- you didn't

9 otherwise testify, did you?

10 A. No.

11 Q. Okay. Give me your understanding of how SB 14

12 is different from the current law.

13 A. Well, again, this is beyond the purview of my

14 -- beyond the purview of what I was asked to do as an

15 expert consult, or an expert witness in this case.

16 But to the best of my knowledge, the

17 existing system, essentially, requires people to present

18 an identification at the poll. There is a match

19 conducted and the person is allowed to vote. So it is

20 not a photo ID, however, you're required to present some

21 form of ID; a driver's license and some range of other

22 official forms of ID.

23 Q. And what if you don't have it?

24 A. If you do not have the ID, my understanding is,

25 is that you sign -- you have multiple forms of ID, and






139

1 you're allowed to sign --

2 Q. An affidavit.

3 A. -- an affidavit.

4 Q. Okay.

5 A. And then in that case, you are permitted to

6 vote.

7 Under SB 14, the key distinction, I think,

8 is that you are requested to bring a photo ID of varying

9 sorts, so a driver's license, a passport, a citizenship

10 certificate, a license to carry. Let's see. And then

11 there is a poll worker who will match, you know,

12 whether, in fact, the name and information presented on

13 photo ID is consistent with the information on the

14 registrar list, and if so, the person allowed to vote.

15 If not, my understanding is that there are

16 several criteria the poll worker is then asked to use to

17 ascertain whether that person ought to be allowed. So

18 when I say the poll worker is concerned it's not a

19 match, that's actually probably not correct, in the

20 sense that if there's not an obvious match, let's say

21 there's a slight discrepancy in name or some other

22 characteristics, their instructions, my understanding,

23 is, instructing the poll worker how to proceed, so the

24 person is not automatically turned away, the person has

25 -- then the poll worker then proceeds to sort of look






140

1 across this list to make a determination if, in fact,

2 there is a match.

3 In cases where the poll worker determines

4 a match, the person is allowed to vote. If not, then

5 the person casts a provisional ballot, and the

6 provisional ballot then puts the person in the position

7 of being able to get their vote -- the person must then

8 come back to the voter registrar, present information.

9 And if that information is presented -- I believe the

10 term is three days, although I could be wrong -- then

11 the provisional ballot will be counted.

12 So the key distinction, it seems to me, is

13 in the presentation of photo identification as opposed

14 to these alternative forms of identification that aren't

15 necessarily photo.

16 Q. If you don't have a photo identification, can

17 you sign an affidavit and vote?

18 A. Excuse me. Say again. I'm sorry.

19 Q. If you don't have photo identification, can you

20 sign an affidavit and still vote?

21 A. Under SB 14?

22 Q. Correct.

23 A. I'm not -- I'm not certain of that, no.

24 Q. Okay. Do expired photo ID holders get to vote?

25 A. My understanding is that there is a short grace






141

1 period. I believe it's six months with respect to

2 drivers' licenses, although I'm not entirely sure about

3 that.

4 Q. 60 days maybe?

5 A. That might be the case, yes.

6 Q. Okay.

7 A. Thank you.

8 Q. Do you know what a suspense voter is?

9 A. Yes. In the state of --

10 Q. What is it?

11 A. I'm sorry.

12 Q. That's okay.

13 A. I was instructed to be -- not interrupt

14 questions, so I apologize for that.

15 In the state of Texas, the suspense voter

16 is someone to whom official mail, that is, government

17 mail, has been sent and has been returned to the

18 government and with a marking that that person is no

19 longer at that address. In that case, typically,

20 suspense voters are purged from the voter registrar list

21 within, I believe, a period of two years.

22 Q. Do suspense voters, if they go to the polling

23 place and they are a suspense voter, do they get to

24 vote.

25 A. My understanding is that they do.






142

1 Q. And the -- okay, strike that.

2 Why don't we go ahead and turn to Exhibit

3 Number 1. I think you still probably have it there in

4 front of you. And I wanted to ask you about your

5 literature review. What was the scope of your review?

6 A. Well, I was interested in looking at work that

7 had been published in peer review journals or books. As

8 it turned out, almost all of the information, or perhaps

9 even all of it, was peer-reviewed journals. And I was

10 also interested in looking at those pieces of

11 information, or those reports that were, sort of,

12 frequently cited within that group of journal articles.

13 And just to be clear, it's -- there's a

14 different standard, obviously, to get an article or

15 report published in a peer review journal, academic

16 journal, than it is to simply put out a report. And so

17 there are, you know, dozens and dozens of, sort of,

18 position papers, white papers, policy papers, put out on

19 the issue of voter ID laws, and, to a lesser extent,

20 photo voter ID. I was more interested in stuff that had

21 been through the ringer, as it were; stuff that had been

22 peer reviewed.

23 So, I guess the starting point, actually,

24 was a special issue of PS, Political Science Magazine,

25 that published a series of articles, some legal, some






143

1 empirical, on voter ID after the Indiana case.

2 The issue came out after a conference. I

3 believe it was the American Political Science

4 Association's annual conference in which there had been

5 a special panel convened on the topic of voter ID. So

6 many of the articles in that special issue came from

7 research that was first presented at conference.

8 So I had seen versions of some of these

9 papers before, and had PS Magazine. So I went there to

10 look at and kind of get an initial sense of what the

11 current research was. And from there, worked backwards,

12 in some sense, and that is, looked at papers that had

13 been cited extensively in that research, and also looked

14 forward, that is to say, went to those authors' websites

15 and looked for additional extended work that they had

16 done on the topic.

17 Q. How did you decide which materials to include

18 in your report?

19 A. Well, as I suggested, I focused primarily on

20 work that has been published in peer review journals.

21 That's not -- that's not true across the board. I

22 believe the Milio piece has not been published in a peer

23 review journal, but was cited extensively, so I thought

24 it was worth touching on.

25 And in fact, the -- I didn't think, and






144

1 this turned out -- I didn't know whether the Alvarez,

2 Bailey and Katz piece had been published. It ended up

3 being published, but a lot of the initial work that they

4 had done was cited extensively in subsequent articles,

5 but when I read those articles, it was cited as a

6 working paper. In fact, that also has been published in

7 a peer review journal. So there are a couple of

8 instances in which I simply looked -- I not only looked

9 at the, sort of, touched-on pieces, as it were, but to

10 the pieces they were relying on also.

11 Beyond that, you know, I read a number of

12 things that were largely summaries of work that had

13 already been done, or were a little more polemical that

14 I didn't think offered any new, kind of, substantive

15 scientifically-valid research on the subject, so I did

16 not choose to include them in the report.

17 Q. You mentioned Alvarez and that you had looked

18 at a working paper, and I know that one of the things --

19 you had mentioned, I believe, in the course of this,

20 that you had looked at Professor Ansolabehere's

21 deposition. And so I -- one of the -- and it's

22 certainly also mentioned in his report. Did you read

23 his rebuttal report?

24 A. Yes.

25 Q. Okay. And so at the time that you wrote what






145

1 is Exhibit Number 1, were you aware that there was a

2 later published piece by Alvarez?

3 A. No. I was unaware of the, I believe, 2011

4 piece in Political Analysis until I had read Professor

5 Ansolabehere's report.

6 Q. Okay. And the -- one of the things that was

7 mentioned by Professor Ansolabehere is in regards to

8 looking at the effects of voter ID, that Alvarez had

9 looked at it in Indiana and Georgia, and, in fact, it

10 had listed that there was a decrease of 10 percentage

11 points. Did you look at that?

12 A. Yeah. I've read the Alvarez, Bailey, and Katz

13 piece in Political Analysis.

14 Q. Do you have any response to Professor

15 Ansolabehere's criticism?

16 A. Sure. The piece that was published, the

17 Alvarez, Bailey, and Katz piece in Political Analysis.

18 Political Analysis is a methodology journal. It's

19 probably the top methodology journal in political

20 science. It's not a substantive journal. And in fact,

21 the article that he is referring to was an article

22 that's key point was that it offered a relatively novel

23 approach to estimating the effects based on survey data,

24 something called a Bayesian shrinkage estimator. That

25 was the primary selling point, if you will, for the






146

1 article and why it was kind of novel.

2 The analysis of voter ID effects was

3 offered as one of two example of the use of a Bayesian

4 shrinkage estimator to say something about a political

5 event, occurrence. The other was, I believe they were

6 looking at the impact of church attendance on voting. I

7 think that was the second example.

8 If you look at that piece closely, so this

9 example, the Bayesian shrinkage estimator that it uses,

10 they look at the effects of various forms of voter

11 identification, ranging from nothing is asked for, all

12 the way up to photo identification required. And I

13 believe it's eight separate types.

14 And the point of their article is to use

15 this estimator to ascertain whether, in fact, you know,

16 there is any kind of order to these different -- eight

17 different possibilities, because the assumption is, is

18 that they range from least stringent to most stringent.

19 And the interesting thing from their piece

20 is, that according to their analysis, if you move from

21 categories zero, which is essentially you're not asked

22 for any identification, to category 7 on their scale, or

23 maybe it's 6, because it's eight points, but the next to

24 last category, the more stringent the requirement, the

25 higher the turnout, according to their estimator.






147

1 And then it is only when you -- so, for

2 instance, the -- you know, if you were to follow the

3 Alvarez, Bailey, and Katz piece, the implication would

4 be that all states, if they wish to increase turnout,

5 ought to require -- require I think it's whatever sort

6 of photo ID, so I believe it's photo ID and signature

7 match. It's only when you get to the photo ID, the most

8 stringent form of photo ID, that they claim you see a

9 drop off in turnout. So it's an interesting piece in

10 that regard.

11 And so when Professor Ansolabehere is

12 referring about a 10 point difference, what he's

13 actually referring to is the difference, I believe, from

14 category 6 to 7 on the scale, in terms, where the scale

15 represents the least stringent to the most stringent.

16 Q. I was going to -- just in terms of that, since

17 there are eight categories, and 8 is the most stringent,

18 would we be referring to 7 to 8?

19 A. I'm always confused as to whether I ought to be

20 talking about zero to 7, which would indicate eight

21 categories, or 1 to 8. So the question is, as you move

22 -- let's assume the scale is from 1 to 8. It would be

23 the movement from category 7 to category 8 where you see

24 the drop off in turnout.

25 And, of course, the problem is, is the






148

1 data that Professors Alvarez, Bailey and Katz are using

2 is survey data. They only have two states in which they

3 actually observe the number 8 on their scale in terms of

4 photo ID being required. And the Bayesian shrinkage

5 estimator is an effort to try to get around the issue

6 that they don't really have many cases in these distinct

7 categories. So even though they've got this large

8 survey, they don't have many observations of interest on

9 the variable they are actually talking about.

10 It's my opinion -- I respect Professors

11 Alvarez and Katz. I do not know Professor Bailey. But

12 I think they are terrific political scientists. I don't

13 believe substantively this piece makes much sense.

14 And I would certainly submit that I -- I

15 think the primary contribution of the piece is the

16 introduction of the Bayesian shrinkage estimator as a

17 way to get at some of the issues involved with our data

18 ordinal -- how do you estimate the effects of ordinal

19 data, for instance, order implying relative stringency

20 of photo ID or voter ID laws. Substantively, I'm not

21 sure many people would think that that -- their

22 estimation of effects is plausible.

