O C TO B E R 2 0 1 0

B R I E FI NG

R E P O R T

U . S . C O M M I S S I O N O N C I V I L R I G H T S

Encouraging Minority Students to Pursue

Science, Technology, Engineering and Math Careers
U.S. COM M I S S I ON ON CIVI L R I G HTS

The U.S. Commission on Civil Rights is an independent, bipartisan agency established by Congress in 1957. It is directed 

to:

• Investigate complaints alleging that citizens are being 

deprived of their right to vote by reason of their race, color, 

religion, sex, age, disability, or national origin, or by reason 

of fraudulent practices.

• Study and collect information relating to discrimination or a 

denial of equal protection of the laws under the Constitution 

because of race, color, religion, sex, age, disability, or 

national origin, or in the administration of justice.

• Appraise federal laws and policies with respect to discrimination or denial of equal protection of the laws because of 

race, color, religion, sex, age, disability, or national origin, or 

in the administration of justice.

• Serve as a national clearinghouse for information in respect 

to discrimination or denial of equal protection of the laws 

because of race, color, religion, sex, age, disability, or 

national origin.

• Submit reports, findings, and recommendations to the 

President and Congress.

• Issue public service announcements to discourage 

discrimination or denial of equal protection of the laws.

M E M B E R S OF TH E COM M I S S I ON

Gerald A. Reynolds, Chairman

Abigail Thernstrom, Vice Chair

Todd Gaziano

Gail Heriot

Peter N. Kirsanow

Arlan D. Melendez

Ashley L. Taylor, Jr.

Michael Yaki

Martin Dannenfelser, Staff Director

U.S. Commission on Civil Rights

624 Ninth Street, NW

Washington, DC 20425

(202) 376-8128 voice

(202) 376-8116 TTY

www.usccr.gov

This report is available on disk in ASCII Text and Microsoft Word 2003 for persons with visual impairments. Please call (202) 376-8110.
Encouraging Minority

Students to Pursue

Science, Technology,

Engineering and

Math Careers

A Briefing Before

The United States Commission on Civil Rights

Held in Washington, DC

Briefing Report





Table of Contents

Executive Summary................................................................................................................ 1

Findings and Recommendations............................................................................................ 3

Summary of Proceedings........................................................................................................ 7

Richard Sander...................................................................................................................... 7

Richard Tapia...................................................................................................................... 21

Rogers Elliott ...................................................................................................................... 22

Thomas Fortmann ............................................................................................................... 26

Robin Willner ..................................................................................................................... 27

Discussion............................................................................................................................... 29

Statements.............................................................................................................................. 3

Richard Tapia...................................................................................................................... 37

Rogers Elliott ...................................................................................................................... 44

Thomas E. Fortmann........................................................................................................... 68

Robin Willner ..................................................................................................................... 71

Speaker Biographies............................................................................................................. 75

Richard Sander.................................................................................................................... 75

Richard Tapia...................................................................................................................... 75

Rogers Elliott ...................................................................................................................... 75

Thomas Fortmann ............................................................................................................... 76

Robin Willner ..................................................................................................................... 76

Commissioner Statements and Rebuttals........................................................................... 77

Statement of Commissioner Gail Heriot............................................................................. 77

Statement of Commissioner Ashley L. Taylor, Jr. ............................................................. 93

Dissent of Commissioners Michael Yaki and Arlan D. Melendez..................................... 94

Joint Rebuttal of Commissioners Gail Heriot, Peter Kirsanow and Todd Gaziano ........... 9

7

6

Executive Summary 1

Executive Summary

The Commission held a briefing entitled, “Encouraging Minority Students to Pursue Science,

Technology, Engineering and Math Careers.” In particular, the Commission examined why

minority college students who begin their college studies intending to major in science,

technology, engineering or math (STEM) leave these disciplines in disproportionate numbers

before graduation.

Experts appearing before the Commission were Professor Richard Sander of the University

of California at Los Angeles (UCLA) Law School; Dr. Richard Tapia, Maxfield-Oshman

Professor in Engineering at Rice University; Dr. Rogers Elliott, Professor Emeritus of

Psychological and Brain Sciences at Dartmouth College; Dr. Thomas Fortmann,

Massachusetts Board of Elementary and Secondary Education; and Ms. Robin Willner, Vice

President of Global Community Initiatives at IBM Corporation.

Of particular interest to the Commission on this occasion was the “mismatch hypothesis.”

The mismatch hypothesis holds that students whose academic credentials are significantly

different from the average student in the class may learn less than they would have learned in

a class in which their academic credentials “matched” those of the average student. Mismatch

may be positive or negative. Students who are positively mismatched – that is, their academic

credentials significantly exceed those of their peers – may not be sufficiently challenged by

the material. As a result, they may become bored or disengaged. Students who are negatively

mismatched – that is, their academic credentials are significantly below those of their peers –

may feel overwhelmed by the speed at which difficult material is being taught. They may get

lost – even though they could have mastered the material had it only been taught at a slower

rate.

Under this hypothesis, aggressive affirmative action or any admissions decision for largely

nonacademic reasons can lead to negative mismatch for any student, including

underrepresented minorities.1 Well-meaning efforts to benefit these students can, if the

mismatch hypothesis is correct, cause these students to drop out of STEM programs in

disproportionate numbers. The result is fewer, not more, minority physicians, scientists, and

engineers.

In this briefing, the term “mismatch” did not include the admission of students with small

academic deficits who, with the kind of support offered by the colleges and universities they

attend, would remain interested in STEM and able to successfully complete a program.

There was substantial agreement among the witnesses. None disputed the evidence that

blacks and Hispanics are at least as likely to express interest in STEM majors as whites prior

1 The terms “minority,” “non-Asian minority,” and “underrepresented minority” refer to the same group and

were used interchangeably by the panelists.
2 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers

to attending college. None disputed the evidence that blacks and Hispanics abandon their

STEM ambitions in greater proportions than do whites and Asians.

Two witnesses, Dr. Sander and Dr. Elliott, each presented an empirical study that supported

the mismatch hypothesis at the undergraduate level. None of the other witnesses disputed

either study. Indeed, to one extent or another, they all agreed on the peril that results when a

minority student, usually unknowingly, accepts an offer of admission at a college or

university at which he or she is mismatched. All the witnesses agreed that prospective

students should be informed that his or her academic credentials are substantially below the

average at a particular school. Students could then make an informed decision about which

school to attend.

No one took the position that the elimination of mismatch in admissions would eliminate the

disparities in average STEM credentials upon completion of high school between black and

Hispanics students on the one hand and white and Asian students on the other. Mismatch is

simply a piece of the puzzle at the college level.

Rather than highlight mismatch, Dr. Fortmann emphasized the difficulty of attracting

competent STEM teachers to K-12 schools, which he blamed for inadequate college

preparation. Dr. Tapia conceded that the data on mismatch presented by Dr. Sander and Dr.

Elliott “are entirely credible to me because they reflect what I have seen at Rice.” While he

stated that he did “not dispute the data,” he took issue with what he perceived to be the

conclusions they drew from it and advocated instead strong support and mentoring programs

at the graduate level. He emphasized the need for “an equitable presence” of minorities at top

research university graduate programs in STEM, where minority faculty members can serve

as both role models and mentors.

Ms. Willner discussed a report entitled, “Out Before the Game Begins: Hispanic Leaders

Talk About What’s Needed to Bring More Hispanic Youngsters into Science, Technology

and Math Professions,” sponsored by IBM.

Based on this testimony, the Commission made the following findings and recommendations:

(Please see next page).
Findings and Recommendations 3

Findings and Recommendations

Findings

1.) Science, technology, engineering, and mathematics (STEM) graduates are important to

the U.S. economy because they enable the United States to maintain its preeminence in

STEM fields. [Approved (7-0): Chairman Reynolds, Vice Chair Thernstrom, Commissioners

Gaziano, Heriot, Kirsanow, Taylor, and Yaki voted in favor.]

2.) Black and Hispanic high school seniors exhibit about the same degree of interest in

pursuing STEM careers as white students (Asian students are still more interested). But

despite these initially high levels of interest, black and Hispanic students are less likely to

major in or obtain a doctoral degree in STEM disciplines than are whites and Asians.

[Approved 4-2-1: Chairman Reynolds and Commissioners Gaziano, Heriot, and Kirsanow

voted in favor; Vice Chair Thernstrom and Commissioner Yaki voted against; Commissioner

Taylor abstained.]

3.) Data presented to the Commission showed that success in a STEM major depends both on

the student’s absolute entering academic credentials and on the student’s entering academic

credentials relative to other students in the class. When a student is in a class in which his or

her entry credentials are significantly different from the median student, the student is

“mismatched” for that class. This mismatch causes a loss of learning, either because the

positively mismatched student is not challenged by the material or because the negatively

mismatched student feels overwhelmed by the speed at which the material is being taught.

[Approved 4-1-2: Chairman Reynolds and Commissioners Gaziano, Heriot, and Kirsanow

voted in favor; Commissioner Yaki voted against; Vice Chair Thernstrom and Commissioner

Taylor abstained.]

4.) Data presented to the Commission indicated that racial or ethnic discrimination in college

was not a substantial factor in black and Hispanic college students’ disproportionate attrition

from STEM majors. The evidence showed that when black and white students have the same

academic index scores, black students are more likely than white students to receive a STEM

degree. [Approved 4-0-3: Chairman Reynolds and Commissioners Gaziano, Heriot and

Kirsanow voted in favor; Vice Chair Thernstrom and Commissioners Taylor and Yaki

abstained.]

5.) The practice of racial and ethnic preferences is one way in which black and Hispanic

students may be admitted to a college or university at which their entering academic

credentials are significantly lower than those of their peers. When top tier colleges and

universities use racial and ethnic preferences to recruit and admit minority students with

academic credentials that are significantly below their median — but match the median of

lower tier colleges — the resulting mismatch at the top tier institutions has a cascading effect

through many lower tiers as each tier engages in racial and ethnic preferences to recruit and
4 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers

admit black and Hispanic students who do not match the mean in its respective tier.

Although the consequence of this cascading mismatch is not the principal reason for the

current disparities between blacks and Hispanics and whites and Asians in STEM (see

Finding 3 regarding absolute credentials), it is a significant reason. There are fewer black

and Hispanic physicians, scientists and engineers today than there would have been if

colleges and universities had not recruited and admitted black and Hispanic students with

significantly lower academic credentials than their average student. [Approved 4-1-2:

Chairman Reynolds and Commissioners Gaziano, Heriot, and Kirsanow voted in favor;

Commissioner Yaki voted against; Vice Chair Thernstrom and Commissioner Taylor

abstained.]

6.) The high STEM-major attrition rate of students with credentials deficits indicates that

many students and their parents may be unaware of the significance of mismatch for

students’ success in STEM fields because of the lack of institutional transparency. [Approved

4-1-2: Chairman Reynolds and Commissioners Gaziano, Heriot and Taylor voted in favor;

Commissioner Yaki voted against; Vice Chair Thernstrom and Commissioner Kirsanow

abstained.]

7.) One panelist indicated that some graduate schools that have intensive support programs

have been successful in ameliorating the effects of a moderate degree of mismatch.

[Approved 4-1-2: Chairman Reynolds and Commissioners Gaziano, Heriot and Kirsanow

voted in favor; Commissioner Yaki voted against; Vice Chair Thernstrom and Commissioner

Taylor abstained.]

Recommendations

1.) A selective college or university should not admit any student with a large deficit in

academic credentials relative to its median student without fully informing the student of the

impact this deficit could have. Such deficits place students at a high risk of failure.

[Approved 5-3: Chairman Reynolds and Commissioners Gaziano, Heriot, Kirsanow and

Taylor voted in favor; Vice Chair Thernstrom and Commissioners Melendez and Yaki voted

against.]

2.) In addition to providing other appropriate support and advice to students interested in

STEM majors and careers, high school guidance counselors should advise these students

about the significant impact of large deficits in academic credentials on college performance.

[Approved 5-3: Chairman Reynolds and Commissioners Gaziano, Heriot, Kirsanow and

Taylor voted in favor; Vice Chair Thernstrom and Commissioners Melendez and Yaki voted

against.]

3.) Each individual student's right to decide which school to attend -- based on the best

available evidence and with help from parents and advisors -- should be respected. To aid

students with the decision-making process, schools with STEM programs should disclose to

all admitted students their projected college grade point averages (and the range of error).

Schools should also disclose to interested students the school's track record for graduating
Findings and Recommendations 5

students with similar academic indices in STEM majors. [Approved 4-3-1: Chairman

Reynolds and Commissioners Gaziano, Heriot and Taylor voted in favor; Vice Chair

Thernstrom and Commissioners Melendez and Yaki voted against; Commissioner Kirsanow

abstained.]

4.) Well-designed academic support programs can sometimes help students with modest

deficits in credentials to succeed in STEM programs. Schools should study and implement

the best practices employed by successful academic support programs. Schools should also

routinely disclose information about academic support services to all admitted students.

[Approved 5-3: Chairman Reynolds and Commissioners Gaziano, Heriot, Kirsanow and

Taylor voted in favor; Vice Chair Thernstrom and Commissioners Melendez and Yaki voted

against.]

5.) K-12 schools should recruit qualified math and science teachers using, if necessary, pay

adjustments and incentives. [Approved 7-0: Chairman Reynolds, Vice Chair Thernstrom,

and Commissioners Gaziano, Heriot, Kirsanow, Taylor and Yaki voted in favor;

Commissioner Melendez did not participate in the vote.]

Summary of Proceedings

Richard Sander

Professor Richard Sander2 has both a Ph.D. in economics and a JD, and is a professor at

UCLA Law School where he conducts empirical research on social policy. He began by

discussing the different underrepresentation rates among major racial groups with respect to

earning an undergraduate or doctoral degree in general education and in STEM disciplines.3

His data analysis4 indicated that black students were less likely than white students to earn a

bachelor’s degree of any kind or a doctorate, relative to their proportion of the general

population. Professor Sander stated that underrepresentation in science is even more

disproportionate: blacks are 36 percent as likely as whites to earn a bachelor’s degree in

science, 15 percent as likely to earn a doctorate in science, and 8 percent as likely to earn a

non-biological science doctorate. He said that underrepresentation among Hispanics was

similar to that of African-Americans with respect to undergraduate and graduate degrees, but

that Asians were overrepresented in science relative to their population numbers. He added

that within a science degree population, however, Hispanics are better represented relative to

their concentrations in other disciplines.