23 Q. What would make it implausible?

24 A. Their argument, if you take their data at face

25 value, is that a state that requires absolutely no forms






149

1 of identification in order to vote, the turnout in that

2 state is less, is lower, than it would be in a state

3 with this next to highest requirement.

4 Q. And what's the difference in turnout? Is it

5 basically flat?

6 A. I recall -- and this is off the top of my

7 head. I think the relationship between institutional

8 arrangements for voting and turnout is almost nothing,

9 that is, for category 1 to category 6, and then you see

10 an increase, as you move to a photo ID requirement. But

11 I've got to be careful because I don't recall, off the

12 top of my head, specifically what category 7 on the

13 scale was. But it was -- it was just short of the photo

14 ID requirement that you have in Indiana and Georgia.

15 Q. Well, I don't want us to guess here, so why

16 don't we go ahead, and I think I can get us a copy.

17 A. Please.

18 MR. MELLETT: I would like to have the

19 Alvarez, Bailey, and Katz piece that we have been

20 referring to here marked as Exhibit Number 4.


22 Q. (By Mr. Mellett) Please go ahead and take a

23 look at it. Is this the piece you're referring to?

24 A. Correct. So if you, please, turn to Page 29.

25 Q. 28 or 29?






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1 A. 29.

2 Q. 29. Okay.

3 A. And Figure 3.

4 Q. Yes.

5 A. Okay. So do you see the categories listed on

6 the -- on the X axis?

7 Q. I do.

8 A. Okay. The next to last category would be Photo

9 ID Requested.

10 Q. Yes, I see that.

11 A. Turnout -- according to their estimator,

12 turnout is 86 percent. I'm sorry. Probability of

13 voting is 86 percent under that regime, as compared to

14 category 1, State Name, the probability of turning out

15 is .82.

16 MR. MELLETT: Off the record.

17 (Brief discussion off the record.)

18 MR. ROSENBERG: I thought he said 29 of

19 the Alvarez article?


21 Yes, Page 29.

22 MR. ROSENBERG: Because my Alvarez article

23 ends at Page 27.

24 MR. MELLETT: This is -- just to be clear,

25 this is -- the title, "An Empirical Bayes Approach to






151

1 Estimating Ordinal Treatment Effects from Political

2 Analysis in 2011."

3 MR. ROSENBERG: I was looking at the other

4 Alvarez article. Okay. That's fine. Go ahead.

5 MR. MELLETT: All right.

6 Q. (By Mr. Mellett) I'm sorry. I've lost where we

7 were. I believe you were explaining the --

8 A. Yeah. Just saying if you take this seriously,

9 and you look across categories 1 through 6, I think your

10 conclusion would be that if we wanted to increase

11 turnout, we would request photo ID, because according to

12 their estimates, those -- and this is controlling for

13 other factors -- those are the states that see the

14 highest turnout levels.

15 Q. I know that according to Professor

16 Ansolabehere, that the Alvarez data is available. Have

17 you looked at that data?

18 A. I have not.

19 Q. Okay. And so for that first level, in terms of

20 not the most stringent, meaning not the looking at the

21 Indiana and Georgia examples, but do you know what

22 states that they are looking at in that next category?

23 A. No, I don't. I actually had a breakdown of

24 this in my notes at some point. And the reason is that

25 I wanted to figure out how many states they had looked






152

1 at that were in, what I would consider Texas's category.

2 MR. MELLETT: Off the record just a

3 minute.

4 (Discussion off the record from 1:24 to

5 1:27 p.m.)


7 Q. (By Mr. Mellett) So I believe you were saying

8 that you had not had an opportunity to look at the data

9 provided by Alvarez et al?

10 A. Correct. It's CPS data, so it's publicly

11 available, but I haven't looked at it.

12 Q. Okay. One of the things I forgot to ask you

13 earlier is: Do you -- have you taught statistics at

14 all?

15 A. I have taught a class called Applied Survey

16 Research Analysis.

17 Q. Okay.

18 A. Which counts sort as the political methodology

19 sequence at U.T., but it is not -- this is an

20 undergraduate upper division course, but it is not a --

21 it's not the political statistics class.

22 Q. So it's kind of an offshoot of statistics?

23 A. I think that's fair to say, yes.

24 Q. Okay. And what's the textbook you use when you

25 are teaching that?






153

1 A. In that class, I'll actually use a couple of

2 textbooks, but there is one by -- it's Joslyn et al,

3 J-o-s-l-y-n, and it's called, I believe, Applied Social

4 Science Methods.

5 Q. And what's the other?

6 A. That's the one -- I actually use, in that

7 class, the Asher book I had mentioned earlier, Polling

8 and the Public.

9 Q. Okay. So getting back to the literature

10 review, because of the increase, you think, in the --

11 what, I guess we're terming the seventh category, that

12 you think that that renders the rest of the analysis,

13 what?

14 A. I would simply say that I disagree with some of

15 the conclusions they reach based on the data they

16 present.

17 Q. And so in terms of the last category, where --

18 for example, if you looked at the linear relationship.

19 If you had taken the line -- again, we're on Page 29.

20 A. Okay.

21 Q. And you looked at the linear relationship

22 there, in terms of the last category, it's significantly

23 lower than what you would get if you locked at a linear

24 relationship; isn't that right?

25 A. The linear -- yes. The linear relationship is






154

1 almost wholly driven by the photo ID required case.

2 That is to say, what you see in Figure 3 is a slight

3 negative slope; that is, the slope characterizing the

4 overall pattern of the data. If you took out the photo

5 ID required case, that slope would not be negative. If

6 I'm eyeballing it correctly, that slope would actually

7 be positive, indicating that up until the point of photo

8 ID required, the more stringent the requirements, the

9 greater the turnout probability. I think that's a

10 curious finding.

11 Q. Well, in your literature review, is your

12 overall conclusion is that photo ID doesn't have any

13 effect?

14 A. My overall conclusion is that there is no

15 scientifically-reliable evidence to suggest that there

16 is a strong substantive relationship between photo

17 identification and turnout.

18 Q. Wouldn't you expect there to be some

19 relationship between photo ID identification and lower

20 turnout?

21 A. As a layman, I think I would expect such a

22 relationship. As a political scientist, I do not

23 expect, necessarily, such a relationship to exist.

24 Q. And why do you not expect that it would exist

25 as a political scientist?






155

1 A. Our broader theories of voting concentrate on

2 how much people know about politics, how engaged, how

3 interested, and how involved they are, and we find that

4 most Americans aren't terribly interested in politics,

5 aren't very knowledgeable and or very engaged.

6 We don't vote at very high rates compared

7 to turnout in other countries. There are a lot of -- a

8 simple way of saying that is, there are a lot of reasons

9 not to vote in the United States. You're not

10 interested. You don't know the candidates. These are

11 reasons that are actually listed in the report in the

12 citation of the CCES. You know, the weather is bad.

13 The institutional effects of turnout, or

14 the institutional arrangements affecting the election,

15 there's a considerable amount of evidence that those

16 things can affect turnout. But mostly those are

17 referent to broader institutional things, like do we

18 have voting holidays. You know, do you have, you know,

19 extended periods of absentee voting or early voting.

20 Those sorts of arrangements seem to have some sort of

21 impact.

22 The presentation of identification or

23 signature doesn't seem to be much to offer much to

24 dissuade people from showing up to vote. That is to

25 say, nobody listed it as a reason why they didn't vote,






156

1 in most of the evidence I have seen.

2 So, it doesn't surprise me too much that,

3 you know, if you look at these aggregate studies that

4 simply look at the arrangements in the state and the

5 overall turnout rates, that other factors dominate those

6 institutional effects, demographic, attitudinal, et

7 cetera, those things seem to be primary here.

8 Q. Do you think that there is voter impersonation

9 fraud in Texas?

10 A. I wasn't asked to consider that, so it's

11 certainly beyond the purview of my report and my

12 expertise.

13 Could you reframe the question perhaps?

14 Q. I'm not sure how I would reframe it in terms --

15 A. Well, could you re-ask it? I want to make sure

16 you said -- you said in-person?

17 Q. Do you think that there is voter impersonation

18 fraud?

19 A. Impersonation. I'm sorry. Okay. I thought

20 said in-person.

21 Q. Yeah.

22 A. Okay. Voter impersonation or fraud, I really

23 don't have any kind of expertise on that.

24 I can say that the political science

25 literature suggests that there is not much voter fraud,






157

1 in-person voter fraud. And also, if you look at -- the

2 studies suggest that it's a very hard thing to get -- to

3 measure or to establish, anyway, and that's kind as much

4 as I know, I think, on that.

5 Q. If there was a significant amount of voter

6 impersonation fraud, would you expect that photo ID

7 would drive down turnout?

8 MR. HUGHES: Just to clarify, because I

9 want to make sure you're communicating, when you say

10 voter impersonation fraud, does that, in your mind, mean

11 the same thing as in-person voter fraud?

12 MR. MELLETT: In-person voter fraud.

13 MR. HUGHES: Okay. I just want to make

14 sure you're communicating.

15 A. I'm sorry. So what was the question again?

16 Q. (By Mr. Mellett) My question related that if

17 there was a significant amount of in-person voter fraud,

18 would you expect that photo ID would decrease overall

19 turnout?

20 A. Oh, okay. I thought you were going to ask

21 would it decrease fraud, but would it decrease turnout?

22 Well, it strikes me -- my understanding is that

23 in-person voter fraud is not terribly extensive, at

24 least we don't have a lot of evidence for that in

25 political science. So my sense, from SB 14, is that it






158

1 wouldn't have an appreciable impact on turnout.

2 Q. And likewise, you said you didn't take a look

3 at whether it would have an affect on fraud; is that

4 correct?

5 A. Correct.

6 Q. In the literature review that you did, you

7 noted that Hood and Bullock showed that minorities are

8 less likely to have voter ID in Georgia than White

9 voters; is that right?

10 A. That's correct.

11 Q. Okay. And I think that you had also cited

12 Barreto, Nuno, and Sanchez --

13 A. Correct.

14 Q. -- in Indiana that showed that Black voters are

15 less likely to have required voter ID; is that right?

16 A. That is correct.

17 Q. Okay. Are there any other states, other than

18 Indiana and Georgia, that have stricter voter ID

19 requirements?

20 A. Stricter, so we're here to referring photo ID?

21 Q. Correct.

22 A. Several are in the works, but my understanding

23 is that through 2010, we only had data from Indiana and

24 Georgia on this particular -- those states are the only

25 states that have these particular arrangements.






161

1 one had an acceptable form of ID after the fact. We're

2 not confident in that anymore, and we simply want to be

3 accurate in our understanding of that law.

4 Q. Just sticking with Indiana and Georgia for a

5 minute, demographically, is the demographic makeup in

6 Texas similar to Indiana and Georgia?

7 A. In some ways, but in some ways not.

8 Q. Can you tell me how it's similar and how it's

9 different?

10 A. I was planning to. The similarity is that --

11 and again, this is compared to the possible combinations

12 of other states that you might compare. There are quite

13 a few states, obviously, that have very, very limited

14 ethnic minority populations, racial or ethnic minority

15 populations. But in the case of Georgia and Indiana,

16 you have fairly considerable minority populations.