Professor Sander set out four hypotheses to explain STEM underrepresentation among nonAsian minority students (slide 3):

x Black and Hispanic students are less interested in science than whites and Asians

(Hypothesis 1);

x Black and Hispanic students have lower achievement levels and credentials by the

time they finish high school, which affects their subsequent success rate (Hypothesis

2);

x Minority students have worse outcomes because of factors such as discrimination or

inadequate support (Hypothesis 3); and

x Many capable minority students go into science but struggle or leave those disciplines

because of mismatch. Professor Sander defined “mismatch” as any loss of learning

that occurs because of a disparity between the credentials of a student and the median

credentials of his classmates in a learning environment (Hypothesis 4).5 Such

disparities can be the result of admissions policies that emphasize affirmative action.

2 STEM Briefing Tr. (hereinafter Tr.) at 11-23. Professor Sander stated that he was presenting preliminary

research, subject to revision, based on data obtained in July 2008 from the University of California, Office of the

President. Dr. Sander stated that he was collaborating with several other scholars in a study of science mismatch

in the University of California system that he hoped would be completed in 2009. During his testimony, he

referred to projected images (slides 1–20) which can be found at the end of this summary.

3 Please refer to slide 2; slide 1 is a title page. Subsequent references to slides will appear in the text. 4 His data interpretation showed relative proportions of general and science degrees earned by college-aged

students of different races compared to a white norm set at 100. This data interpretation showed that black

students were 56 percent as likely to earn a BA of any kind, and 43 percent as likely to earn a Ph.D.

5 According to Dr. Sander, “positive mismatch” occurs when a student is not challenged, since the student can

learn more and at a faster rate than his classmates; “negative mismatch” occurs when a student falls behind or

feels overwhelmed because of the speed or complexity with which material is presented.

Summary of Proceedings 7
Professor Sander found evidence to support both Hypothesis 2 and Hypothesis 4. On the

other hand, the evidence he presented contradicted Hypothesis 1 and Hypothesis 3.

Professor Sander presented data from several studies that showed black and Hispanic high

school seniors are at least as interested in becoming science majors as whites. Based on this

research, Sander argued that Hypothesis 1 (black and Hispanic students are simply less

interested in science careers) is unsupported (slides 4, 5).

By contrast, Professor Sander found that his data supported Hypothesis 2 (black and Hispanic

high school graduates have lower achievement levels and credentials that affect their STEM

success rate) and was probably the major explanation for both their lower graduation rates in

general and higher attrition rates in science in particular (slide 6).

Professor Sander explained that a widely-read book on affirmative action, The Shape of the

River,6 by William Bowen and Derek Bok, has somewhat obscured the relationship between

entering academic credentials and academic success. In that book, Bowen and Bok presented

evidence that at elite schools, SAT scores are not a good predictor of the likelihood of

graduation and that graduation rates are high from these schools regardless of SAT scores.7

Sander stated that any conclusion that SAT scores don’t matter to academic success or to

graduation rates in general is fundamentally wrong and has not held up to further research.

To illustrate the relationship between entering academic credentials and academic success, he

offered an analysis of data obtained from the University of Michigan on several thousand

undergraduates who matriculated in 1999. This database made use of an “academic index”

assigned to each student by the University of Michigan, which took into consideration both

standardized test scores and high school record. Grouping students into three cohorts based

on whether they had received a large preference, a moderate preference, or no apparent

preference, Sander found that black students who received a large preference had a four-year

graduation rate of 21 percent, compared to a 73 percent four-year graduation rate for black

students who received no preference (slide 10). A broadly similar pattern held for whites. He

also offered data from the National Longitudinal Survey of Freshmen, which showed that

students, both black and white, with higher academic credentials have higher four-year

graduation rates than those with lower academic credentials (slide 11). Both sets of data

showed also that blacks with high credentials had a higher four-year graduation rate than

whites with similar credentials.

Professor Sander attempted to demonstrate that what is true for graduation rates also holds

for concentration in the sciences: high credentials are important. He observed that for the

6 William Bowen & Derek Bok, The Shape of the River, (Princeton University Press 2000). 7 Bowen and Bok looked only at elite schools and only at SAT scores, not at other academic credentials like

high school grades. At some schools, students with SAT scores above the school’s median may tend to have

lower high school grades than the average student’s and vice versa; indeed this may account for why the student

is attending that school and not a more (or less) competitive one. As a consequence, efforts to show how well

SAT scores predict academic success that do not control for high school grades will obscure rather than reveal

an important relationship.

8 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
1999 Michigan entering students, 5 percent of blacks who received substantial preferences

ended up majoring in science or engineering, compared with 43 percent of blacks who

received no preference (slide 9). His analysis revealed that whites displayed a similar pattern:

4 percent of those who received a large preference ended up majoring in science or

engineering, versus 33 percent who received no preference. As with graduation, Dr. Sander

stated that blacks with high academic credentials were more likely to major in science or

engineering than were whites with the same credentials. He determined that this not only

supported Hypothesis 2 (credential levels have a significant impact in producing science

graduates), but contradicted Hypothesis 3 (discrimination and inadequate academic support

undermine black and Hispanic academic performance). If high-credential blacks are more

likely to major in and graduate from science programs than high-credential whites at

Michigan, then Dr. Sander did not think it likely that discrimination plays a meaningful role

in STEM attrition.8 He stated that the problem is that blacks (and to a lesser extent,

Hispanics) are far more clustered in the lower-index/high-preference ranges at Michigan than

are whites and Asians.

To examine Hypothesis 4 (the effect of “mismatch” on minority success in science), Dr.

Sander turned to his analysis of a large data set that he obtained from the University of

California, Office of the President (UCOP), that covered nearly a half-million UC students

from 1992 through 2006 (slide 13). He stated that to test mismatch, one must compare

students with similar credentials who are attending institutions with different degrees of

admissions selectivity (slide 12). He stated, for example, that a student with solid but not

outstanding credentials might be close to the student median at UC Santa Barbara, but be

able to attend UC Berkeley only with the benefit of a significant preference, and thus be

potentially affected by mismatch (slide 13). He believed that the UCOP data set makes it

possible to compare many thousands of similar students in different academic settings.

Dr. Sander said that his preliminary analysis of the UCOP data strongly supports his

mismatch hypothesis (slides 14–19). When he compared students at Berkeley and UCLA

whose credentials were substantially lower than the median with similar students attending

other UC campuses, the students at less selective campuses had much higher probabilities of

graduating with a science degree, often double the science graduation rate of such students at

Berkeley and UCLA. He said this held true whether or not one limited the analysis to

students intending to major in science in college, or if one considered only underrepresented

minority students or all students with potential mismatch at Berkeley or UCLA. It also held

true at several different time periods.

Dr. Sander also compared students at UCLA and Berkeley whose credentials were equal to

or stronger than their median classmates with similar students at other campuses. Since these

students would not be mismatched at UCLA or Berkeley, mismatch theory would predict that

they would not be at any disadvantage at those schools. Dr. Sander’s data (slide 19) found

8 Dr. Sander noted that in slide 10’s data set, blacks (and to a lesser extent, Hispanics) are far more clustered in

the lower-index/high-preference ranges at Michigan than are whites and Asians, meaning that conclusions as to

high-preference white rates are based on relatively few data points.

Summary of Proceedings 9
that these students had higher science graduation rates at Berkeley and UCLA than the

average rate for the median students at the other six UC campuses.

Professor Sander also reported on data from the Collegiate Learning Assessment study,9

which attempts to measure student learning at nearly 200 American colleges (slide 20). He

examined cross-section data on factors influencing whether a student was a math major,

including as independent variables student credentials, “mismatch” (measured by the gap

between a student’s credentials and the average credentials of his peers at that college), race,

and gender. His analysis found that the degree of mismatch between student and school was

the strongest (and very negative) predictor of seniors choosing to major in math; credentials

were also strongly predictive, while neither sex nor race predicted pursuit of a math degree.

He viewed this, too, as supporting hypotheses two and four (the role of credentials and

mismatch) and as cutting against hypotheses one and three (student interest and

discrimination).

(Note: Professor Sander’s slides begin on the following page.)

9 See http://www.ssrc.org/press/cla-study (accessed Apr. 6, 2009).

10 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Slide 1

Does the “Mismatch Effect” Reduce

the Ranks of Minority Scientists?

A Presentation to the

US Civil Rights Commission

September 12, 2008

Dr. Richard Sander, UCLA

Slide 2

How Significant Is the

Racial Gap in Science?

Ph.D. 100 15 26 703

Science

BA 100 36 41 454

Science

Ph.D. 100 43 21 130

BA 100 56 33 128

Gen Pop 100 100 100 100

White Black Hispanic Asian

Freq Rel

to Pop

Summary of Proceedings 11
Slide 3

Four Possible Hypotheses

• Hypothesis 1: Black and Hispanic students are less

interested in science than whites and Asians.

• Hypothesis 2: Lower achievement and credentials for Blacks

and Hispanics by the time of high school graduation translates

to lower success rates in science during and after college.

• Hypothesis 3: Minority college students studying science have

worse outcomes than similar white and Asian students,

because of factors like discrimination.

• Hypothesis 4: Many talented minorities interested in science

are admitted through preferences into colleges where their

credentials are much lower than those of their classmates.

This “mismatch” causes them to struggle in science classes

and either leave science or leave college.

Slide 4

Hypothesis One: Are minorities

less interested in science?

• The evidence is consistent and overwhelming that Black

and Hispanic high school seniors are slightly more

interested in a science career than are whites. (Asians

are still more interested, by a substantial margin.)

• When credentials are taken into account, the higher level

of Black and Hispanic interest is even more pronounced.

12 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Slide 5

Slide 6

Hypothesis Two: Do achievement levels

through high school shape

later success in science?

• Yes, very much so.

• There’s a mythology that’s been fostered by many

defenders of affirmative action that credentials have little

or no impact upon success in college. What matters is

not one’s preparation going in, but which college one

attends. Hence, preferences are crucial.

• This was a core proposition advanced by Bowen & Bok

in The Shape of the River.

Summary of Proceedings 13
Slide 7

Slide 8

14 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Slide 9

Slide

10

Michigan 4-Year Graduation Rates

Blacks 21% 50% 73%

Whites 35% 52% 70%

No

Preference

Moderate

Preference

Large

Preference

1999

Entering

Cohort

Summary of Proceedings 15
Slide

11 National Longitudinal Survey of Freshmen

Slide

12

Hypotheses Three and Four

• From my preliminary examinations of the data, it seems

likely that “credential gaps” that exist at the end of high

school account for 60-75% of the “science achievement”

gap between Blacks and Hispanics, on the one hand,

and whites on the other.

• To oversimplify, a central question is whether the rest of

the gap is due to poor treatment of minorities in college

or to the “mismatch” effects resulting from preferences.

• To test this, we want to compare similar students who

experience different levels of mismatch, and we want to

compare outcomes that control for race, mismatch, and

credentials.

16 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Slide

13

The University of California data

• In the past six weeks, Project Seaphe has obtained an

enormous volume of data from the UC system, covering

the period 1992-2006 across eight UC campuses,

ranging from the very elite (Berkeley and UCLA) to very

good but non-elite schools (Riverside and UC Santa

Cruz). It is possible to examine college outcomes – in

particular, the outcome of getting a BA in science – by

comparing students who are heavily “mismatched” at

Berkeley with similar students who attend other UC

campuses. These students will be substantially

mismatched at UCLA, but only moderately mismatched

at other campuses.

Slide

14

Summary of Proceedings 17
Slide

15

Slide

16

18 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Slide

17

Slide

18

Summary of Proceedings 19
Slide

19

Slide

20 An analysis with CLA data

Examining Predictors of Being a Math Major

As A College Senior

Black .006 .91

Gender -.03 .41

Mismatch -.25 <.0001

SAT .19 <.0001

Intercept n/a <.0001

Significance

Level

Standardized

Coefficient

Variable

20 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Richard Tapia

Dr. Richard Tapia,10 Rice University Professor of Engineering and Director of the Rice

Center for Excellence and Equity in Education, stated that under his leadership, Rice

University has produced what he believes is likely the largest number of underrepresentedminority math, science, and engineering doctoral graduates in the country. Unlike the

testimony of Dr. Sander and Dr. Elliott, Dr. Tapia’s testimony centered on graduate, rather

than undergraduate, education. He noted that Rice University is a highly competitive top

research university.

Dr. Tapia recounted his personal history as an underrepresented minority whose parents

came to the United States from Mexico, and his early education at a below-average high

school in Los Angeles where he was not counseled to attend college despite his mathematical

talent. He praised math teachers at the community college he attended for directing him to

UCLA, where he earned a doctorate in math. He described his achievements, such as being

the first native-born Hispanic elected to the National Academy of Engineering, first minority

mathematician promoted to the rank of University Professor, and an appointee to the

National Science Board under President Clinton. Dr. Tapia also cited minority STEM

graduates who have gone on to distinguished careers.11

He stated that the STEM disciplines are a fundamental asset to national economies, and that

the United States leads the world in STEM higher education, producing STEM leaders for

most of the world’s industrial nations. He stated that top research universities choose faculty

with doctorates from top research universities, and that professors with doctorates from

minority-serving or less prestigious schools are not considered for faculty positions in top

schools.

Dr. Tapia did not dispute Dr. Sander’s and Dr. Elliott’s data supporting the mismatch

theory.12 He did state, however, that in his view, minority students and faculty must have an

“equitable presence” at top research universities to serve as role models and mentors. He

asserted that including the larger number of Ph.D.s from lesser universities in data showing

total numbers of minority STEM graduates would perpetuate the stereotype that minorities

receive inferior STEM education. He said the proper form of affirmative action is ensuring

that very capable students are not excluded by an overly rigid use of standardized test scores.

In his program, he applies a cutoff score, both to exclude those who have little chance of

succeeding and to include those who may be on the threshold but will succeed with good

mentoring. He stated that applicants with combined math-verbal scores of 1400 or above are

well able to succeed, and he does not base admissions judgments on scores that are at or

above that level. With regard to cutoff scores, Dr. Tapia agreed with Dr. Sander that there is

10 Tr. at 23-24. 11 See Dr. Tapia’s statement in the “Statements” section. 12 In his written statement, Dr. Tapia stated: “The mismatch theorists have focused light on a huge problem that

I have been fighting at Rice for 20 years. The data they present are entirely credible to me because they reflect

what I have seen at Rice. So I do not dispute the data. It is the recommendations they make based upon the data

that are terribly flawed.” See Tapia Statement below at page 35 of this report.

Summary of Proceedings 21
much more predictive information at the lower ranges of SAT scores than there is at the top,

meaning that someone with combined math-verbal scores below 800 will probably not be

successful in any STEM discipline. He stated that each year his program rejects several

applicants with perfect 1600 SAT scores because test scores are not enough to predict

success.

Dr. Tapia claimed success in graduate student retention by providing peer/faculty mentoring

and community-building, eliminating deficiencies in preparation, and combating minority

students’ perceptions of isolation, which he considers the chief problem in many cases.

At the same time, he agreed that admission without retention is of negative value.13

Moreover, he conceded that most efforts to increase minority presence in STEM graduate

programs and faculties have not been effective.

He nevertheless stated that bringing a minority-serving school up to the level of Rice is not as

realistic as creating retention programs at Rice that would have the same retention success

rate as those at the minority-serving institutions. Dr. Tapia stated that a student with lower

STEM grades from a top research school is stronger than a student with top grades from a

minority-serving school. He concluded his remarks by emphasizing that “treating everyone

the same is not good enough,”14 and “if we leave schools alone and don’t fix them, then the

disaster that is happening will continue.”15

Rogers Elliott

Dr. Rogers Elliott,16 Emeritus Professor of Psychological and Brain Sciences at Dartmouth

College, stated that his data supported Dr. Sander’s findings concerning mismatch (Dr.

Elliott noted that his analysis and data published in 1996 formed an early instance of what

Dr. Sander termed “the mismatch hypothesis.”17) and that race preferences in admissions

were harming the aspirations of some black students seeking to be scientists. He asserted that

the differences are largest at the most selective universities because of their high admissions

standards (two standard deviations above average in developed ability), which some

minorities, especially some black students, fail to meet.

Dr. Elliott described his research among 5,300 students in four Ivy League schools between

1988 and 1992.18 He reported that the black versus white/Asian gap in SAT scores has

actually widened since 1988, and is now about 209 points. His data included the students’

high school and college transcripts, and SAT scores. The results (slide 1) showed that an

13 Tr. at 28. 14 Tr. at 34. 15 See http://www.caam.rice.edu/~rat/cv/minority/mismatch_theory_statement_2008-09-12.htm (accessed Jan.

8, 2009).

16 Tr. at 34–43. 17 Rogers Elliott, A. Christopher Strenta, Russell Adair, Michael Matier and Jannah Scott, “The Role of

Ethnicity in Choosing and Leaving Science in Highly Selective Institutions,” 37 Res. in Higher Ed. No. 6 at

681-709 (1996).

18 Dartmouth College; Brown, Cornell, and Yale universities. Tr. at 39.

22 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
equal portion (about 43 or 44 percent) of incoming students of the three major racial/ethnic

groups (with whites and Asians combined as one group) intended to major in science, but

that the science persistence rates were considerably lower for Hispanics and blacks: 34

percent for blacks and 56 percent for Hispanics, versus 62 percent for the white/Asian

group.19 These data showed that the average incoming SAT math score for whites and

combined white/Asian groups interested in science majors was 715 (the 50th percentile of all

incoming students); the average SAT math score for Hispanics was in the 16th percentile,

and the average SAT math score for blacks was in the 4th percentile of the white/Asian

distribution, a difficult competitive position.20 A general college preparedness score called

the academic index, which consists of high school grades and rank, and achievement and

SAT test scores, showed similar percentiles for the racial groups in Dr. Elliott’s data.

Dr. Elliott emphasized that because science knowledge is hierarchical (meaning that a

student must understand material in one course before advancing to the next) students who

arrived unprepared for the level and pace of work at the highly selective schools in his study

were unable to advance successfully through the course sequence compared to the 90 percent

of students who were well prepared. His data showed that science grades broken down by

SAT math scores reflect this.21 More specifically, 90 percent of science majors had SAT

math scores of 650 or better; of that group, 80 percent were white or Asian students. Only 25

percent of black students in the four Ivy League schools reached that score. Since the score

of 650 appeared to be a break point in the function describing the relation between SAT math

scores and the probability of majoring in science (slide 2), blacks were clearly at a

disadvantage.

Dr. Elliott’s STEM retention data for white/Asian students was 63 percent, 56 percent for

Hispanic students (Dr. Elliott viewed this figure as quite good), and 34 percent for black

students. He stated that for the year 2008, SAT math score data indicate that only about

3,20022 black students in the country reached 650, a number he viewed as problematic for

STEM recruitment to elite research institutions. He contrasted the 50 percent chance that

someone in the top third of SAT math scores in a very selective school would get one of the

science degrees awarded, with the 15 percent chance that a student in the bottom third would

get a science degree. At a less selective institution, a student with an SAT score that would

19 Students who dropped out of science programs did not usually drop out of school; they may have switched to

other majors.

20 Dr. Elliott’s data as presented to the Commission in three slides, showed an entering average Hispanic SAT

math score of 653 and an entering average score for black students of 607. The slides are reproduced

immediately after this summary.

21 For a more detailed explanation, please see the attached statement of Dr. Elliott, also available at

http://www.seaphe.org/pdf/elliott-ethnicity.pdf (accessed Jan. 8, 2009).

22 Dr. Elliott submitted corrections by communications dated April 1, 2009 and July 7, 2009. SAT score data for

2008 show that black students who scored at or above 650 on the SAT math section were at the 98th percentile

of black SAT-takers that year. See

http://professionals.collegeboard.com/profdownload/sat_percentile_ranks_2008_cr_m_w_gender_ethnic_group

s.pdf (accessed Feb. 20, 2009).

Summary of Proceedings 23
be relatively low for a very selective institution would increase his chances of getting a

science degree.23 (slide 3).

Dr. Elliott acknowledged the value of a degree from a top school.24 He stated that he did not

know how to address this dilemma, other than to point out that it is probably better for an

aspiring black scientist to go to a school where he or she could get a science degree than to

suffer the consequences of relative unpreparedness in a school where he or she was

overmatched.

Dr. Elliott’s slides are reproduced below.

Slide 1

23 Dr. Elliott referred during his testimony to three slides on view during his briefing testimony. This is labeled

“Slide 3” in this Commission report. This table can also be found at page 701 of that article and is entitled,

“Table 4. Percentage of Earned Degrees in the Natural Sciences as a Function of Terciles of the SATM

Distribution in 11 Institutions.”

24 Dr. Elliott noted that the biggest undergraduate science degree-granting schools for blacks in this country

were not considered prestigious.

24 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Slide 2 (Figures for four Ivy League schools)

Summary of Proceedings 25
Slide 3

Institution % Degrees SATM % Degrees SATM % Degrees SATM

Institution A 53.4 753 31.2 674 15.4 581

Institution B 57.3 729 29.8 656 12.9 546

Institution C 45.6 697 34.7 631 19.7 547

Institution D 53.6 697 31.4 626 15.0 534

Institution E 51.0 696 34.7 624 14.4 534

Institution F 57.3 688 24.0 601 18.8 494

Institution G 62.1 678 22.6 583 15.4 485

Institution H 49.0 663 32.4 573 18.6 492

Institution I 51.8 633 27.3 551 20.8 479

Institution J 54.9 591 33.9 514 11.2 431

Institution K 55.0 569 27.1 472 17.8 407

Medians 53.6 31.4 15.4

Note : Percentages indicate the proportion of natural science degrees awarded to

students as a function of terciles of the SATM score distribution. SATM numbers are

mean scores for each tercile, which vary depending on the selectivity and general

level of developed ability that characterizes an institution. SATM is the score on the

mathematical reasoning section of the Scholastic Assessment Test.

Tercile 1 Tercile 2 Tercile 3

Thomas Fortmann

Dr. Thomas Fortmann,25 who has an undergraduate degree in physics from Stanford and a

doctorate in electrical engineering from MIT, provided a teacher’s view of the two questions

posed by the Commission’s briefing topic: 1) why minority students disproportionately leave

STEM disciplines, and 2) whether better matching between student and school means that

more are likely to succeed.

His answer to the first question was that anyone who arrives in college with inadequate

STEM preparation will have difficulty finishing a science major, and that certain minorities

frequently have not had adequate K-12 science and math preparation. He described the

cumulative nature of math knowledge, which requires that students master information in

sequence.

He recounted his efforts to improve STEM teaching by founding an institute to train

elementary school teachers in mathematics content. He stated that attempts by programs such

as Massachusetts’s STEM Pipeline Initiative26 which attempts to prepare more K-12 students

for further STEM study, are well-intentioned, but do not address the root cause of the

problem. He offered as an example a simple fractions question given to fifth- and sixth-grade

25 Tr. at 43-52. 26 See http://www.massachusetts.edu/stem (accessed Apr. 3, 2009).

26 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
math teachers, only 24 percent of whom could answer it correctly.27 He stated that

Massachusetts will initiate an elementary teacher qualifying test and require college math

courses to address this problem by the spring of 2009. Dr. Fortmann said that teacher quality

is the most important underlying factor in student math achievement, and that math content

knowledge among teachers in urban minority schools is very low.

Dr. Fortmann’s view of affirmative action is that, in the absence of sustained remediation as

propounded by Dr. Tapia, it does not address the underlying math deficiencies in K-12

education. Dr. Fortmann thus agreed with Dr. Sander and Dr. Elliott that it will consequently

hinder some students’ STEM progress. Dr. Fortmann argued that it was worth putting the

limited resources available into increasing the pool of students able to enter STEM

disciplines, rather than just recruiting harder from the same pool. He also recounted a

statement by a dean of engineering at a major research state university that 50 percent of the

people entering engineering majors eventually switch majors because of inadequate math

preparation.28

He recommended that the Commission investigate, as a civil rights issue, why so many

minority students graduate from high school with so little STEM preparation, i.e., why they

need affirmative action at all, and what policymakers can do about it. He believes that the

answers are, among other things, school choice; better teacher preparation and more

demanding math certification requirements; and differentiated pay scales and incentives. He

also mentioned collective bargaining, accountability, standards-based testing, and school

leadership as important issues.

Robin Willner

Ms. Robin Willner,29 Vice President of Global Community Initiatives at IBM, testified that

changes in the global economy make it even more important that the U.S. provide the talent

and leadership it needs to remain competitive, and to this end, IBM has begun a STEM

program with Latino [Hispanic] students. Ms. Willner stated that other countries have

realized that their competitiveness relies on producing and keeping STEM talent. IBM’s view

is that all sources of talent from all economic and ethnic groups need to be tapped, since the

need for STEM graduates will grow by 50 percent, according to a U.S. Department of Labor

study. Ms. Willner observed that the U.S. is the only industrialized country that will increase

in population in the future, and that much of the growth will come from the Latino

community; however, this community currently makes up a very small percentage (1.5

percent) of STEM doctorates. She asserted that the high school dropout rates for Latinos

were twice that of blacks and three times that of whites.

Ms. Willner stated that commissioned research papers from Public Agenda, a nonprofit

research organization, showed that the Latino educational pipeline is virtually broken in all

subject areas, not just STEM, and that the major causes were poverty and lack of English

27 Tr. at 49. 28 Tr. at 47. 29 Tr. at 52-62.

Summary of Proceedings 27
language skills, role models, adequate parental involvement stemming from long work hours,

language barriers, lack of formal schooling, and cultural attitudes.

She related some of the actions taken by IBM, such as providing translation programming

software and early childhood reading programs, and described a joint meeting on Latino

STEM careers that IBM hosted for global companies such as Exxon Mobil, Lockheed

Martin, and AMD. The meeting produced four chief recommendations, the second of which

bears on the testimony of Dr. Sander and Dr. Elliott: 1) recruit, prepare, and retain qualified

STEM teachers, increase the number of second-career STEM teachers, and redesign existing

teacher preparation courses and certification; 2) reduce attrition in minority STEM graduates

by moving them to programs where they will succeed and also to make sure they can succeed

at the highest levels by providing appropriate mentoring, support services, and financial aid;

3) increase the popularity of STEM careers in the Latino community; and 4) increase the

Latino high school graduation rate by providing mentors, requiring performance standards of

both high school and student, and providing internships.

28 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Discussion

Vice Chair Thernstrom invited the panelists to respond to each other’s testimony before

opening the question period to Commissioners.30

Professor Sander began the discussion by summarizing the points of agreement among the

panelists, such as the academic credentials gap between racial groups by the end of high

school as the single biggest cause of the problems under discussion. He observed also that

Dr. Tapia and Dr. Fortmann believed that such gaps might be counteracted by good academic

support. Dr. Sander stated that most of the panelists did not deny that there was a mismatch

problem, but differed on methods of handling it. Dr. Sander also posited that the credentials

gap in large part was not caused solely by K-12 education, but by other environmental factors

unrelated to schooling, such as low birth weight, parenting practices, socioeconomic

differences, and reading habits. He also referred to studies31 that show that race does not

predict credential score gaps if such environmental factors are controlled. Dr. Sander

concluded that policymakers should look beyond race to seek out those who need help and

end racial preference programs, particularly in the most selective universities whose use of

race leads to preferences chiefly for upper-middle and upper-class applicants.

Dr. Fortmann agreed that socioeconomic factors were important, as were parenting practices,

and that K–12 education was not the sole cause of the credentials gap. He asserted, however,

that there were schools, many of them charter, that improved the educational outcomes for

students from disadvantaged backgrounds.32 Ms. Willner and Dr. Tapia agreed that such

schools could make a large difference. Dr. Tapia cited two viable K–12 programs in which

he was involved,33 and stated also that the practice of including all Hispanics in one group

was misleading, since educational outcomes differ among subcategories such as MexicanAmerican, New York Puerto Rican, and Cuban, for example. He recounted coping methods

he used as a UCLA student that included taking a reduced course load, and improving his

performance in increments rather than all at once.

Commissioner Kirsanow asked the panelists, particularly Ms. Willner, whether minority

STEM graduates of historically black colleges and universities (HBCUs) were in fact

incompetent by private sector standards, and whether the private sector thought it was

important that their new hires come from elite schools such as Harvard, Stanford, and

Cornell.

30 Tr. at 63-149. 31 See, e.g., Roland Fryer, Jr. and Steven Levitt, “The Black-White Test Score Gap Through Third Grade,”

NBER Working Paper Series, Working Paper 11049, National Bureau of Economic Research,

http://pricetheory.uchicago.edu/levitt/Papers/FryerLevitt2005.pdf (accessed on September 21, 2009); 8 Am.