17 That's the similarity. Texas does as well. The

18 difference, obviously, is, is that it's predominately

19 African American in Georgia and in Indiana, whereas in

20 Texas, there is a sizeable African American population,

21 but the predominate minority here are Hispanics.

22 Q. On Page 5 of your report, you say that in terms

23 of -- that are some studies that suggest that imposing

24 new voter ID requirements may have a negative impact on

25 turnout. What were those studies?






162

1 A. Can you point me to the line you're referring

2 to?

3 Q. Sure. It was -- let me make sure that I'm on

4 -- oh, where did it go?

5 MR. HUGHES: You're at the very bottom,

6 Tim.

7 MR. MELLETT: Yeah, I see it now. Okay.

8 Q. (By Mr. Mellett) Do you see where that is?

9 A. Yes, I do. So it would be the next to last

10 paragraph, I guess the last full paragraph.

11 Q. Yes. Okay. And my question is, is what are

12 those studies that you looked at?

13 A. Yeah. Actually, the studies that I'm referring

14 to here are studies that were cited earlier. So for

15 instance, the Barreto piece and the earlier, the 2008

16 Alvarez, Bailey, and Katz piece. So it's -- when I say

17 some studies suggest, the suggestion is actually the

18 back end of those studies.

19 Q. Okay. So there isn't any additional studies

20 that you're alluding to but not citing?

21 A. No.

22 Q. Okay. Have you looked at the rebuttal reports

23 that have made you aware of additional studies?

24 A. I have looked at the rebuttal reports from

25 Professor Ansolabehere, Professor Marker, Professor






164

1 who --

2 A. Professor Ansolabehere.

3 Q. -- who referenced the 33 studies. There were

4 specific studies cited by Professor Lichtman.

5 A. Correct. Five of them have been published in

6 peer review journals. As I said, my analysis was

7 largely limited to pieces that have subject to peer

8 review processes.

9 Q. So I guess one of the questions I have about

10 peer review process is that wouldn't that, by

11 definition, mean that you're looking at older data?

12 A. Yes. That is correct. There is a lag time.

13 Q. And, in fact, on the information that you're

14 citing, doesn't it really look at 2006 and earlier?

15 A. Most of -- most of the cases are 2006 or

16 earlier, which, of course, is why the CCES data, which

17 is conducted not only in 2006, but similar, but not

18 entirely similar studies in 2008 and 2010, are data from

19 2008 and 2010 were important to the report.

20 Q. But in terms of the studies, you're looking at

21 basically 2006 and earlier, correct?

22 A. Correct, because after that point -- and there

23 are some exceptions. The Alvarez, Bailey, and Katz

24 piece was published in 2011, although it is dealing with

25 2000 and 2006 data. There have -- the paper is






165

1 analyzing data from more recent election cycles, to the

2 extent they're out there, are still working papers and

3 may be undergoing the peer review process.

4 Q. Is it your assessment that these working

5 papers, if they haven't been fully reviewed by peers,

6 should carry less weight?

7 A. As a general matter, yes, I personally give

8 less professional weight to papers that have not gone

9 through the peer review process.

10 Q. And so the information, is that why you don't

11 list any of these other papers in your report?

12 A. No. As I suggested, that some of the papers do

13 make it in. As you suggested, they tend to be a little

14 older because they're referenced in the peer review

15 publications. But in an area like this, I think you

16 have to be discerning. A lot of these papers that are

17 cited, you know, for instance, in Professor

18 Ansolabehere's citation of 33, most of those are

19 reviews. They do not actually contribute original data

20 to the question; they simply review information that's

21 out there.

22 Some of them are polemical. They are

23 published by organizations, some professional and

24 serious, some much more oriented towards advocacy that

25 don't particularly seek to engage the question in an






168

1 study. I believe upwards of 30 universities and

2 colleges participated, and some of the usual suspects,

3 Michigan, Harvard, Stanford, Princeton, UCLA, Berkeley,

4 places like that.

5 Q. One of the things that you reference, and this

6 is on Page 7 of your report, is that you had mentioned

7 that in terms of voting behavior, for example, in 2008,

8 that 87 percent of the respondents had successfully

9 voted and 79 percent did so in 2010. And I guess that's

10 -- part of it has to do with my question about who the

11 population is that -- because, for example, you say

12 well, 10 percent didn't vote. So who is it that is

13 responding?

14 A. Right. What we have here is a sample that's

15 weighted to American Community study specifications of

16 the American population. So in other words, the sample

17 against which -- from which they're drawing these

18 inferences is representative according to census

19 information.

20 What tends to happen, in surveys like

21 this, is that when you ask people if they voted, a

22 straight did-you-vote question, you will sometimes get

23 what we call an overreport. So people who didn't vote

24 may say they voted. This happens when you have what we

25 refer to as a socially desirable behavior. And since we






169

1 think there's some kind of positive norm associated with

2 voting, people who didn't vote might claim that they

3 did. So -- and it's just difficult from the outside

4 because people look at the survey and they say, well,

5 this is -- you know, the reported voting rates are, you

6 know, 87 percent or 80 percent, and we know that

7 nationally about, you know, 75 percent of registered

8 voters and 60 percent of all, you know, eligible adults

9 voted in the election.

10 There have been a number of studies about

11 the consequences of overreporting. On our models of

12 turnout, for instance: How can you model turnout if so

13 many people say they voted? And most of that literature

14 concludes that what you get is a slight effect, and the

15 slight effect is that it exaggerates what we call the

16 predictable correlates of the vote. And that is to say,

17 when you look at the self-reported vote and you're

18 trying to predict it, income, age, education are more

19 highly correlated than they would be with the actual or

20 validated vote. And the social science explanation is

21 that these are people who place kind of value on voting

22 and are more likely to say they voted when they might

23 not have.

24 The substantive effect is, therefore, is

25 that when we run these models of voting, we get slightly






170

1 higher, not -- I want to be clear -- not significantly

2 higher, but slightly higher estimates of the correlates

3 of things like age, education, income. And, you know,

4 the simple version is, we think those are people who are

5 a little ashamed about not having voted and are more

6 likely to suggest that they did when maybe they didn't.

7 Q. I guess, according -- tell me if this sounds

8 right to you: That according to the Secretary of State

9 in Texas in 2008, they estimated voter turnout at 45.5

10 percent. Does that sound about right to you?

11 A. Of the voter age population or the voter

12 eligible population?

13 Q. I would have to go back and look. I don't -- I

14 don't know if -- between the two. Well, you tell me

15 what you would know about that.

16 A. It sounds like the voting age population. The

17 voter eligible population purges people who are

18 institutionally incapable of voting, but are sometimes

19 left in the denominator incorrectly. So people who are

20 incarcerated, people who are institutionalized, et

21 cetera, who, in the state of Texas, are not allowed to

22 vote should not be counted as nonvoters since they're

23 not allowed. And I know it sounds trivial, but it

24 actually tends to have a 3, 4, 5 percent impact on your

25 estimated turnout. In a state like Texas, with a






172

1 rates in the samples. As a matter of fact, it's not the

2 case. Therefore, you're left with another explanation,

3 which is that whoever is included in the sample are

4 simply, you know, more likely to say they voted when

5 perhaps they didn't.

6 Q. How do you deal with the problem of people not

7 telling the truth in phone samples?

8 A. In the case of voting, we have a validation

9 possibility. That is, I certainly check how you voted,

10 but I can look and see if there's a record of you having

11 participated in the election. This is difficult to do

12 for some of reasons we've encountered in this case

13 generally, which is matching a person to some other

14 voter. Registrar lists can be -- can be tricky

15 sometimes. But, in fact, in Professor Ansolabehere's

16 initial report, he talks about how Catalist was used to

17 validate data, voting data, in, I believe, the National

18 Election Study, in the most recent version, so the 2008

19 National Election Study.

20 With respect to opinions, it's not really

21 an issue; that is, your opinion is what is. The

22 question of overreporting comes into play with respect

23 to behavior. And it's more of an issue with behavior

24 that has strong social desirability primes. I hate to

25 lapse into lingo, but prime simply meaning that you're






173

1 -- that there's a strong reason to think that -- or a

2 reason to think that there might be a strong impulse to

3 say you engaged in certain behavior when, in fact, you

4 didn't. And so we think that voting is one of those

5 sorts of behaviors.

6 Q. Is saying that you have an ID one of those

7 sorts of behaviors?

8 A. It's an interesting question. It's not clear

9 to me why people would claim they have an IDD if they

10 didn't. It's conceivable, I suppose, that people might

11 be embarrassed. But, of course, you recall that we

12 asked a series of these questions about ID possession,

13 and I think in most of these instances, any social

14 desirability norm is very, very difficult to discern.

15 So, for instance, you know, we ask not

16 about driver's license, but passports, about citizenship

17 identification and about license to carry, and what I

18 would notice is that you'd get a kind of predictable

19 variance in the responses as you go across those. In

20 other words, you know, you'd get more people saying they

21 have driver's licenses and significantly fewer saying

22 they have these other forms of ID. The variance is

23 sensical across racial or ethnic groups; that is to say,

24 Hispanics are more likely to say they have visas or

25 passports and citizenship identification.






174

1 So I think it's unlikely that there's much

2 of an upward bias here with respect to that, at least I

3 can't see the theoretical reason why that would be the

4 case.

5 Q. Let me ask you about the passport and

6 citizenship certificate. For somebody who is Hispanic

7 and they're being called on that, do -- particularly if

8 they're concerned about such a thing, you know, for

9 example, they may not have identification, but, say but

10 you know I'm here. I'm, you know, valid. I should be

11 here. You know, I'm not in any way a noncitizen, but

12 I'm concerned about saying that I don't have the ID

13 because somebody may say well, therefore, you aren't a

14 citizen. Is that a concern?

15 A. Right. Right. I think it's always -- I mean,

16 the sensibilities of Hispanic respondents is an issue

17 across the board, even with respect to the introduction

18 and making sure that they have an option to have a

19 Spanish interview, for instance, you know.

20 I think, again, what gives us comfort in

21 the data is that, you know, we're asking across a range

22 of these different forms of identification. So what's

23 unclear to me is that you would claim, say, you know, to

24 have a driver's license, which most Hispanics do in this

25 survey, and then also feel compelled to say I have a






175

1 passport and/or citizenship papers. In other words, I

2 certainly can see that this is something we want to be

3 attentive to, but it wasn't clear to me that that was

4 what was going on with the data.

5 Q. Is there any way to control for that, or to

6 check it?

7 A. Other than, you know, we -- we're very

8 concerned, obviously, about assuring anonymity in the

9 survey, so people would feel free to express their

10 opinions. And so the only way to do it would be if you

11 trapped specific individual information that allowed you

12 to identify the respondent, and then checked the record.

13 And we discussed this, but we're really

14 insistent -- and this part is almost exclusively my

15 fault or call, if you will -- I thought it was

16 absolutely crucial to the integrity of the data that we

17 able to assure people their responses were anonymous.

18 And so we didn't trap that information, so we now do not

19 have the capacity to go back and check the records.

20 Q. If the survey had not been anonymous, what

21 potential bias would you have?