Law Econ. Rev. 249-281 (2006).

32 Dr. Fortmann cited a case study of 15 schools in “It’s Being Done: Academic Success in Unexpected

Schools,” by Karin Chenoweth, published by Harvard Education Press (2007).

33 “Rising Above the Gathering Storm,” http://www.nap.edu/catalog.php?record_id=11463 (accessed January

13, 2009).

Discussion 29
Dr. Tapia asserted that the HBCU STEM graduates were not incompetent, but insufficiently

prepared to be competitive with graduates from schools such as Rice. Also important, in Dr.

Tapia’s view, was recognizing that a degree from a highly selective school is necessary in

order to be hired as faculty at a similarly selective school. Part of the problem, he stated, was

that some HBCUs are wholly nonselective and are unable to enforce academic standards for

fear of failing too many students. Dr. Tapia questioned whether HBCUs were at a point

where they should reevaluate their role, since their original purpose resulted from segregation

and the nation’s colleges are no longer segregated.

Commissioner Kirsanow asked Ms. Willner to comment. She answered that the most

important qualification was the applicant’s knowledge and skill, not the reputation of the

school, but that more selective schools produced more highly skilled and creative graduates.

Vice Chair Thernstrom asked whether IBM had its own testing process for applicants. Ms.

Willner stated that it did, but that to some extent the company used the reputation of the

school as a proxy for such evaluation because of IBM’s familiarity with the schools’

programs.

Professor Sander addressed Commissioner Kirsanow’s question by differentiating between

mismatch in undergraduate and graduate STEM programs. Dr. Sander asserted that faculty

hires are dependent almost entirely on the graduate advisor and school attended, whereas the

science minority STEM dropout problem was an undergraduate problem that could be

alleviated by reducing the mismatch between student and school. He referred to social

science studies that showed HBCU graduates in both STEM and non-STEM majors who

perform well in college have slightly better outcomes over the years than students who

perform poorly at elite schools.

Commissioner Gaziano asked Dr. Tapia if he thought it was better to have one successful

STEM minority graduate from an elite school and a hundred STEM dropouts, or 100 STEM

doctorates at slightly lesser schools. Dr. Tapia answered that 100 successful STEM graduates

from lesser schools was a better outcome.

Commissioner Gaziano then asked how large a mismatch could be before it undermined

success. Dr. Tapia answered that the question should be why so many top math graduate

schools made no effort to retain capable minorities, particularly public universities. Dr.

Elliott answered that if the top schools reduced the degree of the mismatch of their minority

STEM admits by admitting only the top half of those currently admitted, then schools down

the selectivity index would have a greater number of properly matched minority STEM

students available to them. Such students would then be at the 30th percentile of

competitiveness within their schools, as compared to the fourth percentile. He acknowledged,

however, that schools that are less selective also have much less money with which to assist

students, and minority students often need such help. Dr. Elliott supported some degree of

affirmative action in public universities, but pointed out that at the graduate level, elite

schools take very high-level students and push them to meet extremely high standards. The

outcome is a high level of performance at such schools, which if lowered, would result in a

loss of the school’s reputation and elite status, and a loss in performance quality in their

programs.

30 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Dr. Tapia agreed with much of what Dr. Elliott had said concerning high levels of

performance in elite private schools, but stated that public universities had a moral obligation

to do more than just research using the highest performing students available regardless of

racial or ethnic imbalances.

Vice Chair Thernstrom asked what effect there would be on K-12 schools with ill-trained

teachers if colleges required uniform standards for every applicant; and whether such

standards would result in increased pressure on such K-12 schools because they would be

unable to ascribe blame to others.

Dr. Sander agreed that the mismatch effect is a problem for those students who receive the

largest preferences, while his data concerning those students who receive modest preferences

did not show a mismatch effect. He stated that socioeconomic preferences were less likely

than racial preferences to produce mismatch effects because those credential gaps were

smaller; economically disadvantaged students who persevered all the way to an elite school

generally displayed essential elements for success, such as determination and drive. Dr.

Sander also asserted that a student coming into a school at the 25th or 30th percentile in

terms of credentials instead of at the 5th or 10th percentile could use the resources of the elite

school more effectively.

Ms. Willner agreed with Dr. Tapia that the size of the preference (degree of mismatch) is

what determines a student’s success or failure in a STEM program. She stated that accepting

an applicant whose credentials are far below those of the other accepted candidates is

different from accepting a student at the top of the SAT scale (1400–1600) with some leeway

for modest differences from the median. She agreed with Dr. Tapia that someone at the lower

end of the SAT scale with a combined score of 800 would not succeed in a selective STEM

program. She also agreed with Dr. Tapia that public universities have an obligation to

provide effective support and interventions to students admitted to their programs, and that

IBM views as critically important the existence of a diverse group of STEM graduates

available to global companies. Dr. Tapia emphasized that it was important for potential

minority students to see faculty of their own ethnicity or race because that gave them a sense

that they were not alone, and that others of their ethnicity or race had succeeded.

Commissioner Gaziano asked Dr. Fortmann what minimum qualifications math teachers

should have; for example, whether second-career STEM professionals need further

certification to be able to teach in K–12 schools. Dr. Fortmann responded that Massachusetts

allows someone to obtain a provisional license for immediate entry into K-12 teaching, but

that requirements differ from district to district. He noted also that such teachers rarely enter

elementary or middle schools, so there is still a need to improve the qualifications of existing

K-8 teachers. Ms. Willner added that IBM offers its employees a teaching skills program that

facilitates the transition to K–12 STEM teaching, because knowing the content area is not

enough to become a good teacher. The program, called “Transition to Teaching,” helps

develop the other essential skills in teaching, and provides a paid leave of absence for student

teaching before the employee leaves IBM.

Discussion 31
Vice Chair Thernstrom observed that other programs also have been successful in placing

non-education majors into classrooms after very short preparation, such as the Teach for

America program. Ms. Willner agreed, but added that in her experience, most people who

participate in that program claim that the first year of teaching was unnecessarily difficult

because of inadequate preparation.

Dr. Fortmann agreed with Ms. Willner’s support of more extensive teaching preparation than

what is provided in the Teach for America program, but did not believe that an entire year of

education courses, or the onerous certification requirements in many states, was necessary.

Commissioner Kirsanow stated that the U.S. Supreme Court’s Grutter decision34 set limits on

a school’s use of racial or ethnic preferences of any size in admissions. He pointed out that

however important diverse points of view were in law schools for admissions purposes, and

thus arguably within the bounds of the Constitution, the same could hardly be said of physics

and math disciplines in which ethnic differences were irrelevant to the quantitative analysis

performed.

Dr. Tapia believed that an ethnically broad student and faculty community teaches white

students how to deal with people of different ethnicities and races. He also stated that such

experience in a broadened academic environment allowed students to build a multi-ethnic

academic community that would last throughout their lives. He added that, in his view, court

decisions had significantly cut back affirmative action programs, with the result that colleges

now recruited from abroad to the detriment of American minorities.

Professor Sander raised two points concerning the practical effects of race preferences. First,

he stated that the use of preferences may produce both positive and negative results, meaning

that preferences may combat negative stereotypes by the increased presence of minorities,

but may also reinforce negative stereotypes if the ability differences are large—on the order

of a two standard deviation gap. Second, he stated that large racial preferences further isolate

such students socially from normally admitted students, resulting in increased selfsegregation along racial lines. Professor Sander supported this statement by citing a recent

study posted on Duke University’s website by three economics professors at Duke

University.35 He also reported results of his own study of study groups in law school, which

found that if there are large racial preferences, whites and Asians assume that the best

students to invite into their study groups will be whites and Asians rather than blacks and

Hispanics. He asserted that study groups are important in law school because they improve

students’ grade point averages, and that study groups composed only of minority students do

not improve grades.36

34 See Grutter v. Bollinger, 539 U.S. 306 (2003). 35 Peter Arcidiacono, Shakeeb Khan, and Jacob Vigdor, “Representation versus Assimilation: How do

Preferences in College Admissions Affect Social Interactions?” November 5, 2007, available at

http://www.econ.duke.edu/~psarcidi/knewminisk.pdf (accessed Jan. 23, 2009).

36 Tr. at 111–12.

32 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Vice Chair Thernstrom observed that Harvard undergraduate admissions does not give large

racial preferences, but that before the ban on preferences in California, the racial gaps at

Berkeley between underrepresented minorities and whites or Asians was enormous. The Vice

Chair also observed that the pool of high-SAT-score underrepresented minorities is small,

and absorbed by very few schools.

Commissioner Taylor said he found it disturbing that schools were not communicating

information about mismatch and its consequences to minority students and their families

before they determine which college to attend, and how much success they might achieve

relative to other students. He stated that a student needs to know what the range is at any

particular school and whether he or she is within that range; if the student is below that range,

no additional help from the school or anyone else will be sufficient. He emphasized that the

critical public policy perspective should focus on what will help the minority community to

do well.

Professor Sander articulated four policies to address Commissioner Taylor’s points that he

believed all the panelists would endorse. First, he recommended transparency, meaning that

African-American or other minority students ought to know before selecting a college what

the ultimate outcomes have been for students with their credentials. Commissioner Taylor

asked the panelists whether they would agree with Professor Sander’s first point, and they

replied affirmatively. Ms. Willner added that she thought the colleges also owed students

evidence demonstrating that they had given needed help to similar students in the past.

Commissioner Taylor endorsed this suggestion and pointed out that this information was no

different than providing prospective athletic students a coach’s track record of success. He

observed that policies of affirmative action had been more concerned with enrolling a target

number of black and Hispanic students than helping them make sound decisions about the

best colleges for them as individuals.

Professor Sander next suggested that colleges be held accountable to all prospective and

current students, meaning a) they disclose their record of retaining science majors to

graduation; b) they take responsibility for improving their record; c) they change their

admissions practices; or d) all of the above. His third suggestion was that college admissions

emphasize socioeconomic preferences over racial preferences. Lastly, he recommended that

colleges curtail large mismatches in admissions that have clearly shown negative effects on

minority students.

Commissioner Kirsanow asked Professor Sander for his view of the extent of current

transparency and accountability. Professor Sander stated that on a scale from zero to 100, it

was a 3. Dr. Tapia agreed that getting such information was extremely difficult, and said the

recommendation for greatly increased transparency and accountability was excellent. He also

gave examples of successful programs, such as Rice’s, that were able to recruit able students

by word-of-mouth because of a reputation for producing minority successes. He gave as a

cautionary example a student who told Dr. Tapia that he had been accepted to Princeton with

Discussion 33
a 940 combined SAT score, and had been told (and believed) that the average SAT score at

Princeton was 950. Dr. Tapia said he urged him to check further.37

Commissioner Taylor stated that he strongly opposed any public policy that masked

discussion of such information, and further, that he believed concealing such information was

intentional.

Dr. Elliott agreed that the size and significance of mismatch in schools was hard to obtain,

and that schools concealed such data in order to meet their quotas or goals for enrolling

minority students. Vice Chair Thernstrom asked whether colleges cared more about showing

off diversity of their freshman classes than results of such policies in senior year with respect

to the numbers of minority students in STEM majors. Ms. Willner agreed that letting a

student in was easy, but should be matched by a college’s willingness to help that student

succeed.

Dr. Tapia stated that he visited Berkeley and UCLA frequently and was saddened to see the

effects of the California ban on racial preferences there, since administrators had made no

effort to create other programs that would work for minorities, such as the “Ten Percent

Plan” in Texas. The Texas law requires the flagship campus to accept the top 10 percent of

students in each Texas high school regardless of SAT scores, which Dr. Tapia believed has

been successful because the university supports the students in special programs once they

arrive on campus.

Vice Chair Thernstrom asked Dr. Sander why he thought socioeconomic preferences were

less likely to result in mismatch than racial preferences. Professor Sander responded that by

broadening the definition of diversity to include socioeconomic preferences, colleges would

increase the size of the applicant pool and decrease the size of the mismatch they would have

to accept. Second, his data indicated to him that credentials more likely understate potential

in lower socioeconomic status (SES) applicants, and they perform better than expected.

Third, the resulting smaller gap would not, in his view, create social isolation problems of the

kind discussed earlier in the hearing. His experience with expanding admissions to include

low SES at UCLA after Proposition 209 passed in California showed that this approach

worked. He added that this program was not continued because it didn’t produce enough

African-American students to satisfy administrators, and that in its place the law school

started a “Critical Race” program38 for minority students admitted with large credential gaps.

Professor Sander stated that the Critical Race program was a subterfuge that produced even

fewer black law students; during the course of the program, 30 white applicants were denied

37 Princeton’s current average SAT verbal and math combined score is 1485. See

http://collegesearch.collegeboard.com/search/CollegeDetail.jsp?collegeId=4221&profileId=6 (accessed Feb. 24,

2009).

38 One definition is as follows: “Critical Race Theory (CRT) is an intellectual movement of progressive law

scholars–primarily of color–who view the law as complicitous in sustaining white supremacy, and, by

extension, upholding similar hierarchies within gender, class, and sexual orientation.”

http://tarlton.law.utexas.edu/lpop/etext/lsf/isaksen24.htm (accessed September 17, 2009).

34 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
entry with Law School Admission Test (LSAT) average scores of 163 and eight black

applicants were admitted with an LSAT median of 154.39

Dr. Tapia interjected a comment that UCLA law school had produced Johnny Cochran;

Professor Sander responded that that was an example of entirely race-neutral policies. He

added that UCLA’s preference programs produced great successes for some individuals, but

large preferences had counterproductive effects.

Vice Chair Thernstrom observed that the Bok and Bowen study was of undergraduate

admissions only, and that about half the underrepresented minorities had not needed

preferences. Professor Sander agreed, noting that Barack Obama had not needed preferences.

Dr. Tapia added that the Bowen and Bok study was limited to African-Americans and did not

include Hispanics.

Commissioner Kirsanow asked whether schools are discouraging the participation of Asians,

who are overrepresented in science programs. Professor Sander said probably not, although

he hoped to study that issue. Dr. Tapia stated that to the contrary, U.S. Asians are becoming

underrepresented because of assimilation, and schools are bringing in more foreign-born

Asians. Professor Sander disagreed in part, referring to his U.S. Census data that showed

Asians still hold a large proportion of science doctorates.

Vice Chair Thernstrom asked whether the decreasing portion of Asians in graduate school

just showed that they were understandably turning to well-paying business careers, as were

other minorities. Dr. Tapia suggested that they were turning to other careers simply because

they believed, incorrectly, that a few low grades disqualified them from graduate school.