22 A. If it -- we think that the kinds of things

23 you're talking about, that is, perhaps noncitizens,

24 perhaps people who, you know, are, you know, living with

25 noncitizens or recently-established residents would be






176

1 very reluctant to participate.

2 My experience has been that when you get a

3 call, especially even though the caller identifies his

4 or herself from Sentis Research, we're doing an academic

5 study, et cetera, that any official-sounding call from

6 an unknown source can spook people. And so we thought

7 it was important to -- not only to correctly identify

8 who we were and where we were from, but also to make

9 sure that respondents were comfortable participating in

10 the survey.

11 Q. One of the things you had noted in the CCES

12 study, in particular, was in Indiana where people

13 with -- I guess it was, if you take their first or

14 second reasons -- I'm actually referring to Page 15.

15 First or second reasons, that they -- that there are --

16 I think the 1 percent are first reasons, 7 percent are

17 second reasons, and they indicated that they did not

18 vote because they didn't have a proper form of

19 identification. And I guess my question on that is:

20 When people are listing first and second reasons, should

21 we add them together as reasons not to vote as to why

22 they didn't vote?

23 A. So we're referring here to Tables 1, 2, and

24 then I guess 3 and 4 of Exhibit A? Exhibit 1?

25 Q. It's, yeah, of Exhibit 1, and yes, we're






177

1 starting with Table 5 -- Table 6 on Page 15.

2 A. All right. So then the question would be,

3 again, is it -- correct me if I'm wrong -- is it

4 legitimate or would it be reasonable to simply add

5 anyone who mentions in these multiple probes, anyone who

6 mentions not having the correct form of identification,

7 to sum them together as an estimate of the total number

8 of people who may not have voted because of that?

9 Q. Correct.

10 A. Yeah. I think that's not unreasonable.

11 Q. In terms of --

12 A. May I backtrack just slightly on the last

13 statement?

14 Q. It's --

15 A. Sorry.

16 Q. I obviously want you to tell me what you feel

17 comfortable with.

18 A. Sure. I would just say that the backtrack is:

19 It does somewhat depend on the response on the first, on

20 their first question. You know, so, for instance, if I

21 said I was out of town, and then I didn't have the

22 correct form of identification, I'm not -- I'm not quite

23 sure what I would make of that.

24 You know, if it was -- conversely, if, you

25 know, if I said I was sick or disabled, or, actually, by






178

1 the same token, if I'm sick or disabled, and then I said

2 I didn't have the correct form of identification, I

3 mean, I'm not quite sure what I would make of that. I

4 would tend to go with the first response as kind of

5 being the more compelling. But, again, it depends. So

6 it's a small caveat. I'm sorry to slow us down, but I

7 just wanted to say I'm -- I think it's not -- I still

8 think it's not unreasonable, but I'd like to look at the

9 first reason, and then make a judgment as to whether the

10 second ought to be added.

11 Q. Looking at Figure 6, which is on Page 16, the

12 -- it indicates there that in terms of persons who are

13 asked to show identification, that it's 60 percent in

14 Texas. Do you see that?

15 A. Correct.

16 Q. Okay. And that's -- and I guess I'm not sure.

17 Is that 60 percent referring to the 87 percent who

18 voted, or is that our total?

19 A. I believe it's -- I believe it's 60 percent of

20 people who stated they voted.

21 Q. Okay. And the -- it's 99 percent in Indiana

22 and Georgia. I guess in terms of predictive quality,

23 would you expect that Texas would then increase to 99

24 percent?

25 A. I think that's probably a reasonable inference.






179

1 Q. Would you consider that difference significant

2 if 39 percent more of the population is being asked for

3 ID?

4 A. Significant in what sense?

5 Q. Well, I guess in the sense of if you added an

6 additional 39 percent of the population that isn't being

7 asked, would it -- would it matter in terms of turnout?

8 A. Oh, with respect to turnout. I don't know that

9 there's much evidence to suggest it's going to have much

10 of an impact on turnout.

11 Q. Do you have any concerns about the predictive

12 quality of the states that have gone before, since Texas

13 has a more stringent voter ID than any of them in SB 14?

14 A. I think you always have concerns when you have

15 only two cases upon which to draw some kind of relevant

16 history here or set of inferences. And I think details

17 do matter. So I think, yeah, I would concede you have

18 concerns about extrapolating from, you know, these

19 previous cases.

20 On the other hand, this is what you have.

21 And in my case, you know, I was asked to kind of -- to

22 take a look at the literature, take a look at the

23 existing data, and the existing that are relevant really

24 are from Indiana and Georgia.

25 In Professor Ansolabehere's rebuttal, he






180

1 sort of castigated me a little bit for not offering

2 predictions, which I think I did, but they were kind of

3 -- they were kind of couched in language, because, you

4 know, Texas -- Texas will only be the third instance --

5 maybe some others go simultaneously -- but only the

6 third instance in which this has been the case. And so

7 I think you're always concerned about that.

8 MR. MELLETT: I think now would be a good

9 time to take a break. Let's take a five-minute break.

10 (Recess from 2:09 p.m. to 2:21 p.m.)

11 Q. (By Mr. Mellett) Professor Shaw, I -- you had

12 asked me before about the cite, and I thought I have the

13 study with me, but I don't, regarding the one I cited

14 before on, and this was --

15 A. The Borreto case?

16 Q. Yeah. Correct. And the -- this was dealing

17 with the disproportionate impact of voter ID laws on the

18 minority electorate. And I had the date written down

19 here as August 2011, but I don't see it here, but that's

20 not something you recall reviewing anyway.

21 A. No. I believe I saw it mentioned in one of the

22 reports but I hadn't read it.

23 Q. Okay. And while we're on that, the -- one of

24 the reports which is similar, this is Sanchez, Nuno and

25 Borreto, and this is, the title of it is "Racial and






187

1 in Spanish?

2 A. Yes. I know the percentage.

3 Q. Okay.

4 A. The percentage was, let me refer here to

5 Exhibit 2, I believe.

6 Q. It's on Exhibit 2?

7 A. Yes. On Table 3. You see listed in Shaw

8 Hispanic Survey 1, 34 percent of the interviews were

9 conducted in Spanish.

10 Q. Okay.

11 A. And then on the Hispanic survey using the

12 Ansolabehere list, 33 percent of the interviews were

13 conducted in Spanish.

14 Q. And those are the ones that were completed,

15 right?

16 A. Correct. Correct.

17 Q. The -- let me refer to Page 19 of your

18 report. And the question I have, and this is in dealing

19 with the weighting, it is in the second paragraph, and I

20 don't know, it's I guess the third sentence down, where

21 it starts, "In this case," do you see that, "In this

22 case, although we possess information"?

23 A. Yes.

24 Q. Okay. There you gone go on to say, "It is

25 unclear that this population is properly identified."






188

1 What do you mean by that?

2 A. Is this the -- I'm sorry. Let me make sure

3 that I'm clear. Is this the original report?

4 Q. This is the original report. Page 19 of 48.

5 A. Okay. I just wanted to make sure.

6 Let me say that I'm not quite sure. There

7 are two possibilities with respect to the language, and

8 I'm not sure which was running through my mind when I

9 wrote the report.

10 The first is that we did not have a full

11 demographic profile of the at-risk population. That is

12 to say, normally with census data, so it would be the

13 American population, you have gender, race, education,

14 et cetera. And for the initial Secretary of State's

15 identified list of 800,000, we obviously didn't have

16 that information. So I'm not clear, though, whether I

17 was referring to that -- in other words, it's not quite

18 clear what the entire sample population is supposed to

19 look like -- or whether I was referring to the

20 possibility that the list itself might -- there might be

21 questions about whether this was the entirety of the

22 population. I'm not sure which of those prompted that

23 specific comment. But again, that's why we include

24 both, to the best of our ability, the weighted as well

25 as the unweighted numbers.






189

1 Q. The Footnote 5, which talks about socioeconomic

2 status and dealing with response bias, you didn't weight

3 for socioeconomic status in any of the surveys, right?

4 A. No.

5 Q. Do you sometimes weight for socioeconomic

6 status in your surveys?

7 A. Actually, I tend not to. I tend to use two

8 forms of weights, a race-region weight. That is to say,

9 in the case of the American -- a sample of the American

10 population: South, nonSouth, Black, White populations,

11 so you're anticipating four cell entries.

12 In the case of Texas and in the case of a

13 Texas poll, it would be a different regional breakdown,

14 but it would be Hispanic-Anglo. So race-region would be

15 one and age-gender is the other.

16 What tends to happen is that when you

17 weight by race-region and by age-gender, your

18 socioeconomic variables balance out. That is, in other

19 words, they look fine. They match the population that

20 you're interested in. So I have not tended to do that,

21 you know, just as a matter of course.

22 Q. The -- one of the questions that I saw that

23 were included in both surveys is that you had included

24 information on renting or owning. Why do you include

25 that?






192

1 percent for Texas.

2 A. Sure. All right. The -- the point estimate

3 here is 20 percent. It's a 600-person sample, but I

4 believe 520 people self-identify as African American out

5 of that. So the margin of error off of that is probably

6 about 5 points. So you know, it doesn't particularly

7 bother me. It's higher than the average population, but

8 recall, of course, that this isn't the average

9 population, this is a subset of it. And it's not that

10 far off, given the plus or minus error term.

11 Q. Okay. Why don't I go ahead and introduce as

12 Exhibit Number 5, the Rebuttal Expert Declaration of

13 Daron Shaw.


15 Q. (By Mr. Mellett) And while I'm doing exhibits,

16 why don't we just do Exhibit Number 6 , I believe, which

17 is the incidence report that you had also provided along

18 with that.


20 Q. (By Mr. Mellett) In Exhibit 5, which is the

21 rebuttal declaration, in terms of -- if you can look at

22 Table 1 on Page 7, and I guess what I want to refer you

23 to is in terms of the disability of looking at the Black

24 sample that we're looking at, where we've got -- do you

25 see where it's 41 percent for the Social Security






193

1 Administration and 20 percent for Veterans' Affairs?

2 A. Yes.

3 Q. Okay. I guess my question is: Compared to the

4 ACS survey, it seems that disabled persons are

5 significantly overrepresented, and does that cause any

6 concern for you?

7 A. Yes. Yes. That number seems high. I'll check

8 on that, make sure that's accurate within the sample.

9 Q. Would we also have the raw data on that --

10 A. Yes.

11 Q. -- to be able to check?

12 A. Yes.

13 Q. Okay. The -- in terms of a -- if the number is

14 accurate, if we look at it and we find the number is

15 accurate, do you have a concern regarding any sort of

16 response bias?

17 A. Not particularly. I mean, I think it's hard

18 for me off the top of my head to think of a way in which

19 this question could be misinterpreted. But perhaps when

20 people hear Social Security Administration, they think

21 we're asking about, you know, something besides actual

22 potential of a disability, maybe that, you know, they

23 receive some sort of benefit from Social Security. It's

24 speculative, but the answer strikes me as being too

25 high.






199

1 Ansolabehere sample.

2 Q. Well, right. But you didn't weight that

3 sample, did you?

4 A. No.

5 Q. Is that --

6 A. The weighting --

7 Q. So we don't know what the weight would be, do

8 we?

9 A. That's correct, we do not know what it is. But

10 you know, the sort of point remains the same, though,

11 which is it's possible that the effect would be -- there

12 would be an effect on the driver's license. It's also

13 possible that the full sample doesn't need a lot of

14 weighting. We just don't know in the case of the

15 Ansolabehere sample.

16 Q. And let's look at Table 9, and this is Exhibit

17 1, the original report, compared to Table 1 in Exhibit 5

18 regarding the Hispanic sample there. Whether, I guess,

19 if you have unweighted, it's 76 percent. If it's

20 weighted, it's 78 percent. Compared to 68 percent. The

21 fact that that is 10 percentage points lower, does that

22 cause you concern?

23 A. No. You recall that there's -- both Hispanic

24 sample -- both Hispanic samples are 600 persons each, so

25 you're talking about a margin of error, plus or minus 4,






201

1 A. To Table 8?

2 Q. So to Table 8 and Table 9.

3 A. Table 8, okay.

4 Q. Table 8, as you're looking at the full sample.

5 Table 9 is you're considering the Hispanic.

6 A. So the estimate that you're comparing then

7 would be 10 percent in the full sample in Exhibit 5,

8 Table 1, versus either 4 or 5 percent in Table 8,

9 correct?

10 Q. Correct.

11 A. No, I don't find that particularly troubling.

12 Q. So again, I guess that's plus or minus 3, so

13 you figure that that makes it barely?

14 A. Yes.

15 Q. Because in terms of looking at the other one?

16 A. Yeah, it's fairly close.

17 Q. Okay. I had a question about the Black

18 sample. One of the things, and I guess this goes to

19 Footnote 7. It's on Page 6. And you talk about the

20 number of people who identify as Black, in the Black

21 sample, and it's 406. And so that you say that the

22 information that you'll be using is for that 406, not

23 for the 600, correct?

24 A. Correct.

25 Q. Okay. Doesn't that change the margin of error?






202

1 A. It does. It does.

2 Q. And so I believe when we were talking earlier

3 that that would change it to about plus or minus 6

4 percent?

5 A. Correct.

6 Q. Were there any thoughts of trying to make sure

7 that you had 600 Black respondents?

8 A. We did not anticipate what the match rate would

9 be for -- from the Catalist data, so it frankly did not

10 occur to me to ask for 700 or 800 matches using the race

11 question as a screener question. It might have been a

12 little problematic, because when you ask -- you tend to

13 ask people race late in the survey, because for some

14 people, giving up that information can be a little

15 sensitive, and some people even terminated interviews.

16 So we aren't particularly comfortable asking the race

17 question at the front end. We tend to ask it at the

18 back end of the question. So -- I'm sorry, the short

19 answer is we did not consider the extra 200 cases.

20 Q. The -- if I can refer you to Exhibit 6, and

21 this is also in reference to Exhibit 5. But in terms of

22 the -- do you see -- if you can get on the same page

23 where it says "African American Sample Disposition

24 Report"?

25 A. Yes.






203

1 Q. Okay. And one of the things that's on there is

2 "Wrong Number." Do you see where that is down -- I

3 think it's 96?

4 A. Yes.

5 Q. And that's at 10 percent. Are you concerned

6 about that number?

7 A. Not especially.

8 Q. Have you compared it to the other numbers where

9 it's -- where's those numbers are, you know, different?

10 A. So that would be 6 percent in the general

11 sample and --

12 Q. Right.

13 A. -- and 8 percent in the Hispanic sample. Not

14 particularly.

15 Q. And in terms of -- now, these are, in dealing

16 with the appended phone numbers, these are supposed to

17 mean matches, right?

18 A. I'm sorry? Say that another way.

19 Q. This goes back to the Exhibit Number 2 where we

20 are looking at the append rate of 35 percent. Does this

21 mean the append rate is actually lower because you've

22 got an additional 10 percent that were wrong numbers?

23 A. Yes. That would mean that some numbers that

24 were appended were not, in fact, correct numbers.

25 Q. So --






204

1 A. But by the way, I should point out, the append

2 rate is -- you know, that is the -- it's a look-up

3 rate. It's not guaranteed to be a successful look-up

4 rate. In fact, I don't know append numbers that take

5 into -- nobody has reported append numbers that I'm

6 aware of that takes into account wrong numbers in

7 calculating the append rate. Now, they probably should,

8 but that's not standard practice anyway.

9 Q. Now, one of the things that you had mentioned

10 in general is that -- that this is for land lines, and

11 so it doesn't take cell phones into account; is that

12 right?

13 A. Correct.

14 Q. And what effect do you find by not taking cell

15 phones into account?

16 A. There's been a lot of research conducted on

17 this lately. We find that cell phone populations tend

18 to be younger, tend to be slightly more ethically

19 diverse, that is, slightly higher percentages of African

20 Americans and Hispanics, and that, in political terms,

21 they tend to be a little more -- or a little less

22 engaged, a little less interested. And I think this is

23 a finding that's fairly common, commonly known now in

24 the public opinion literature.

25 Q. Do you have any idea of what percentage of now






205

1 homes have land lines still?

2 A. I know the percentage of people who are cell

3 phone only, and that's roughly 22 percent nationally.

4 Q. And do you know for Texas what it is?

5 A. I do not.

6 Q. Is it that something that you take into

7 consideration when you are surveying in general?

8 A. Yes.

9 Q. And how do you take it into consideration?

10 A. We usually supplement state-wide surveys or

11 national surveys with what we call a cell phone

12 supplement. That is, if we're doing a survey of a

13 thousand, we'll do 200 cell phone interviews and 800

14 land line interviews. And then we will weight those two

15 populations according to a set of specifications,

16 because the cell phone population doesn't look like the

17 rest of the population.

18 Q. Is there a reason why that wasn't done here?

19 A. Yes. Cell phone numbers are extremely

20 difficult to look up, and it's extremely expensive.

21 It's also the case that the response rates are much

22 lower for cell phone calling because people have an

23 opportunity to -- you know, they know that they're

24 paying for the call, the cost, and they tend to screen

25 out calls coming in. So, you know --






206

1 Q. And I know you already had 2 percent in your

2 response rate though. And that brings up a good

3 question is, is there a level --

4 MR. HUGHES: Wait. Were you finished with

5 your answer?

6 MR. MELLETT: Oh, I'm sorry. I didn't

7 think I cut him off, but --

8 A. I think that's adequate. Yeah.

9 Q. (By Mr. Mellett) Okay. The -- because,

10 obviously, if you want to say more, you can always say

11 more.

12 MR. HUGHES: I wasn't sure.

13 MR. MELLETT: I thought he was done.

14 Q. (By Mr. Mellett) The -- but it does raise

15 that, in terms of the 2 percent, is there a level at

16 which the response rate gets so low that you say, okay,

17 that's just way too low?

18 A. I don't think there's a standard level. It

19 depends on the population you're interviewing. And as I

20 said, it depends very much on the back end, that is,

21 once the data become to come in, do the data seem to

22 reflect the underlying population.

23 Q. Now, one of the things that I've seen, actually

24 on your website, is indications of callbacks. When do

25 you decide to call back and when don't you call back?






207

1 A. You mean with respect to the interview process

2 here?

3 Q. Right. That I -- well, I think I saw it on the

4 Lyceum site, and I think it was in 2009, actually, is

5 that where you said that we did calling back and talked

6 about that process.

7 A. Right.

8 Q. When do you decide to do that versus not

9 calling back?

10 A. Well, all of these surveys involve callbacks.

11 The question that's germane is how many callbacks before

12 you basically decide that is a refusal. And in the

13 Lyceum poll, for instance, one of our sort of points of

14 pride, since it's a very what we call a slow-burn

15 polling project, that is, we can leave it in the field

16 for a fairly significant period of time, because our

17 questions don't tend to be time-sensitive, is that we do

18 multiple callbacks. And the idea is that I may not get

19 you on the first call, but if I call two, three or

20 four -- on the fourth time, I may actually get the

21 person originally selected. And so it is an effort to

22 get at this issue of response biases, to get the people

23 that you randomly selected in the first instance.

24 And for the project at hand, however,

25 there were time constraints such that we weren't in a






208

1 position of doing -- I think with Lyceum, we do as many

2 as five callbacks. We simply didn't have the time or

3 resources to do that for this survey.

4 Q. Do we know how many people were called back

5 here?

6 A. I believe there's a callback entry here. In

7 the general sample, it says 582. This is Exhibit 6.

8 Q. And what does that number mean?

9 A. That means that you actually identified the

10 person or reached a number and either talked to that

11 person or arranged to call back with somebody at that

12 house and then subsequently called back, so...

13 Q. And they can also be part of the completed --

14 A. No.

15 Q. -- or they would not?

16 A. No. Callback here simply indicate people who

17 were called back but they're -- you know, that was the

18 last status before the project was completed.

19 Q. So it was arranged maybe, for example, to say,

20 "Hey, can you call me tomorrow?" They didn't call, you

21 know -- and they couldn't call tomorrow because it was

22 due that night?

23 A. Correct.

24 Q. Okay.

25 A. So the total number of callbacks actually






209

1 involved in the project is going to be significantly

2 higher. It's -- you have to have a single designation

3 here for what -- you know, how a particular case was

4 treated.

5 Q. Is it the case that, in terms of phone surveys,

6 that the longer you have to do them, that the better and

7 more careful the survey will be?

8 A. I think you would prefer to have multiple

9 callbacks to reduce this issue of response bias. Again,

10 the tradeoff is expense and timing. And there's a

11 considerable amount of research come out lately. I

12 mentioned earlier the Pew Report dated May 15th, that

13 analyzes some of these issues, particularly response --

14 response rates.

15 And you know, the good thing from our

16 perspective as social scientists is that, even though

17 response rates are declining across the board, does seem

18 to be that the quality of the samples hasn't really

19 deteriorated much. And there are a variety of metrics

20 they use for judging that. But I think that's

21 something -- that's something that people need to be

22 aware of in their general discussion of polls and in the

23 specific consideration of what we're doing here.

24 Q. So in terms of percentage, because I -- you

25 know, looking all at all of the percentages in terms of






210

1 the ones that were complete, the fact that, you know, as

2 you've got, in general, most of them, and I guess I

3 would refer to Exhibit Number 2 here in terms of

4 completion rate, that first page?

5 A. Uh-huh.

6 Q. So the fact that most of them -- well, they're

7 all between 2 and 2 1/2 percent; is that right?


9 Q. Okay. And have you ever had another survey

10 where you've had a completion rate that's lower than

11 that?

12 A. Not to my recollection. I should -- I've never

13 been involved in a survey of what I would refer to as

14 such a low incidence population, as a difficult to reach

15 survey. I've had ones that are reasonably difficult to

16 reach, but not quite on this order.

17 Q. So if -- based on our earlier conversation, you

18 would get reports on this nightly, would that be right?

19 A. Yes.

20 Q. Okay. And so when you got the first report,

21 for example, dealing with your original survey, did you

22 change any of your instructions based on the low

23 response rate you were getting?

24 A. We got a call from Adam Dipaula, D-I-P-A-U-L-A,

25 at Sentis Research, saying that they had anticipated an






214

1 to get older people. In this sample, I would have to

2 look. I don't readily recall whether we consistently

3 did weekend interviewing or not.