Commissioner Yaki observed that it is misleading to consider all Asians as one group, since

there are great disparities within that group based on assimilation over generations into

American society and outcome differences between Japanese or Chinese groups and other

Asians. Both Vice Chair Thernstrom and Dr. Tapia agreed. Dr. Tapia stated that a group

label is also misleading for those considered “Hispanic” since the disparities in outcomes

within such a group are extreme. He stated also that there have been changes in cultural

adherence to educational expectations over time within some ethnic groups, resulting in some

preference for taking well-paying jobs versus aspiring to attend graduate school, or, in other

cases, reduced educational aspirations.

Commissioner Yaki also claimed that since the passage of Proposition 209, the University of

California system is accepting foreign Asian students who pay full tuition as a means of

avoiding payment of subsidies that accompany in-state students. Professor Sander agreed that

the University of California is attempting to maximize its tuition revenues but asserted also

that the poorest students in the Los Angeles area are in fact Cambodian, not black or

Hispanic.

39 This represents about a one standard deviation gap in the LSAT.

Discussion 35
Vice Chair Thernstrom stated that it is not clearly in the public interest that students enter

graduate programs instead of the business world. Dr. Tapia agreed, but asserted that it is bad

for University of California and Ivy League math departments to have no AfricanAmericans.

Commissioner Kirsanow asked Professor Sander to what degree the mismatch in STEM

disciplines differed from the mismatch in other disciplines, such as law. Professor Sander

answered that the STEM mismatch gap at the undergraduate level is uniquely problematic as

a result of the linear sequence required for science and math courses, and the impossibility of

watering down the required curriculum to push students through to graduation. He observed

that law is similar in that it requires bar passage, whereas the academic discipline of English,

in his opinion, has no good outcome measures.

Dr. Tapia added that as a result of his frequent work with lawyers as an expert witness in

federal court trials, he viewed law and science differently. He claimed that creativity was not

a necessary part of success as a lawyer, whereas it is for STEM graduates.

Commissioner Yaki observed that Professor Sander had narrowed his definition of mismatch

and that the gap may be due to factors not discussed in this briefing. He also stated that

affirmative action in higher education, characterized by Professor Sander as dying, was

instead being killed by initiatives across the country. Commissioner Yaki also stated that

although he was not criticizing the panelists who were in attendance, he did not believe that

they represented a balanced panel on the subject. He further indicated that he was glad that

panelist Hazel O’Leary (President of Fisk University and former Secretary of Energy), who

had accepted an invitation to participate in the briefing (possibly to speak about the role of

HBCUs in STEM) and then cancelled, was not attending this briefing. He stated that the

easier accessibility of HBCUs was used as an excuse for doing away with affirmative action,

and noted that Dr. Tapia had testified that the HBCUs were insufficient with regard to STEM

graduates. Commissioner Yaki stated that affirmative action is about measuring potential,

and that closing off access to selective research universities because of statistics would not be

acceptable. The briefing then ended.

36 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Statements

(Note: Statements are unedited by the Commission and are the sole work of the author.

Professor Sander submitted slides in lieu of a written statement that are appended to the

summary of his testimony, supra.)

Richard Tapia

The Flaws in the Mismatch Theory

Picture the nation’s research universities in the mid-1960s. Legal and discriminatory

obstructions had allowed only a very few underrepresented minorities to gain admission to

the nation’s top science and engineering institutions. For instance, until 1964, when its board

petitioned the courts for a change of its charter, Rice University had been constrained to

educate only the "white inhabitants of Houston and Texas.” Raymond Johnson then became

the first African-American student admitted to Rice and went on to earn his Ph.D. in

mathematics in 1969.

His Rice Ph.D. launched a very successful career, including the chairmanship of the

Department of Mathematics at the University of Maryland. Stories of early minority

scientists and mathematicians produced in this country are amazing, but reflect a truly sad

component in our educational history. The few that were produced in those early times

invariably were so brilliant with so much potential in their fields that someone in their

department would champion their admission, and of course these students were quite

successful. But what about all of the other minorities who could have made it, yet had no

champions? Certainly this has been a great loss to the country’s productivity and leadership.

In the mid-1960s, affirmative action was born. America’s universities began to use

affirmative action policies to increase the participation of minority groups in higher

education. Designed to level the playing field, university admissions policies attempted to

normalize for differences in the quality of academic preparation. Admissions criteria were

developed to identify students with the capacity to succeed but who were not identified

through traditional admissions criteria. Yet these policies have been controversial throughout

their history and have faced repeated legal challenges—with much of the controversy

centering on whether affirmative action is reverse discrimination and unfair to white students

rejected in favor of minority applicants who are perceived as “less qualified.”

Recent controversy about the fairness of affirmative action now raises a very different

question. Some are now claiming that affirmative action policies can be unfair to the

minority students that they are intended to help. The current “Mismatch Theory,” promoted

Statements 37
by Panelists Rogers Elliott40 and Richard Sander41, suggests that minority students are more

likely to leave science and engineering when affirmative action has placed them into colleges

for which they are not prepared. They contrast this failure with the success that

underrepresented minority students experience at less rigorous schools, especially at

Minority Serving Institutions (MSIs), and suggest that minority students would be better

served by attending less competitive schools where they can be more successful.

It is clear that what many, including several of my colleagues who are underrepresented

minorities, want is a strong refutation of the Mismatch Theory as a whole--that it is totally

wrong with no foundation or no basis. I claim that the Mismatch Theory is terribly flawed,

that it could set underrepresented minorities back 40 years in science participation and

achievements, but its flaw is not in its data but in the conclusions drawn by Professors Elliott

and Sander. The mismatch theorists have focused light on a huge problem that I have been

fighting at Rice for 20 years. The data they present are entirely credible to me because they

reflect what I have seen at Rice. So I do not dispute the data. It is the recommendations they

make based upon the data that are terribly flawed.

I should explain why I believe that I was asked to serve on this panel. I have been a

mathematician at Rice University since 1970. I received a B.A. in mathematics from UCLA

in 1961, and a Ph.D. in mathematics from UCLA in 1967. I have received numerous awards

for my accomplishments as a mathematician: I was elected to the National Academy of

Engineering, appointed to the National Science Board by President Clinton, and at Rice

University promoted to the position of University Professor, of which there have been only

six named in the history of the university. Upon first glance this appears to look like any

traditional academic path to success. We make all kinds of assumptions about the

background of such individuals, including the certainty and predictability of the path to

success. In my case, most of those assumptions would be wrong.

I was born in Los Angeles to parents who immigrated from Mexico. I attended a belowaverage high school in the Los Angeles Unified School District. I was not directed to college

by my teachers or counselors although I had demonstrated strong mathematical talent. I

started to work at a muffler factory where a co-worker recognized my talent and daily

insisted that I go to college. I often think of how different my life would have been if this

hadn’t happened. I was very fortunate. I began at community college, where I was strongly

directed to UCLA, and away from less selective four-year colleges, by two of my community

college math professors. Little did I know that this advice would be critical to my career. I

went on to get a Ph.D. because I saw other students with less mathematical talent than I had

who were going on and felt that if they could, I could too.

40 Elliott, Rogers, et al. “The Role of Ethnicity in Choosing and Leaving Science in Highly Selective

Universities.” Research in Higher Education. Vol. 37, No. 6 (1996).

http://www.springerlink.com/content/l662845727427n33/

41 Sander, Richard, 2005. “A Systemic Analysis of Affirmative Action in American Law Schools,” Stanford

Law Review 57 (2) 367-484.

38 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
After receiving my Ph.D. from UCLA, I was directed and guided by David Sanchez, the only

underrepresented minority faculty member in the UCLA Mathematics Department, to faculty

positions at Wisconsin, Stanford, and Rice. This intervention and guidance was probably the

most important in my entire professional life. At many junctures, my life could have taken a

very different path rather than to University Professor. Like so many I could have easily

fallen through the many dangerously wide cracks. I owe my success to my education at a

research university. While at Rice, I have served as dissertation director or co-director for

many successful minority doctoral recipients in science, technology, engineering, and

mathematics (STEM). Some of them, perhaps most of them, would fit the pattern of the

Mismatch Theory, entering Rice less prepared than the majority of their fellow Rice students.

Also, I have taught many underrepresented minority Rice undergraduates, and again, some,

perhaps most, fit the pattern of the Mismatch Theory. Over the years, I have been frustrated

at the number of Rice’s underrepresented minority students who migrate from science and

engineering to humanities or social sciences, where they have experienced more success.

Selective research universities recruit some of the nation’s most capable minority students,

who enter intending to pursue a career in science or engineering, and then lose

disproportionate numbers of them to other disciplines. I agree with Sander and Elliott that

admission of minority students without retention is of negative value. This is what I have, for

years, called the “loss of the precious few.” Where I strongly part with Sander and Elliott is

in what we should do about it. Sander and Elliott say that we should steer students to less

challenging schools where they are more successful. According to them, this will be better

for the students and better for the nation because it will increase the numbers of

underrepresented minority students receiving degrees in science and engineering. I say we

should insist that elite research universities put into place programs that have proven

successful at supporting students so that they are successful. Simply stated, in a “sink or

swim,” non-mentoring, non-supportive environment, which is what we see at many of our

elite research schools, those with poorer preparation will rarely succeed, minority or

majority. Why are we not demanding from public and private universities that receive federal

funds that which is critical for the health of the nation--quality education of all our citizens?

Why are we letting them off the hook as they conveniently build an ever increasing base of

foreign STEM graduate students and faculty42?

Creating a Permanent Underclass

What is wrong with Sander’s and Elliott’s resolution of this problem? Why do I find it a huge

mistake? In my opinion, nothing can do more to establish minorities as a permanent

underclass in science and engineering than this.

If the goal is just to produce larger numbers of underrepresented minority scientists, then the

Mismatch Theory is a great idea, but numbers of degrees alone are not a good measure of

success. Underrepresented minorities must be competitive with the overall population; how

else can we break the stereotype? The distribution cannot be skewed toward weaker schools.

Steering minorities to lesser schools reminds us of the separate but equal mantra. It turns out

42 Tapia, Richard A. "True Diversity Doesn't Come From Abroad.” Chronicle of Higher Education, p. B34.

September 28, 2007.

Statements 39
that separate but equal is always separate, but never equal. But this is worse. This assumes

from the start separate and weaker. This would take us back to the pre- to mid-60s, where

only the very rare minority student who has been prepared well and tests well under

traditional admissions criteria would be admitted to the nation’s research institutions.

Race and ethnicity should not dictate educational destiny. Steering capable students to lesser

schools puts a cap on their potential achievements. Top research universities choose faculty

from Ph.D.s produced at top research universities. If we underrepresented minorities are ever

to be an equitable presence as faculty at our top-level schools, then our students must be

schooled at those same institutions. Leadership in science and engineering comes from top

research institutions. MSIs do some things very well. Their students speak warmly of how

confident and supported they felt in their experiences there. Research universities should

learn from them how to nurture that kind of confidence, but Ph.D.s produced at MSIs will not

become faculty at top research universities. We need minorities who will become national

STEM leaders, and these have to be produced by institutions that are recognized as giving

credibility to the scientific accomplishments of the individual.

Below is a list, which is not exhaustive, that I quickly generated with a few examples of

people that I know who received their Ph.D. in science or engineering from an elite research

school and who have gone on to assume national scientific leadership.

National Leaders in Science and Mathematics who are Underrepresented Minorities

Name Ph.D. Current Leadership Position

African-Americans

Shirley Ann Jackson MIT President, RPI

Freeman Hrabowski Illinois President, University of Maryland Baltimore Co.

Shirley Malcom Washington Head of Education Programs, AAAS

William Massey Stanford Professor, Princeton

Arlie Petters MIT/Princeton Professor, Duke

Sylvester Gates MIT Professor, Maryland

Director, Center for String and Particle Theory

Mexican-Americans

Hector Ruiz Rice Executive Chairman of AMD

Rodrigo Banuelos UCLA Head, Mathematics, Purdue

Francisco Cigarroa UT/Harvard President, UT Health Science Center, S. Antonio

Richard Tapia UCLA University Professor, Rice University

Carlos Castillo-Chavez Wisconsin Regent Professor, Arizona State

Where is the list of individuals with Ph.D.s from lesser universities who have outstanding

scientific accomplishments or outstanding scientific leadership accomplishments?

40 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
The Systems Are Broken

Consider three systems that prepare minority students: A) K-12 schools, B) MSIs, and C)

research institutions. For very different reasons, none of these adequately promotes equitable

representation in science and engineering. But consider, which problem is easier to solve?

A. Transform urban K-12 schools that educate the vast majority of underrepresented

students so that they prepare students equally to the best K-12 schools,

B. Bring MSIs up to the academic excellence of research institutions so that capable

minority graduates will be competitive with students from elite schools in the

industrial job market, professional leadership positions and graduate and professional

school, or

C. Design and implement programs at the most selective research universities so that

capable minority students have the same retention rates and confidence levels in

science and engineering as those at minority serving institutions.

Clearly C has the most viable solution. A by-product of this solution is the added bonus of

enhanced training and opportunities and a greater likelihood of ascending to leadership

positions. It has taken more than a century to build the sophisticated machinery of research

universities.

So What Do We Do Now?

Solving the three problems described in A, B, and C above would require a giant overhaul of

the entire systems. While we should keep such an objective in view, we cannot wait for this

change. There are things that we can do short term that I believe will have a significant

impact on improving the representation of underrepresented minorities in STEM careers and

leadership positions across the full spectrum of opportunities. My recommendations are as

follows.

Recommendation for Dealing with Problem A

Talented underrepresented minorities should be identified early in their education

(elementary and middle school) and motivated and directed to attend the best magnet

secondary schools in the city. This activity would involve working with the parents and the

school districts to facilitate and implement these plans. This recommendation has been

influenced by the following experience. At the present time at Rice University I am working

with three outstanding minority Ph.D. candidates in mathematics and in computer science.

All three have distinguished themselves in their research and in their academic

accomplishments, including being awarded prestigious National Science Foundation

graduate fellowships. Two are African-American and one is Mexican-American. All three

were born and raised in the minority areas of large U.S. cities. However, each was directed to

a STEM magnet school in their city, performed well, and was encouraged to apply to

selective research universities for undergraduate training. All three attended Rice as

undergraduates, where I met them and encouraged them to attend graduate school (not

necessarily Rice). They received excellent high school and undergraduate preparation and are

Statements 41
now outstanding graduate students. I expect to hear in the somewhat near future that they are

excellent STEM faculty at research universities in the country.