4 In Texas -- this is something I've learned

5 since I've come here -- you have to be very careful

6 about calling on Saturday night and Sundays, that you

7 will offend people and they will not complete your

8 survey because they think you've messed with them. In

9 fact, in some places in Texas, East Texas, Wednesday

10 night is church night. And we've -- I've done some

11 races where we do not interview on Wednesday nights,

12 because we will not only not get respondents, we will

13 get people angry.

14 Q. So -- and that was my next question, is whether

15 you did do any calling on the weekend here.

16 A. I'd have to check the record.

17 Q. For these -- for either of these surveys.

18 A. I'd have to check the record. I frankly didn't

19 give it as much consideration as I would with a

20 political survey, you know, a partisan or campaign

21 survey of some sort.

22 Q. The -- the contact rate that you listed --

23 again I'm back on Exhibit 2 -- is that just they've

24 reached somebody on the phone? What is that?

25 A. Right. As you see in the exhibit -- I'm not






215

1 sure, we have two definitions here. We need to expunge

2 one, right?

3 Q. That was part of my confusion.

4 A. Yeah, there should be one. I believe the first

5 listing, the first asterisk listing here is the correct

6 one. And this isn't my exhibit. I've gone to my sheet

7 here. The first definition, I believe, is the one we

8 wanted. Percent of households in which an adult. So

9 that would be reference to the Pew study listed here in

10 the final column.

11 Q. Okay.

12 A. Or a target respondent. So these would be the

13 Texas studies that we conducted was reached. So it's an

14 effort to render the Pew number here comparable to the

15 Texas data.

16 Q. What accounts for the difference between a

17 contact rate of 62 percent with Pew and the contact rate

18 that we're seeing here between 19 and, what, 25.5?

19 A. Right. The fact that the locations we're

20 calling, the numbers we're calling, that these are not,

21 you know -- there's a couple of things going on. These

22 could be calls to numbers where that individual used to

23 be but has moved. Since we're by definition talking

24 about a more mobile kind of more off-the-grid

25 population, that's reflected in these contact numbers.






216

1 The other thing is, as is indicated in the

2 definition itself, is that it's a list versus a

3 traditional survey. A list means, when I call your --

4 if I pick your name, I need to contact you and interview

5 you. In a Pew study or something of that sort, it's a

6 national survey in which they're calling a household and

7 asking may I speak to the oldest registered voter or the

8 voter with the next birthday at this household. So the

9 selection process is such that you're more likely to get

10 a respondent that you are when you're doing list-based

11 sampling.

12 So those are two reasons: The nature of

13 the population, and then the fact we're doing list

14 versus an RDD, a random digit dial sample.

15 Q. In terms of contact, people that -- who was

16 your contact person at Sentis Research?

17 A. Adam Dipaula.

18 Q. Was he the only person you spoke with?

19 A. For this project, yes.

20 Q. And so did you talk with Adam Dipaula nightly

21 as to how the surveys were going?

22 A. No. Actually, Josh Blank, the expert

23 consultant on the case, was the one who was overseeing

24 the nightly operation of the poll.

25 Q. And he was then advising you how things were






218

1 for, but yes, we will look at that.

2 MR. MELLETT: Okay. All right. Let's go

3 off the record.

4 (Recess from 3:16 to 3:30 p.m.)

5 Q. (By Mr. Mellett) Okay. Dealing with Exhibit

6 Number 5, your supplemental report, I guess I had a

7 question in terms of the -- on Page 2, and this is the

8 next to last paragraph where it starts an analysis of

9 Dr. Ansolabehere's data. Do you see he where that is?

10 A. Yes.

11 Q. Okay. And my question is -- so you say that

12 18.44 percent of those are over age 65, and when I say

13 of those, it means that the people on Dr. Ansolabehere's

14 list; is that correct?

15 A. Yes.

16 Q. Okay. And so therefore, you're saying that

17 they just ought to be removed all together; is that

18 corrected?

19 MR. HUGHES: Object to the

20 characterization.

21 MR. ROSENBERG: Are people speaking? I

22 lost the sound from your side.

23 MR. HUGHES: So there's a question

24 pending, Ezra, and I objected to it, and now I guess

25 we're going to have an answer.






219

1 THE WITNESS: Yeah, I'm simply reading the

2 paragraph.

3 MR. ROSENBERG: Okay.

4 A. Well, I'm not sure I'm saying anything more

5 than it's not clear how these people ought to be

6 treated.

7 Q. (By Mr. Mellett) So you aren't suggesting that

8 the 18.4 percent should be treated in any particular

9 way, those that are over age 65?

10 A. I think all I'm suggesting is that, to

11 necessarily treat them -- to ignore the fact that the

12 law provides for an opportunity to get an absentee

13 ballot without showing any photo indication is not at

14 all considered in Professor Ansolabehere's report.

15 Q. In terms of your conclusion at the end, where

16 you say that the persons who are over 65 with a

17 disability are exempted from showing photo

18 identification; do you see that? This is on Page 8.

19 This is in that paragraph that starts "Again, however."

20 A. Right, I have it.

21 Q. Okay. So in light of that, are you suggesting

22 that these 18-point -- that 18.4 percent or these

23 342,000 people therefore should not be considered as

24 persons who -- whether they have ID or not, that it's

25 not relevant?






220

1 A. I think what I do here and what I do in the

2 initial report is simply lay out the percentage of

3 people in the overall at risk, or in Professor

4 Ansolabehere's terminology, VRNID list, that is voter

5 registered no ID, simply lay out the percentage that

6 fall into this category. In this case, amongst the

7 remaining population, the population that remains that

8 does not have, that does not have one of these other

9 forms of identification. And I don't know that I make

10 any specific recommendations on how they ought to be

11 treated other than to point out here's the number of

12 them that fall into that category, and including them or

13 excluding them lead to a further -- you know, excluding

14 them from the at-risk population would lead to a further

15 reduction in the percentage of people potentially

16 affected. So I don't know that I make a

17 recommendation. I simply point out that if you had done

18 this, the number would be even lower. I believe that's

19 what I'm getting at here.

20 Q. And I think I'm confused because I'm not sure.

21 Are you making this observation based on the phone

22 survey, or are you making it based on the records from

23 the Secretary of State?

24 A. Well, the reference that you made earlier,

25 which was to Page 2 --






221

1 Q. Uh-huh.

2 A. -- is simply a comment on Professor

3 Ansolabehere's list and how he treats them.

4 Q. Okay.

5 A. The reference on Page 8 is to the percentage of

6 people in the general sample, all right, who amongst

7 those who do not have ID who fall into that

8 categorization might also be considered to have an

9 identification that would allow them to vote.

10 Q. Now, we've already established that you didn't

11 weight the supplemental, right?

12 A. Correct.

13 Q. Let me refer to Page 6, and this is estimating

14 voter ID possession. Do you see under that heading?

15 A. Yes.

16 Q. And in terms of the numbers that you have

17 listed there in age, you say that 49 percent are over

18 the age of 65. Do you see where that is?

19 A. Yes.

20 Q. And so you don't weight that number down, do

21 you?

22 A. Correct.

23 Q. And so in terms of that one percent number that

24 you come up with on Page 8, automatically we've just

25 eliminated half the survey, haven't we, because they're






222

1 over 65?

2 A. No. Because that number is referent to -- the

3 calculation takes into account -- estimates the number

4 of people who claim to have possession of identification

5 permissible under SB 14, and that number gets down to, I

6 believe, I think it's 94 or 95 percent claim to have an

7 ID of that sort. And then the statement then says:

8 Amongst the remaining population, this percent is over

9 65. And therefore, you could -- so your statement is

10 correct insofar as it refers to that 5 to 6 percent who

11 do not have another form of ID. But, yes, I would say

12 50 percent of those ought to be excluded, and you're

13 correct in observing that's based on the unweighted

14 numbers here.

15 Q. But -- and so aren't saying, just to make sure

16 that I'm clear on this, is that you wouldn't be saying

17 that we don't need to look at 50 percent of the survey

18 because they're over 65?


20 Q. Okay. And then likewise, dealing with your

21 initial survey where it was 67 percent, you wouldn't be

22 saying, "We don't need to look at 67 percent of the

23 people in my survey because they're over age 65"?


25 Q. Okay. The -- the 18 percent that I referenced






223

1 on Page 2, is, well, about one third lower than the 49

2 percent. Not -- I guess not quite one third. But

3 there's a significant difference between the 18 percent

4 and the 49 percent in the survey. Does that cause you

5 concern?

6 A. I'll refer back to Exhibit 2 here.

7 It doesn't cause me particular concern

8 because I've looked at the distribution of responses

9 across the different age categories, and they're not

10 appreciably different. So you know, the -- you have to

11 think about the implications of these distributions, and

12 what you would be particularly concerned with is if you

13 had overrepresented seniors. That seems to be case in

14 the unweighted Shaw survey based on the Ansolabehere

15 list, if they had distinct opinions from the other age

16 groups.

17 However, that's not the case. So for

18 instance, if you look at self-claimed possession of

19 driver's licenses or these other forms of

20 identification, it doesn't much matter whether you're

21 looking at seniors, younger people, et cetera.

22 Now, there are some differences depending

23 on the particular form of identification, but in

24 general, and particularly with respect to driver's

25 licenses, is it doesn't really affect anything.






226

1 in my data set in responding to that.

2 Okay. So the only difference is that we

3 asked them of everybody in the second survey.

4 Q. Okay. Since I haven't asked this of the

5 supplemental report: Are you aware of any errors or is

6 there anything in your supplemental report that could

7 mislead the court?

8 A. I believe, once again, in the description of

9 the sample universe -- let me find this specifically.

10 Yes. So Page 5 of Exhibit 5.

11 Q. Okay.

12 A. This would be -- oh, perhaps I'm looking at the

13 wrong number. Oh, yes. I'm sorry. So this would be

14 the first paragraph?

15 Q. Yes.

16 A. Of page 5?

17 Q. Yes.

18 A. The sentence says, "The sample design is

19 similar to one previously performed. Out of the 1.9

20 million person list, we randomly selected approximately

21 98,000 people from which to append phone information."

22 The correct number, as indicated in

23 Exhibit 2, is that -- is that we randomly selected

24 300,000 people for whom 102,459 appended phone records

25 were provided.






227

1 And so the discrepancy here then is it's a

2 98,000 person list. It's actually 102. And I wanted it

3 to be clear that those were the number of appends we got

4 out of the poll of 300,000. I'd like to correct that.

5 Q. Is there anything else?

6 A. Not to my knowledge.

7 Q. On Page 5 of Exhibit 5, I had a question in

8 terms of the -- of the first part, "Problems with Using

9 Catalist's Race/Ethnicity Projections." And in terms of

10 the way that the survey works, is it correct that you

11 ask people first whether or not they're Hispanic?

12 A. Let me refer specifically back to Exhibit 5,

13 and I believe it's Page 13. Yes. We asked, "Do you

14 consider yourself to be Hispanic or Latino" prior to

15 asking their main race.

16 Q. Okay. And so then the question on race is

17 "What would you say is your main race?" Is that

18 correct?

19 A. Correct.

20 Q. And so in fact, people who also identified as

21 Hispanic may consider their main race to be Black; isn't

22 that true?


24 Q. Okay. So you wouldn't necessarily -- it

25 wouldn't necessarily be correct to eliminate the 5






228

1 percent who were Hispanic there, would it?

2 A. No.

3 Q. Okay. In terms of the "something else"

4 category, what is something else? Where they say 11

5 percent is something else, what is that?

6 A. This has been an issue with the census lately.

7 People, even when you ask them for their main race, they

8 want to claim multiple racial identifications, or some

9 smaller subset refuse to acknowledge the specific

10 designations that you've given.

11 For example, I've done polling in New York

12 and African American is rejected as a race because they

13 consider themselves Caribbean American.

14 Q. Do you experience the same with Haitians?

15 A. I have not, but I would not be surprised.

16 So there's some subset who simply don't

17 recognize the legitimacy of the categories we've

18 provided, and then there's some who refuse to choose one

19 versus the other.

20 And then it's possible that in this

21 particular instance that we are missing native

22 Americans, who would claim that as a race. We did not

23 provide an option there.

24 Q. There isn't a significant Native American

25 population in Texas, is there?






229

1 A. Not to my knowledge, no.

2 Q. So if, for example, then where they're asked

3 what their main race is and they say, you know, "I'm

4 Jamaican and, you know, and also Black." Would that go

5 under something else?

6 A. The interviewers are instructed, when they're

7 provided with closed ended options, in this case, White,

8 African American, Asian or something else, and someone

9 offers another category to say, to follow up by the

10 specific options again, not with any threat or stronger

11 action but, "That's fine. Would you consider your main

12 race to be White, African American, Asian, or something

13 else?" I don't know for a fact how many cases they had

14 to involve the secondary language or a secondary probe,

15 but they are asked to choose from the closed ended

16 options we provided.

17 Q. So couldn't it also be possible that even a

18 majority of that 11 percent would also be considered as

19 Black?

20 A. To what 11 percent are you referring?

21 Q. The "Something Else" category. Isn't it

22 possible they also could be Black? In other words, that

23 they're giving multiple answers or, as we've discussed,

24 something specific, and couldn't they also be considered

25 in that --






230

1 A. I see what you're saying. I see what you're

2 saying. I think its possible that some people in that

3 category could be considered by others to be Black, but

4 we're asking them, of course, to rate themselves and

5 they don't choose to select African American in that

6 response there.

7 Q. Well, and I guess part of my question, though,

8 is: Is it fair in the sense to say Catalist does an

9 poor job of finding out the information as to whether

10 people are Black, when in fact they may have found that

11 out, it's just you've got somebody who says they're not

12 going to respond to question. You know, they're going

13 to say, "I'm going to say something else," as opposed to

14 that they're Black.

15 A. Sure. I think even if you granted an upper

16 limit, you know, what I think would be a highly

17 unrealistic limit to how that something else category is

18 identified, you're still talking about correctly

19 classifying four out of five, which means you have a

20 twenty percent miss rate. That's a significant miss

21 rate when you're attempting to represent this

22 population. And that's our only point I think here.

23 And I don't mean to -- this is very difficult work. So

24 I think it reads necessarily as a criticism, an

25 indictment of Catalist, but the reality is they're






231

1 attempting to assign race based on somebody's name and

2 geographic location, and that's very, very difficult.

3 Q. All right. We have not talked about popularity

4 of voter IDs, and I don't want to miss that before I go

5 anywhere.

6 MR. HUGHES: Amen.

7 Q. (By Mr. Mellett) So what -- what I want to know

8 on the popularity of voter IDs, is your statement on

9 your first report, Page 24, I found it very

10 interesting. It's at the very bottom. And it says, "In

11 political terms, this is clearly a winning issue for GOP

12 politicians." Do you see where that is?

13 A. Yes, I do.

14 Q. "Because Democratic politicians are forced,

15 based on certain portions of their coalitions, to take

16 what amounts to a very unfavorable position on these

17 laws." And I've got a couple of questions about that.

18 First, when you say that they are forced,

19 based on certain portions of their coalitions, what do

20 you mean?

21 A. Sure. This is in political science terms a

22 wedge issue, and that is to say the distribution of

23 opinion is such that, from a Republican perspective,

24 there's high levels of support, for independents there

25 are high levels of support, and amongst democrats






232

1 there's ambivalence. Some Democrats support voter ID,

2 some don't, but the distribution is close to fifty-

3 fifty. And that puts Democratic politicians in a

4 difficult point of view.

5 The Democratic coalition is comprised,

6 since the New Deal essentially, of ethic minorities,

7 working class Whites, Jewish people, and in the old days

8 White Southerners, although that's changed

9 considerably. Different parts of the Democratic

10 coalition have different views on this particular

11 issue. Ethnic minorities for the most part tend to

12 oppose it. That is, I should say, interest groups that

13 are important to the Democratic party but may not

14 necessarily reflect the public opinion of the groups

15 they represent.

16 So, for instance amongst Latinos, you see

17 marginal support for voter ID, but the Latino groups are

18 very strongly against it. And that makes it difficult

19 for lawmakers or other people who are responsive to

20 public opinion and what we call issue publics, that is,

21 highly energized elements of the coalition to take a

22 position in the issue that's in accord with broader

23 public opinion.

24 Q. I guess this goes back to what we talked about

25 in general in terms before, in terms of legislators, you






233

1 know, following public opinion or looking at public

2 opinion. And I guess my question is: Do you think that

3 most of the minority members of legislature that opposed

4 SB 14 are doing something that is not in their self

5 interest?

6 A. Not especially, because voter identification is

7 not a very salient issue for most voters. What we

8 demonstrated here is that there's pretty considerable

9 support for it, but if you asked about the most

10 important issues facing the State of Texas, people will

11 talk about the economy, dominant, and to slightly lesser

12 extent, immigration and border security. You know, this

13 issue doesn't show up on the very top of that list.

14 So I would submit that a lot of these

15 Democratic legislators aren't necessarily, you know, in

16 lockstep with their constituents on this particular

17 issue, but there's not a lot of pressure coming from

18 minority voting groups to act on this particular issue;

19 whereas, on other issues, there's more support.

20 Q. And so in looking at the voter ID issue, have

21 you either talked with, looked at, have an assessment as

22 to why minority legislators would be so opposed?

23 MR. HUGHES: Object to the form.

24 A. Can you rephrase? I think I know what you're

25 saying.






234

1 Q. (By Mr. Mellett) Well, I'm trying to get at,

2 again, based on your knowledge. I'm not trying for you

3 to, you know, guess what they're thinking. But based on

4 what you've read, what you've seen, because obviously

5 you said you've looked at quite a bit in this area, is

6 why it would be that they would oppose it, given what --

7 you know, given, for example, your research and what you

8 said here about -- it's not going to hurt them.

9 A. I was asked -- and the only reason that this

10 issue is in the report, is I was asked to directly kind

11 of entertain the question of why it would be that the

12 Texas Legislature would act on this issue, are there

13 alternative explanations to some of those offered by

14 people like Professor Kousser. And, you know, looking

15 across the range of opinion, it seems pretty obvious

16 that there's fairly widespread support both nationally

17 and in Texas for voter identification.

18 So that's why I'm sort of engaging in this

19 question. Why is it that, let's just say for lack of

20 better term, Democratic elites are by and large

21 opposed. I mean, I tend to think that politicians, as

22 bad a name as they have often times, are sincere, and

23 most of these people believe this is not good public

24 policy, will not be good for their constituents, and so

25 while, you know, they're attentive and understand that a






235

1 lot of their constituents probably support this, you

2 know, they're acting I believe on what they think is in

3 the best interest of their community.

4 Q. I take it that you were not asked to look at

5 whether or not voter ID has any effect on voter

6 confidence?

7 A. No, I was not.

8 Q. The -- and I want to know if you'd agree with

9 me on a statement, which is that popularity would not be

10 a justification for adopting a law that would

11 discriminate against minority voters?

12 A. Would I agree or disagree with that statement?

13 I haven't been asked to comment on these sorts of

14 issues. As a citizen or as anybody, sort of an

15 interested American, no, I think, you know,

16 discriminatory laws are by definition something we ought

17 to assiduously avoid.

18 Q. I've got just a couple of questions that deal

19 with Professor Kousser's and Professor Ansolabehere's

20 rebuttal reports. What I want to know: You've

21 indicated that you have looked at both of their reports?

22 A. Yes.

23 Q. Their rebuttal reports?

24 A. Yes, I have.

25 Q. And I'm going to start first with Dr. Kousser's






236

1 rebuttal report. Do you have any the criticisms of

2 Dr. Kousser's rebuttal report?

3 A. I do not have it in front of me, and I had some

4 thoughts when I read it, but I can't recall off the top

5 of my head what those were. If you'll give me just a

6 moment to sort of reflect on it.

7 Q. Because in part, he talked about the popularity

8 aspect.

9 A. Yeah. I believe that what Professor Kousser

10 said in main was that I do not advance a broad theory of

11 elite domination of public opinion like he does, and

12 therefore, the results that I give don't necessarily

13 refute what he is saying.

14 My response would be I'm not particularly

15 interested in refuting his fairly long kind of narrative

16 for how the Texas Legislature has acted on this issue.

17 I'm simply posing what I think is a plausible

18 alternative, which is that they're largely looking at

19 the distribution of opinion and thinking this is a good

20 issue for them politically.

21 He had a particular criticism of the way

22 in which the questions were asked, which my restrained

23 reaction would be it's an ad homonym attack, the sort of

24 which you could make on any question. So he has a

25 criticism of the general question which is: Do you






237

1 support or oppose voter ID? He also had an objection to

2 a two-sided question, in which you attempt to represent

3 both sides of the issue. He does not offer an

4 alternative, except to say that, to cite a Borreto piece

5 which offers an alternative two-sided version of the

6 question which he reports could alter the distribution

7 so it's closer to fifty-fifty on the question of voter

8 ID, to which my response is: I haven't read that

9 particular piece by Professor Borreto. I know Professor

10 Borreto's work pretty well, and I wasn't aware that he

11 had done that. I'm quite sensitive to question wording

12 effects, but -- and I would concede the point that, if

13 you are looking to arrange a two-sided question in a way

14 to alter the distribution of opinion, it's possible to

15 do that.

16 Q. Are you otherwise planning on, at trial, having

17 additional discussion that would refute Dr. Kousser's

18 report on intent?

19 A. I do not believe so at this time. I was asked

20 in the initial report, and then to a lesser extent in

21 the rebuttal, to address this question of popularity of

22 voter ID. I don't see that I -- there's any particular

23 reason for me to comment on this beyond the evidence

24 I've already presented.

25 Q. So at this point anyway, you --






240

1 (Recess from 4:04 to 4:08 p.m.)

2 Q. (By Mr. Mellett) I just have a couple of more

3 questions.

4 One of the things that you had mentioned

5 in your report was that 46 percent of people who did not

6 have ID's said they would intend to get a card, I guess,

7 either were somewhat likely or very likely; is that

8 right?

9 A. Is the first or second survey?

10 Q. I believe this is the rebuttal report.

11 A. Okay.

12 Q. And I believe that this is -- I think it's the

13 rebuttal report. Let me check. Yeah, it's on Page 9,

14 "In addition, amongst those," if you can look at that

15 paragraph.