Recommendation for Dealing with Problem B

Many MSIs are open admissions (all who apply are admitted) and also try to be all things to

all people. I have a colleague who teaches chemistry at a local Historically Black College and

University. He says that in his introductory classes he has some outstanding students and

some students who are extremely poorly prepared, and that there is no way that he can do

justice to either group of students when they are all in the same class. His level of frustration

is extremely high. I recommend that MSIs adopt a magnet secondary school format. They

should develop excellent undergraduate courses in selected disciplines and only allow

selected, well-prepared students to take these classes. In this way the best students will be

well prepared for graduate work in the appropriate discipline at a research university. The

details involved in implementing this suggestion would require more thought, but I believe

that the direction is correct.

Recommendation for Dealing with Problem C

The challenge is to admit underrepresented minority students in larger numbers in science

and engineering at the nation’s research institutions and then support them to be successful.

The research schools must be held accountable for both admission and retention of minority

students in their chosen disciplines through the completion of their degrees.

To address admissions, we must evaluate our admissions criteria. I refer to this as second

stage affirmative action. Is it excluding individuals with talent to succeed? At Rice, in both

graduate and undergraduate admissions, we have successfully turned to what I call the

Threshold Approach. We pick a threshold level at which students will be successful that has

been determined from years of experience of working with all students. Actually the

threshold level is a fuzzy interval of scores. Those students with scores significantly above

the threshold are deemed equivalent as far as the test score goes, and the score is dismissed

and admission decisions are guided by other factors. Students with scores significantly below

the threshold value are not accepted, and those students with scores near the threshold value

are looked at with extra care. My experience has been that there is no predictive value at the

high end of the test score. For example, there is essentially no value in favoring a student

with a combined SAT score of 1500 over one with a combined score of, say, 1300.

The same can be said for a graduate student whose GRE score is in the 95th percentile versus

one whose GRE score is only in the 85th percentile. However, I have never seen an

undergraduate student at Rice succeed in math, science, or engineering with a combined SAT

score below 900.That is, there is much more predictive information at the low end of the

scale than there is at the high end of the scale. Indeed, each year Rice rejects a good number

(say five or so) of undergraduate applicants who have earned perfect 1600 SAT scores. Of

course, the Rice admissions officers feel that some of the high-scoring SAT students were

lacking in other significant evaluation components. The misuse of standardized test scores,

guided by the belief that there is predictive power at the upper level of the scale, is one of the

worst enemies of underrepresented minorities. I have seen underrepresented minority

students graduate from Rice with honors, and yet they entered with modest SAT scores,

42 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
albeit, the highest scores in their minority school. At Rice this is particularly true of Hispanic

women.

Following these guidelines, we have produced a very large number, probably the largest

number in the country, of underrepresented minority doctoral recipients in mathematics,

science, and engineering. In the last 10 years approximately 1,000 STEM Ph.D.s have been

produced in the country, and Rice has produced more than 60 of these doctoral students. One

year the National Science Foundation informed Rice that in that year we had produced

approximately half of the nation’s doctoral recipients in the mathematical sciences. The

Mathematics Departments at the University of Iowa, through the leadership of David

Mandersheid, Cornell University, and Arizona State also have good Ph.D. productivity rates

for underrepresented minorities in mathematics; in the latter two situations the champion has

been Carlo Castillo-Chavez. Again, success comes from strong commitment, aggressive

support, and a champion. These successes demonstrate that it is possible to produce minority

Ph.D.s at a high rate at research universities. We now offer a success at the undergraduate

level, as well. Due to the Texas Top 10% Rule43, the Mathematics Department at the

University of Texas Austin has the highest percentage of underrepresented minority

undergraduate mathematics majors (nearly 30%) of any research university in the country.

With innovative support programs they retain minority students through graduation at a rate

above the majority student rate.

My summarizing point here is that underrepresented minorities need not be sent to MSIs to

succeed. With support and caring we can succeed at the best schools in the country. Indeed,

many of us have. And more of us will.

The Consequence of the Mismatch Theory

I suspect that many faculty and administrators from research universities would breathe a big

sigh of relief when they read about the Mismatch Theory. It certainly lets them off the hook,

doesn’t it? What it does is reduce expectations and set the country’s research institutions

back to pre-1964. It ignores all that we have learned about educating minorities and

guarantees the formation of a permanent science underclass in America. A two-tiered

America is certainly not healthy for the country.

43 Created to avoid the impact of Hopwood v. Texas, the case banning the use of race as a factor in admissions,

1997’s Texas House Bill 588, guarantees Texas students who graduate in the top ten percent of their high

school class automatic admission to all state-funded universities.

Statements 43
Rogers Elliott

(Note: Professor Elliott submitted the following article in lieu of a written statement, which

may also be found at http://www.seaphe.org/pdf/elliott-ethnicity.pdf (accessed July 27,

2010). It is reprinted by permission of the copyright holder.)

The Role Of Ethnicity in Choosing and Leaving Science In Highly Selective Institutions

From Research in Higher Education, Vol. 37, No. 6, 1996

Authors: Rogers Elliott, A. Christopher Strenta, Russell Adair, Michael Matier, and Jannah Scott

(Foreword: This study sought to assess the role of ethnicity in both initial choice of, and persistence

in, science majors. Standardized test scores, high school records, initial concentration preference,

college grades, and final majors of all the white, Asian, black, and Hispanic students who enrolled

in 1988 at four highly selective institutions provided the database. Despite relative deficits in

scores on measures of preparation and developed ability, blacks entered college with a strong

interest in majoring in science. Black students interested in science also suffered the highest

attrition from it; Asians were lowest, with whites and Hispanics near the average attrition of 40%.

Ethnicity did not add significantly to ability and achievement variables in predicting attrition from

science. The results are discussed in terms of two main issues: first, the effect of different

standards of selection for the various groups on their success in science curricula; and second,

the relevance of various well-known intervention strategies to the problems of minority attrition in

science in highly selective institutions.)

The question of why much larger proportions of non-Asian minorities leave the science

pipeline than do whites or Asians has long concerned all persons and organizations

interested in the vitality of science and in equality of opportunity to become a scientist.

Science is a rewarding career for those inclined to pursue it, and many of the world's serious

problems cannot be solved without science and technology. If large pools of potential

scientists are being shut out by action of educational institutions themselves, that fact needs

to be known, and the problem needs to be described and examined, so that effective ameliorative policies might be devised.

Our first reports (Strenta et al., 1993, 1994) concerned general issues about choice of,

persistence in, and attrition from science, along with the way gender affected those issues in

our population. Here we will examine these questions with respect to ethnicity.i

Our

strategy and goal is as it was with gender: to describe and analyze the predictors of initial

interest in science, and then the predictors of persistence in science—that is, actually

majoring in science—in terms of variables measuring intellectual achievement and

developed ability.

The situation with respect to minorities differs from that for women very likely in several

ways, but surely in one important respect: minorities are at least as interested in pursuing

science as whites (Astin and Astin, 1993; National Science Board, 1993; White, 1992), and

the attitude toward science, at least for African-Americans, is very positive—more positive,

44 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
other things being equal, than that of whites (Dunteman, Wisenbaker, and Taylor, 1979; see

also citations in Oakes, 1990). In large unselected samples of college-bound students, just

about a fifth of the whites, blacks, and Hispanics taking the SAT or filling out a student

information form in their first college term intended to major in science or engineering

(College Board, 1988a, or any recent year; National Science Board, 1993), with whites

being slightly lower in rate of interest than blacks or Hispanics; over a third of Asians

intended to major in science. In the somewhat more selective longitudinal sample reported

by Astin and Astin (1993), the rates of initial interest were higher but in similar ethnic

order: Asians, 53%; whites, 27%; Hispanics (Chicanos), 36%; and blacks, 34%.

Recent accounts (Oakes, 1990; Suter, 1993; White, 1992) of race, ethnicity, and science

make it clear that non-Asian minorities are relatively low on most measures of preparation

and developed ability, and that these deficits begin early in their schooling careers. They

are considerable just before the point of entrance to college. Both the average SAT

mathematics (SATM) scores and the math and science proficiencies of twelfth-grade blacks

are about a standard deviation (S.D.) behind, and those of Hispanics are about .75 S.D.

behind, those of whites (Suter, 1993). Thus, black grade 12 achievement in math is about the

same as, and in science a little worse than, white grade 8 achievement. And while blacks

and Hispanics are a little closer to whites on scores on College Board Achievement Tests

and Advanced Placement (AP) tests, that is in part because very small and selected

proportions of those minority groups take such tests (White, 1992).

Partly for these reasons, not many minority students actually enter science in higher

education, and many who do drop out along the way. White (1992) and the National

Science Board (1993) have reported that blacks received about 5.3% of the bachelor's

degrees in science in 1989 and 1991, though they constituted about 13% of the population and

about 9% of the higher education enrollment; Hispanics, who were about 7% of the general

population, and 5% of the higher education enrollment, had 4% of the science degrees.

Asians (9%) and whites (82%) together had 91% of the science baccalaureates given in

1991, with Asians obviously greatly overrepresented.

The recent study by Astin and Astin (1993) illustrates the disproportionately large losses of

blacks and Hispanics (in their case, Chicanos). The final pool of blacks in science was only

47% of the size of the pool of those initially intending to major in science, and of Hispanics

only 37%, whereas the corresponding percentages for Asians and whites were 68% and 61%,

respectively (all these figures are overestimates of persistence rates, because there was some

recruitment from nonscience pools into science). This result occurred even though in the

original pools of those initially interested in science and engineering as freshmen, as shown

above, blacks and Hispanics had just over a third of their numbers declaring initial interest in

science majors and were 7-8% more likely to do so than whites. Other large and possibly

more representative samples (National Science Foundation, 1990) have found persistence

rates of only 21% for minorities, compared with 43% for majority students. And Hilton,

Hsia, Solorzano, and Benton (1989) reported persistence rates for the high school and beyond

database (high school seniors who had intended to go to college and major in science or

engineering and who were in college still doing or intending to do science 2 years after

graduation) as 54% for Asians, 44% for whites, 36% for blacks, and 29% for Latinos;

considering only those students who had actually gotten to college and remained there, the

Statements 45
corresponding rates were 61%, 58%, 54%, and 48%. Finally, in Phillips's recent report (1991)

of a large representative sample of engineering students from predominantly white schools,

the 5-year graduation rates were as follows: for whites, 67%; for Hispanics, 47%; and for

blacks, 36%.

Rates of persistence depend on its definition—they are lower measured in the senior than

in the sophomore year of college, and lower in less selective pools—but it appears that of

students who actually begin their first year in college and intend a science major, Asians

will have the highest proportion, they will be best prepared (White, 1992), and they will

persist most strongly; whites will have the lowest proportion of students interested in

science, but those will be well prepared and about as highly persistent; blacks will be

strongly represented in initial interest, but they will be the least well prepared and over half

will leave science; and Hispanicsii will be represented as much as, and a little better prepared

than, blacks, but slightly more likely to drop out.

There is some evidence, however, indicating very substantial persistence rates among

non-Asian minority students. Hilton et al. (1989), studying gifted (i.e., SATM scores of 550

or more) students interested in science, found that the persistence of non-Asian minority

students in math and science fields in (usually) the spring of their second year beyond high

school was higher than that of matched whites (61% vs. 55%). Because the black and Hispanic

samples of this study were, like our own, highly selected, we will have more to say about

them below; but the study certainly supports the view that equally developed ability among

students interested in science predicts equal persistence, regardless of ethnic or racial

affiliation. Finally, historically black colleges and universities (HBCUs) have a strong record

of B.S. (and, later, science Ph.D.) production, more so than more elite, predominantly

white institutions (Culotta, 1992; Thurgood and Clarke, 1995), despite student bodies that

are on average much less well prepared than black students in elite institutions.

This last fact makes clear that persistence is not just a matter of average preparation, but of

competitive position as well: a reasonably well-prepared student at an HBCU who would be

in a strong competitive position in his or her institution would be in a far less strong one at an

elite institution. The context for judging equality of developed ability is at least as salient

within institutions as between them. At white-majority institutions non-Asian minorities are,

by virtue of race-preferential admission policies, at an often serious disadvantage with

respect to validly predictive indices of talent, and if equally developed ability predicts equal

persistence, unequally developed ability should predict differential persistence. For example,

Ramist, Lewis, and McCamley-Jenkins (1994) have shown that for thousands of students in

various racial and ethnic categories, from dozens of predominantly white institutions of

higher learning, blacks averaged nearly 100 points and Hispanics nearly 50 points lower

than whites in SATM, a strong predictor of science and math performance (Astin and

Astin, 1993; Ramist, Lewis, and McCamley-Jenkins, 1994; Strenta et al., 1993), and the

differences were larger for more selective schools. Since the standard deviation of SATM

within their institutions was 85 to 90 points (and less than that in highly selective

institutions), these are substantial differences.

46 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Not only SATM but other preadmission indicators (SATV, high school grades,

achievement tests) are significant predictors of success in science courses. Basic science

courses are difficult, fast-paced, impersonal, and competitive (Hewitt and Seymour, 1991;

Manis et al., 1989; Tobias, 1990), and the more selective the school, the more this is likely to

be the case. Science is also hierarchical, so that relative failure at the basic levels is not only

discouraging but to some extent incapacitating for the next courses. We would expect, for the

foregoing reasons, that the relative deficit in preparation and ability-achievement measures

of the black and Hispanic students who go to very selective and predominantly white schools

will be especially damaging to their prospects in science. There have been dozens of studies

showing associations between ethnic differences in SAT scores and corresponding

differences in college grades. We know of none, however, in which both the high school

and college grades of different ethnic groups have been separated into science and nonscience

categories for differential prediction of science-relevant outcomes. Such a level of analysis is

important, we think, to a more complete understanding of differential persistence in science.