16 A. Okay. Yes.

17 Q. And my question there is: Did you look at what

18 barriers people may face in order to be able to try and

19 get such cards?

20 A. As background, we talked fairly extensively --

21 I talked fairly extensively with some people about how

22 this would be administered. I understand the -- there's

23 a bit of a controversy about -- and this from my reading

24 actually of the Senate transcript, that these DPS

25 offices, not enough of them are located in heavily






241

1 minority areas and that it could impose a burden. But

2 my understanding of the law is that money would be

3 provided so that there would actually be mobile election

4 identification centers that would operate throughout the

5 state, you know, trying to sign people up in advance of

6 the election, that were steps being taken to try to

7 correct some of the issues. So as a matter of

8 background, yes. In terms of the question, no, I really

9 didn't see any way of, you know, kind of dealing with

10 this fact or potential issue.

11 Q. In your report, did you consider how the SB 14

12 would be implemented?

13 MR. HUGHES: Object to the form.

14 A. Could you ask that another way, please?

15 Q. (By Mr. Mellett) Well, the -- like you

16 mentioned there, that in terms of, you were saying that

17 there was additional money that was going to be

18 provided, and what I wanted to know is, because I didn't

19 otherwise see it in your report, is that if you had

20 looked at the effects of, for example, how much money

21 was going to be allocated and what that meant for

22 whether people who didn't have ID would be able to get

23 ID?

24 A. No, I don't believe I did.

25 Q. In general, did you look at, in terms of the






242

1 administration by poll workers, did you look at how poll

2 workers in Texas would administer SB 14?

3 A. I looked at a report that -- and I don't have

4 the statute in front of me, but it provided a set of

5 guidelines for poll workers to observe as they were

6 administering the new law under SB 14. And I believe I

7 referenced this earlier, but that my understanding is

8 that that set of instructions included how to treated

9 match cases, how to treat ambivalent cases, and what to

10 do when there was -- when the poll worker decided, after

11 looking through the other criteria, there was no match,

12 how to administer provisional ballots. So I saw some

13 instructions on that. But in terms of influencing the

14 design of surveys or the lit review or things of that

15 nature, it wasn't directly relevant to what I was doing.

16 Q. And so you didn't reach any conclusions as to

17 how SB 14 would be implemented if it went into effect?

18 A. That's correct. I would say that there was an

19 assumption that people -- that poll workers, for

20 instance, we were comparing it to Indiana and Georgia,

21 would implement, you know, would ask for photo ID as

22 instructed in all -- you know, in all instances.

23 So for instance, earlier we referred to 60

24 percent of the voters had been asked for identification

25 in the state of Texas. One of our assumptions is that






243

1 that would go up to 98 or 99 out of a hundred percent as

2 it looks in Indiana and Georgia where they have photo ID

3 laws.

4 Q. But otherwise, in terms of how they were going

5 to implement -- how the poll workers were going to

6 implement it, you didn't make an assessment on that?

7 A. Correct.

8 MR. MELLETT: I have no further questions:

9 MR. ROSENBERG: Okay. I have a few, and I

10 will try to be as expeditious as possible. I know that,

11 Dr. Shaw, you have a five o'clock break and we will

12 definitely meet that.

13 THE WITNESS: Thank you, sir.

14 EXAMINATION

15 BY MR. ROSENBERG:

16 Q. My name again is Ezra Rosenberg. I represent

17 two of the intervenors in this case, and I'm sitting

18 here in beautiful New Jersey, not quite as warm as you

19 are there.

20 A couple of questions, and just so I get

21 kind of the big picture right. Is it fair to say that

22 even though the State records showed approximately

23 800,000 people as not having driver's license or photo

24 ID's, your survey concludes that that is a wrong figure

25 by a margin of about 75 to 80 percent?






246

1 percentage of false negatives in terms of the matches,

2 that at least your survey would say exist in the State

3 database?

4 A. I think in absolute terms, it's a large

5 number. I don't think it's inconsistent with some of

6 the data that we've seen from other states. That is

7 say, you know, as I characterize in the literature

8 review in the first report, it seems to be the case that

9 there are not a significant portion of people who are

10 adversely affected by these voter ID requirements, and

11 so I would have to say that, while there's a lot of

12 people who the State says -- or at least the State's

13 best list says do not have a photo -- do not have a

14 driver's license, the possibility that they may in fact

15 have a driver's license actually would square with some

16 of the research we see on actual behavior in other

17 states.

18 Q. But your report only analyzed the -- those

19 persons who are not matched in the databases; is that

20 correct?

21 A. That is correct.

22 Q. Did you make any attempt to analyze those

23 persons who were matched in the databases?

24 A. No.

25 Q. Do you accept the real possibility that there






247

1 might be mistakes going the other way in the State's

2 databases?

3 A. I think it's possible that there are people for

4 whom there are records of driver's licenses who may not

5 in fact have driver's licenses, but I also point out

6 that amongst the at risk population, as we see in the

7 report, there are significant, you know, very, very high

8 levels of people who have driver's licenses. So, you

9 know, the arrow running in the other direction is a

10 possibility; it just strikes me as being fairly

11 minimal. And amongst that population, we don't have a

12 sense of whether they have other forms of identification

13 as well, which are claimed at fairly high rates in the

14 existing -- in the sample that we've provided.

15 Q. But you did not undertake that analysis?

16 A. We did not.

17 Q. Did you undertake any runs on the data that you

18 decided not to include in either of your reports?

19 A. Could you rephrase that?

20 Q. Sure. Did you -- for example, let's take your

21 weighting analyses. Did you make any runs of weighting

22 that you decided not the to include in your final

23 reports?

24 A. Do you mean any alternative --

25 Q. Yes.






248

1 A. -- weighting schemes for the electorate? No,

2 we only did the one.

3 Q. Okay. Now, you've -- I think you've mentioned

4 a couple of times Dr. Marker's rebuttal report, and I

5 think you stated that you thought that his conclusions

6 concerning response rate were not accurate and not up to

7 date. Is that a fair characterization of your prior

8 testimony today?

9 A. Yes. Although, I believe that the accuracy

10 claim is highly contingent on the secondary claim, that

11 they're not accurate because they're not in fact up to

12 date.

13 Q. Okay. Could you --

14 A. I'm sorry. Please ask the question. I

15 shouldn't have interrupted.

16 Q. No, no, I interrupted you. It's more difficult

17 over the telephone. I was just going to ask you to tell

18 me why you believe that his report, his opinion is not

19 up to date.

20 A. Sure. Again here I'm referring the May 15,

21 2012, Pew Research Company report. Dr. Marker was

22 referring to response. I have two sort of responses.

23 The first is that he's comparing apples to oranges, in

24 the sense that he's comparing response rates from

25 national RDD polls or some of these government studies






249

1 which have long, long time frames, face-to-face

2 interviewing, budgets of hundreds of thousands of

3 dollars, you know, he's citing response rates sort of

4 based on those. And even his response rates he's citing

5 from U.S. national surveys, he's talking about maybe a

6 30 percent to 50 percent response rate.

7 The Pew study shows that -- and those

8 numbers were accurate in 1997. In 2012, the response

9 rate across U.S. national surveys, according to Pew, is

10 9 percent, and that's using, you know, RDD samples, not

11 list base, and not at risk populations.

12 So my sort of pushback or criticism is

13 that I don't believe the characterization of response

14 rates he's offering is up to date.

15 Q. And I -- I believe you testified earlier that

16 you had never done a survey where you had as low a

17 response rate as -- as in this case; is that correct?

18 A. I believe that's correct. Oh, may I amend that

19 slightly?

20 Q. Uh-huh.

21 A. I have been a consultant on some automated call

22 surveys in which the response rates were actually

23 considerably lower.

24 Q. And what do you mean by automated response

25 rates?






250

1 A. They're popularly known as robo calls.

2 Q. Uh-huh.

3 A. And those are surveys where you can actually

4 automatically dial hundreds of thousands of numbers over

5 the course of an evening, and you get lots of interviews

6 but very low response rates. And they're conducted via

7 touch tone -- push button responses, you know, press 1

8 for Obama, press 2 for Romney.

9 And people like Scott Rasmussen, Survey

10 USA, other organizations, do this kind of thing, and

11 their response rates are actually appreciably lower than

12 2 percent. And I've been involved in some projects

13 where we did those sorts of calls.

14 Q. Have you ever published on the basis of

15 automated robo call surveys?

16 A. No. I have cited Rasmussen polls in some

17 academic work, but I've never published based on it.

18 Q. Is it your opinion that the sample that you've

19 gotten from your surveys is representative of the entire

20 Texas voting registration population?

21 A. Which sample are you referring to?

22 Q. Well, let's start with your original sample.

23 A. It is -- do you mean to ask is it

24 representative of the registered voter population? Or

25 of the Secretary of State no ID population?






251

1 Q. The latter.

2 A. Okay. The weighted sample I think clearly

3 is. The unweighted sample needed to be weighted to be

4 demographically representative.

5 Q. And what -- what do you base your conclusion

6 that the weighted sample is? And let me be more

7 specific. How do you know, for example, that the Blacks

8 who gave you survey responses are representative of the

9 entire population of Secretary of State at risk African

10 Americans?

11 A. Ah, that's a good question. It's difficult to

12 tell with any high degree of precision. What I did was

13 looked at the education and income profiles for those

14 groups. And I think you're correct in inferring that we

15 do not have detailed information against which to set

16 targets. That is, I'm not confident that I can weight

17 to those particular points. However, what I'm looking

18 for is significant variation in the presence of people

19 that, in this case, lower levels of educational

20 attainment, lower levels of income. I'm looking for a

21 appreciable presence in that African American

22 subpopulation, and that is what we found both in the

23 initial survey and then in the surveys using the

24 Ansolabehere list.

25 Q. And why were you looking for lower levels of






252

1 educational and economic standing?

2 A. Sure. The standard criticism, when we're

3 talking about harder to reach populations, is that they

4 tend to be a little downscale economically. These are

5 groups that are more difficult to reach for a variety of

6 reasons: residential mobility, sort of the age

7 structure, reticence to participate in these sorts of

8 surveys and things like that. So we -- when we tend to

9 have samples that come back that are, you know, we're

10 interested in looking at the Hispanics population that

11 we attained, or the African American population that we

12 attained, for weighting purposes, we tend to look at the

13 internal profile so that we're not creating an overall

14 sample that overrepresents certain kinds of African

15 Americans when you weight to larger targets.

16 Q. By the way, when you did the -- when you

17 selected the people for the rebuttal report on the

18 Ansolabehere VRNID, did that universe include people

19 whom you had originally surveyed?

20 A. I'm not sure that that -- I'm not entirely

21 confident that we excluded people based on that. I

22 believe that we excluded, but I will ask Ross Hunt about

23 the selection process.

24 Q. Would that be apparent from the data that was

25 sent over today, do you know?





Exhibit - Moritz College of Law - Home · Daron Robert Shaw, Ph.D. June 25, 2012 22 1 however, is...

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Transcript of Exhibit - Moritz College of Law - Home · Daron Robert Shaw, Ph.D. June 25, 2012 22 1 however, is...