It is sometimes alleged that predominantly white institutions are difficult for blacks and

Hispanics to deal with for reasons that go beyond achievement and ability. In a recent

special report on minorities in science (Gibbons, 1992, p. 1194), Treisman is quoted as

follows: "There is a belief that [minority] kids that are strong will make it anyway. In fact,

national data show that's false. If you control for socio-economic background and class

rank in high school, black kids still do less well than nonminorities. These [lower

performances] are measures of institutional inhospitality." The controls Treisman mentions,

however, do not control for SAT total scores: matching on parental income or education

preserves from 75% to 90% of the mean black-white population difference of about 200

points on SAT (e.g., College Board, 1988a). High school grades are moderately correlated with

SAT scores (about r = .55 in the whole population, and less in selective schools; see Ramist,

1984; Ramist et al., 1994; Strenta et al., 1993). However, SAT scores contribute more to the

prediction of individual course grades, especially at selective colleges, than do high school

grades (Ramist et al., 1994). In the Ramist et al. sample, blacks were only .36 S.D. lower than

whites in high school grades, and Hispanics were actually slightly higher than whites, which

means that with respect to freshman grade-point average, on which those groups were .7 and .4

S.D.s lower than whites, both groups were greatly overpredicted by high school grades. (They

were overpredicted by the SAT as well, but only by about half as much.)

A test of whether there is an "inhospitality" effect or any other ethnic effect is to use a

regression analysis of persistence with ethnicity as a predictor, along with high school grades

and test scores—if there is no ethnicity effect, there is nothing to explain in terms that go

beyond the preadmission measures. Both Hilton et al. (1989) and Astin and Astin (1993)

have done such analyses, with no reported ethnic effects, but their students were attending

an enormous number and variety of institutions. We wished to study institutions that were

very much alike in being high in selectivity and high in the production of scientists and

science practitioners. We have chosen for study four Ivy League schools that are so similar

in admission practices and academic standards that they may be treated, as we do here, as

one superinstitution with four campuses.

Statements 47
The group of students we are investigating here, especially those initially interested in

science, is obviously representative of students in highly selective private research

universities, of which the present four are a part. These four alone are collectively an

important producer of scientists, even though the 1,625 science majors in this group represent

only I% of the total science B.A. degrees given by U.S. institutions (National Science Board,

1993: about 165,000 degrees in natural sciences, math and computer science, and

engineering were conferred in 1991, or about a sixth of all baccalaureates). But however

highly selected these students are, and however elite their institutions, we think that they are

not very different from natural science and engineering majors at other selective colleges or

public research universities. There are some 30 private universities and technical schools

with average SAT totals of about 1,200 or more, and about 25 smaller colleges that are

similarly selective. We believe that 8-9% of the total science degrees is a reasonable

estimate of their production.

There are at least 15 great public research universities, where the culture, curricula, and

standards of high-level science are similar to those that prevail in the ones we are

investigating here. Though they are less selective overall than the highly selective private

universities, they are closer to them in science than in other areas, because the degree of

selection for developed ability in the science departments of selective public research

universities is severe: smaller proportions of students enter such institutions initially interested in

science, and persistence rates are lower (see the review in Strenta et al., 1993). But the select

few who remain include many very talented students. Thus, for example, Humphreys and

Freeland (1992) have shown that the SAT scores for four successive groups entering the UC

Berkeley School of Engineering are very close to the average for the engineering schools

or departments of the group of schools we are studying (Strenta et al., 1994). These public

universities are huge by private standards, a fact that offsets to some extent the smaller

proportions of science concentrators in them. We assume that they give at least another 10-

12% of the total of science degrees. Finally, we assume that these degrees represent the

best of science education of students in the high end of the ability range, so that the roughly

20% under discussion will constitute a far larger percentage of postbaccalaureate science,

engineering, and medical students.

In short, though our argument rests heavily on plausibility grounds, we would not expect

the major factors affecting choice of and persistence in science to be very different at such

public research universities as Washington, Michigan, Berkeley, Illinois, San Diego, Texas,

UCLA, Wisconsin, Virginia, or North Carolina than they are at Rice, Stanford, Notre Dame,

Duke, Chicago, Northwestern, Tufts, Georgetown, Carnegie-Mellon, Washington University,

or Johns Hopkins. Chipman and Thomas (1987, p. 425), noting that high-ability students

were not much studied, went on: "Yet they are the population of real interest with respect to

participation in mathematics and science. It would be particularly important to study minority

students of high ability." That is what we do here.

METHOD

Subjects

In 1988 an average of about 13,000 students applied to each of the four highly selective

institutions whose data are combined here for analysis. These institutions accepted between a

48 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
fifth to a quarter of them, and matriculated about half of those. The population of students

under investigation was thus highly selected by the institutions, and also highly selfselected in applying.

With respect to the four ethnic groups targeted here for study, an average of 8,250 whites,

averaging a total SAT of 1,268, applied to each institution; 22% were selected, yielding a

group of white matriculants with an average SAT of 1,325. Similarly, an average of 735 black

students applied to each institution, averaging a SAT score of 1,089; 35% of them were

selected, with a resulting group of matriculants having an average SAT of 1,160. Of the

1,620 Asian applicants per institution, with an average SAT of 1281, 23% were selected,

producing a matriculant group averaging 1,345; and of the 490 Hispanic applicants per

institution (SAT = 1,152), 29% were selected, resulting in a matriculant group with a 1,219

average SAT. The matriculant groups averaged 410 points above their respective population

1987-88 SAT means, ranging from 390 for whites to 425 for blacks.

Measures

The basic data came from high school transcripts, admissions office data, and college

transcripts through June 1992. We employed the following pre-matriculation measures in

many of our analyses: SAT verbal score and SAT math score (SATV and SATM); the

average of the best three achievement tests (ACH); the number of high school science and

mathematics courses (NSCI); average grade earned in these courses (HSSCI); average grade

in high school nonscience courses (HSNON); stated initial interest (INT) in a major (the first

stated if more than one), coded 0 for nonscience and 1 for science, where science is

defined as natural science and engineering. Students who were undecided or wrote nothing

were classified as nonscience. Other prematriculation measures occasionally employed were

the standard measures used by admission departments: the high school percentile rank in

class converted to a normal deviate with mean 500 and standard deviation 100 (CRS, or

converted rank score), and the Academic Index (AI), which is one-tenth the sum of (a) the

average of the two SAT scores (e.g., 670), (b) the ACH (e.g., 680), and (c) the CRS (e.g.,

690 for someone who was third in a class of 100); in the examples, the AI would be 204.

Finally, we coded participation and performance in high school science courses.

College performance measures included the grade-point average for science and mathematics

courses taken during the first 2 years (SGPA), the counterpart measure for nonscience courses

(NGPA), and the broad area of actual concentration (MAJ, coded, like INT, as 0 or 1 for

nonscience and science, respectively). Other measures occasionally used were the yearly

and cumulative GPAs.

We were conservative in what we classified as science, not including history of science,

cognitive science, psychology, environmental science, science and ethics, biology and

society, or other interdisciplinary concentrations, which were placed into social science

(usually) or humanities as seemed most appropriate. We were interested in analyzing

science concentrations like those that are traditionally part of natural science divisions:

hierarchical, laboratory-based disciplines with several prerequisites, usually including many

mathematics courses, and usually with heavy workloads and frequent assignments.

Statements 49
RESULTS AND DISCUSSION

Preparation

The top panel of Table 1 shows the percentage of each group that took the indicated

Advanced Preparation (AP) science course, and the average group grade for each course.

The most frequently recorded course was AP Biology, closely followed by AP Chemistry;

AP Physics and AP Calculus BC were substantially less often chosen. With but three

exceptions for grades and one for percent participation, the order of grades and participation

was Asian, white, Hispanic, and black. Regardless of these differences, the overall participation

in advanced high school science courses was well above the national average (College

Board, 1988b). Group differences on these variables, as on those of the lower panel, were

highly significant, which simply means that much of the effect of ethnicity occurred prior to

college matriculation. We take such differences into account in examining whether there

were further ethnic effects during college.

The bottom panel of Table 1 shows the values of the preadmission variables used in various

analyses. Most of the preadmission data are standard, but we have included as a variable

the number of science and math courses (NSCI), and disaggregated the overall high school

GPA into science (HSSCI) and non-science (HSNON) components. The standard predictors,

SATM, SATV, and Achievement Test average (ACH), are shown in rows 4-6; as noted,

these, along with high school record, make up the Academic Index (Al—shown in row 7),

which is the chief predictor of grades used by the admission departments of these schools.

In this population, AI correlated r = .50 with first-year GPA, and .45 and .46, respectively,

with NGPA (the average grade in courses outside the science division in the first 2 years) and

SGPA (the average grade in science division courses in the first 2 years). The eighth row

indicates the percentage of each group that expressed an intention to major in science or

engineering.

These credentials shown in the bottom panel are the ones that admissions officers look at,

and they manifested extensive course work in science and math, very good high school

grades, and high scores on standardized tests. As the introduction and the AP science course

data suggest, the Asian students showed the greatest preparation and the most highly

developed ability, especially with respect to science-related scores, averaging just over a

third of an S.D. above the general average on those. Asians and whites together constituted

about 77% of the students who were initially interested (and 82% of the students who

finally majored) in science, with blacks and Hispanics together making up about 11% of

those interested (and 7% of those who finally majored) in science. (The remainder was made

up predominantly of foreign students, many of them Asian, and students of unknown

ethnicity, many of them white.) From the point of view of the non-Asian minorities, then,

50 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
AP Courses % GPA % GPA % GPA % GPA GPA SD

Biology 33.2 3.71 22.5 3.64 21.5 3.44 26.4 3.52 3.63 0.47Chemistry 33.4 3.65 20.0 3.70 17.0 3.55 14.7 3.19 3.65 0.52Physics 23.6 3.52 17.7 3.61 12.5 3.43 5.2 3.29 3.56 0.58Calc (BC) 22.4 3.62 14.3 3.50 5.0 3.30 4.3 3.19 3.51 0.57Variables M S.D. M S.D. M S.D. M S.D. M S.D.NSCI 9.91 1.33 9.29 1.39 9.25 1.37 8.94 1.37 9.34 1.40HSSCI 3.75 0.31 3.62 0.38 3.52 0.44 3.33 0.46 3.61 0.39HSNON 3.75 0.51 3.67 0.52 3.59 0.62 3.44 0.59 3.66 0.54SATM 712. 54 692 62 641 73 597 73 685 68SATV 633 79 633 70 578 81 563 75 625 75ACH 680 57 663 62 628 70 577 64 657 67AI 208.4 11.8 204.6 13.2 193.7 14.0 183.6 14.2 203.1 14.5& Interest in Science 43.4Note: Panel A includes the percent of students in each ethnic group taking indicated high school AP courses and their meangrade point average. In Panel B, NSCI is the mean number (M) and standard deviation (S.D.) of all math and sciencecourses taken in high school; HSSCI is the high school science GPA; HSNON is the nonscience GPA; SATM and SATV arethe math and science portions of the SAT; ACH is the mean of the highest three Achievement Tests; AI is the AcademicIndex; and % Interest is the percentage of each group expressing an intention to major in science or engineering. Meantotals are weighed. Ns listed are maxima; some data are missing in every cell.

B: Admission Data

55.0 41.4 44.0 44.2

N = 216

N = 355

N = 4687

Asian White Hispanic Black

TABLE 1. Preadmission Data by Ethnic Group

A: Advanced Placement Science Courses: Percent Participation and Grades

Asian White Hispanic Black M Total

M Total

N = 582

N = 3534

Statements 51
their colleagues and competitors in science classes were overwhelmingly whites and Asians,

and we take the combined white-Asian mean as the reference for non-Asian minority disadvantage in preadmission and college performance variables.

For blacks, that disadvantage was a third of an S.D. in number of high school science courses

taken (NSCI), and four-fifths of an S.D. in high school science grades (HSSCI). On SATM,

ACH, and AI, blacks were 1.3 to 1.5 S.D.s behind. The relative disadvantage for Hispanics

was about half that for blacks on the most science-relevant variables—HSSCI, SATM,

ACH, and Al. Note, as Ramist et al. (1994) showed (particularly at selective colleges of

the sort under study here), that high school grades evinced far smaller disadvantage for

blacks and, especially, for Hispanics, than SAT scores. Note also that nearly all of these

minority disadvantages would be larger if measured against the Asian-white standard

deviation.

Apart from the Asians, these differences in preparation and developed ability for science did

not affect the proportion of each group having an initial intent to major in science (row 8 of

the lower panel of Table 1), with blacks and Hispanics having been a little more interested

initially than whites, despite relative deficits in high school preparation, performance, and test

scores. Such a result implies an ethnic effect of the sort suggested in the literature: blacks,

especially, aspire to be in science, all other measures held equal (Dunteman, Wisenbaker,

and Taylor, 1979; Oakes, 1990). This implied finding is important, because intention to

concentrate in science is by far the strongest predictor of actually doing so (in our group

overall, the phi correlation was .55).

The implication of an ethnic effect was tested by analyzing the residuals from the multiple

regression equation predicting initial interest (Science = 1; Nonscience = 0). In the

predictive equation, all the preadmission variables were highly significant (p < .0001),

with R2 = .20; number of high school courses in math and science (NSCI), the average

grade in them (HSSCI), and SATV were by far the most powerful predictors, the last one

being negative. High school nonscience grades (HSNON), SATM, and ACH were weaker

predictors, with the first being negative. Analysis of variance of the residual scores by ethnic

group yielded a significant ethnic effect (F(3, 3662) = 5.05, p < .002). Blacks were more

likely than predicted to express an intention to major in science (mean residual, .10), and,

by Bonferroni t-tests, were more likely than the other groups (whose mean residuals were

.00, .00, and — .01 for Asians, Hispanics, and whites, respectively) to do so.iii The

interactions of ethnicity with the preadmission variables were separately assessed by the

tests for covariate-by-treatment interactions outlined by Stevens (1992, pp. 344-355). No

single covariate-by-treatment interaction was significant, nor was the lumped covariate-bytreatment interaction.

It does appear, once more, that blacks would be very well represented in science if intention

to be a scientist were the decisive controlling variable. The present data on rates of initial

interest in natural science and engineering agree with data cited in the introduction: Asians

and whites are high and low in interest, with blacks and Hispanics close together in the

middle.

52 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Table 2. Preadmission and College Performance Variables by Ethnic Group and Initial Interest

Variables M S.D. M S.D. M S.D. M S.D. M S.D.NNSCI 10.24 1.26 9.89 1.20 9.58 1.33 9.47 1.22 9.90 1.23HSSCI 3.80 0.25 3.75 0.29 3.62 0.37 3.44 0.31 3.73 0.31HSNON 3.74 0.51 3.67 0.54 3.51 0.62 3.46 0.55 3.66 0.55SATM 721 52 714 52 653 74 607 72 704 63SATV 621 81 627 68 563 84 541 78 617 76ACH 685 58 677 58 630 78 573 66 669 66AI 208.6 12.0 206.9 12.1 193.2 15.4 182.4 15.0 204.9 14.2SGPA 2.94 0.64 2.99 0.70 2.46 0.68 2.21 0.71 2.89 0.72NGPA 3.23 0.48 3.23 0.52 2.97 0.63 2.85 0.58 3.19 0.54% Sci. Major 70.0 60.6 55.8 33.8 60.00& Terminated 4.0 4.1 10.5 14.6 5.2NNSCI 9.50 1.30 8.85 1.35 8.98 1.35 8.53 1.34 8.90 1.36HSSCI 3.68 0.35 3.53 0.41 3.44 0.47 3.24 0.49 3.52 0.43HSNON 3.76 0.52 3.68 0.52 3.65 0.61 3.42 0.56 3.67 0.53SATM 701 54 677 63 632 71 589 74 670 69SATV 648 74 637 71 590 76 579 69 632 74ACH 673 55 653 63 626 63 580 62 648 66AI 208.1 11.5 202.9 13.7 194.1 13.0 184.5 13.6 201.6 14.5SGPA 3.08 0.75 3.02 0.82 2.73 0.92 2.22 0.96 2.96 0.85NGPA 3.32 0.39 3.25 0.49 3.08 0.54 2.80 0.55 3.22 0.51% Sci. Major 14.9 8.6 5.8 2.5 8.6& Terminated 4.6 4.7 10.7 11.1 5.5

A: Initial Interest in Science

320 1462 95 157 2034

Asian White Hispanic Black

Note : For both Panels, N = sample size. Total sizes exclude unknown ethnicity and foreign students. NSCI is themean number (M) and standard deviation (S.D.) of all math and science courses taken in high school; HSSCI is thehigh school science GPA; HSNO is the nonscience GPA; SATM and SATV are the math and science portions of theSAT; ACH is the mean of the highest three Achievement Tests; AI is the Academic Index; SGPA is the grade pointaverage for science courses in the first two undergraduate years; NGPA is the average for nonscience courses in thefirst two years; % Sci Major is the percentage of each group who majored in science or engineering; and %Terminated is the percentage of each group no longer matriculated in the 1991-92 year (i.e., students who left or werese

parated).

Total

B: Initial Interest Not in Science

262 2070 121 198 2653

Statements 53
Performance

Table 2 shows data for the same variables shown in the lower panel of Table 1, now

subdivided by initial interest in either science or nonscience majors, and it adds data on

college performance variables of interest. These are grades in the first two undergraduate

years in science courses (SGPA), courses not in science (NGPA), and the percentages of

each group who finally majored in science. The chief differences between the two major

interest groups were, understandably, on three variables very strongly predictive of interest

in science—number of and grades in high school science courses (NSCI and HSSCI),

and SATM, where the differences exceeded a half standard deviation—and on ACH, where

the difference amounted to a third of an S.D. Because grades in nonscience high school

courses were nearly the same in each major group, and SATV scores only moderately favored

those not initially interested in science, the students initially interested in science had a

modestly though significantly higher AI, a common result (Green, 1989; White, 1992) with

respect to the relatively high overall quality of academic preparation among science

students.

Despite these differences, science grades in the first two college years were slightly greater

for the group not initially interested in science than for the group that was. We analyzed

this anomaly in the earlier paper (Strenta et al., 1994): science departments offer fairly easy

courses for nonscientists and do not grade them as rigorously as courses that are part of

their majors. Here, however, we are primarily concerned with ethnic differences, in particular

differences in persistence among the students who came to their colleges intending to

concentrate in science. Some can be accounted for by differences in preadmission measures

of preparation and developed ability; whatever cannot be so accounted for may be fairly

attributable to ethnicity or to variables associated with it.

Of the students initially interested in science, the relative position of blacks and Hispanics

on science-relevant variables was worse than it was among all students (as was shown in

Table 1), another example of the rule that the more rigorous the selection from groups differing

at the mean, the greater the relative disadvantage of the groups with the lower means. The

deficits were particularly large on the Academic Index (Al), about 1.7 and 1 S.D., respectively,

below the average of similarly interested white and Asian students. There were somewhat

smaller but still substantial deficits in high school science grades (HSSCI of about 1.0 and

0.5 S.D.s, respectively) and ACH (about 1.6 and 0.7 S.D.$), so that the deficits in the

Academic Index were about the same as in SATM (in these comparisons we have used as

divisors for units of effect size the S.D.s for the students interested in science, since they are the

ones populating the serious introductory science classes—if the white-Asian S.D.s are used, the

differences grow by 15% to 20%).

Persistence

The expected consequences of these differences on science-relevant variables are differences

in persistence, the proportion of students initially interested in science who actually majored

in science, shown in the next-to-last row of the top panel of Table 2. Such persistence varied

predictably: the rate for Asians, at 70%, was twice that for blacks (34%); and rates for

whites (61%) and Hispanics (55%) were intermediate. The differences shown in percent who

majored in science were highly significant (x2 = 58.99, df = 3, p < .0001), as were the ethnic

54 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
differences, in the same order as just given, in rate of recruiting to science majors (next to

last row of the lower panel) from those students who had not expressed an initial intent to

major in it (x2 = 23.37, df = 3, p < .001). The high rates for Asians and whites resemble

those given in the High School and Beyond (in Hilton et al., 1989) and the Astin and Astin

(1993) data discussed in the introduction.

The most serious form of nonpersistence, leaving school altogether, manifested similar

differences (final row of each panel). For students initially interested in science, the ethnic

termination rates were significantly different (x2 = 37.91, df = 3, p < .001), as were the

differences among the highly similar termination rates among those students not initially

interested in science (x2 = 21.40, df = 3, p < .001). By national standards, of course, the

termination rates shown in Table 2 are very low loss rates.

Hispanics appear to have persisted more, and blacks less, than preadmission variables might

have indicated. The R2 for the regression of persistence on preadmission variables was .10,

with the strongest predictors being number of, and grades in, high school science courses

(NSCI and HSSCI), ACH, and (negatively) SATV (all p < .0001). We again analyzed the

residuals from this regression by ethnic group. The F-ratio (2.54, df = 3, 1631, p < .06) was

nonsignificant. Blacks averaged a residual score of — .08 (they persisted less than

predicted); Hispanics averaged .09 (they persisted more than predicted); whites (— .01) and

Asians (.04) averaged closer to prediction.iv The interactions of preadmission variables with

ethnicity were again assessed for covariate-by-ethnicity interactions (Stevens, 1992), which

were again nonsignificant.

The marginal ethnic effect of the main analysis perhaps warrants some speculation. The

decrement for blacks may be to some degree the complement of the "excess" initial interest

beyond what preparation and developed abilities would have predicted. The Hispanic

increment over the predicted rate may have to do with the uncommonly large proportion,

over 50%, of their science-interested group who wanted to go into engineering, the science

area where persistence is highest. These speculations notwithstanding, however, the main

result of this analysis of ethnic group residuals is not significant: preadmission variables

accounted for a significant fraction of the variance of persistence decisions and ethnicity

did not. This lack of ethnic effects on persistence echoes similar noneffects in the Hilton et

al. (1989) and Astin and Astin (1993) regression analyses.

Overview

For our subjects, the combined effects of persistence, recruiting, and termination left 45.2%

of the entire incoming group of Asians, 30.1% of whites, 27.8% of Hispanics, and 16.6% of

blacks still majoring in science after 4 years. By comparison, a recent NSF report (National

Science Board, 1993) gives corresponding percentages of all science degrees (among all

bachelor's degrees given in 1991) as 33.1% for Asians, 14.0% for whites, 10.3% for

Hispanics, and 12.4% for blacks. Astin and Astin (1993) reported corresponding figures of

35.9%, 16.6%, 13.1%, and 16.1%. The Asians, whites, and Hispanics in our selective sample

did much better, but the blacks, though also highly selected, did not.

Statements 55
Figure 1 shows the conventional grade-point averages (GPAs) of the different ethnic groups,

for each year and by kind of major: science in panel A and nonscience in panel B. As is

typical, grades in humanities and social sciences were generally higher than those in science,

even though the average Academic Index (AI) in the nonscience majors was significantly

lower, by 0.4 S.D., than that in science. Grades in nonscience majors rose more steeply from

the first to the final year; indeed, grades of science majors did not on average rise at all in

the second year, and for minority groups they fell. The ordering of the ethnic groups was the

same, regardless of year or category of major.

We used these data to test a common hypothesis, the "late bloomer" hypothesis: that is, that

non-Asian minority groups will close the initial gap with whites and Asians after they

have made their adjustments to a putatively strange, unsettling, elite, largely white

collegiate world. The dependent measure was the difference between first- and fourth-year

GPA, by group and category of final major. The effect of major category was very large

(FBI, 4186) = 64.5, p < .0001), the effect of ethnic group nonexistent (F < 1), and the

interaction of ethnicity and major category marginal (F(3, 4186) = 2.37, p < .07). This last

result arose from the very small net upward shift over years for blacks who majored in

science, and it may have something to do with the fact that their average science grade in

the first 2 years (SGPA = 2.40) was 1.3 S.D.s lower than the average SGPA of white and

Asian science majors (3.16), a very difficult competitive position. But the chief result here

was one found in every longitudinal test of the "late bloomer" hypothesis we know of

(Elliott and Strenta, 1988; Wilson, 1980, 1981): non-Asian minorities do not catch up with

whites and Asians over time. Astin and Astin (1993) reported, in fact, that the AfricanAmericans in their longitudinal sample had lost relative ground on quantitative tests (e.g.,

from SATM to GREQ) over 4 years, probably because they were less likely to have studied

in quantitative areas.

56 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Many discussions of choice of, and persistence in, science do not employ many of the

variables used here—achievement test scores and scores derived from high school

transcripts—because they are unavailable or difficult to get. But many investigators do have

SAT scores for analysis. We therefore present a more detailed analysis of the SATM

scores—their relation to various choices and their distribution—to facilitate comparisons

with other work. Figure 2 illustrates the general relation between SATM scores and the rate,

at any score level, of majoring in science in this sample. For scores below 640 the rate was

low and moderately rising. Above 640, there was a steep increase in rate with score level

until at the top two score levels over half the students majored in science. Indeed, 89% of all

science majors had SATM scores of 650 or more, and 70% had scores at or above 700. The

implications of these figures for the representation in science majors of Hispanics and

blacks, of whom only 53% and 25%, respectively, had scores of 650 or more, are negative.

Statements 57
The leftmost panel of Table 3 shows the SATM score distribution for each ethnic group, as

proportions of each group falling within three broad score categories: <550, 550-640, and

650-800. The middle and rightmost panels show the proportions within each score category

who were interested in or who majored in science, respectively. The rightmost panel shows

that, given a score of 650 or better, the Asians were more likely than all others to major in

sciencev (x2 = 32.2, df = 3; p < .001); the proportions for the other groups were not

different. Given a middling score of 550-640, both Asians and Hispanics were relatively

more likely to major in science (x2 = 25.3, df = 3, p < .001) than blacks and whites, and

Group <550 550-640 >640 <550 550-640 >640 <550 550-640 >640

ASIAN ____ a 10.0 89.1 ____ a 36.8 57.3 ____ a 26.3 47.6

WHITE 2.1 18.8 79.1 11.3 22.3 47.4 5.6 13.0 35.4

HISP. 10.0 37.0 53.1 23.8 46.2 46.4 4.8 32.1 29.5

BLACK 23.8 51.0 25.2 33.3 46.6 48.8 7.4 13.2 30.2

TOTAL 3.9 21.0 75.1 24.2 29.6 48.9 6.7 15.4 36.9

a

Cell size <10.

TABLE 3. Distribution of SATM Scores and Science Choice by Ethnic Group

Of All Students Interested in Science Who Majored in Science

Percent in Each Score Category

within each of those pairs there was no difference. Particularly noteworthy is the fact that,

score level for score level, roughly the same proportions of blacks as whites majored in

science, and at the highest level where the vast majority of the majors came from, Hispanics

were also the same as blacks and whites.

These data may assist us in dealing with the most obvious disparity in results concerning

persistence in science among talented non-Asian minority students. We refer to the results of

Hilton et al. (1989) on students who aspired to major in science or engineering and had

SATM scores of 550 or better. Our persistence rates of 70% for Asians, 61% for whites,

and 55% for Hispanics are similar to the corresponding rates of 70%, 55%, and about 60%

for the groups of students studied by Hilton et al., but their rate for persistence by blacks was

nearly double ours, 62% vs. 34%. Can this disparity be reconciled?

Whether it can be completely or not, we think the size of the discrepancy is more apparent

than real, for several reasons.

First, to mention probably the smallest contribution to it: over half the non-Asian minority

subjects in Hilton et al. (1989) were prospective engineers (compared with 42% of our black

and Hispanic science intenders), and engineering is the field of highest persistence. Second,

their subjects were selected from SAT takers who had SATM scores of 550 or higher in

1984-85, intended to major in science or engineering, and were later asked, in February

1987, what they were doing. Of the half who responded to the questionnaire, 61% were in

a 2-year or 4-year college or university and either majoring or intending to major in science

or engineering: i.e., they were persisters. But a few of those persisters had less than a year of

higher education, and virtually none would have completed more than three semesters.

Persistence in sciences, especially outside of engineering, can by no means be assumed at

58 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
that point in a career-there is a substantial outflow from the science pipeline after the

second year (NSF, 1990; Massey, 1992). In a large-scale study of persistence in

engineering, for example, a third of black and a fifth of Hispanic attrition occurred after

four semesters (Phillips, 1991).Thus, the 61% overall figure would probably have diminished

in the next 2 to 3 years by some nontrivial amount.

Third, and most challenging, Hilton et al. (1989) give the figures for black persisters in six

Ivy League schools, including three of those studied here, and they show 58% persistence,

well above our 34%. Perhaps the postsophomore attrition just mentioned would bring the

figures together, but so might other influences. The 93 black students in those institutions in

the Hilton et al. sample were, we estimate, about a third of all the black students on those

campuses interested in science, and they may well have been among the best ones, both

because none were below 550 in SATM, and because, within the study sample, self- and

institutional selection may have worked to that end. In our sample, nearly a quarter of the

black students had SATM scores below 550, and while a third of that group was initially

interested in science, only a fifth persisted. At the other end, the persistence rates of blacks

in our sample with SATM scores of 650 or more was 59%, about the same as the figure of

61% for whites.

Finally, Phillips (1991), reporting on engineering students who began higher education, as most

of Hilton et al. (1989) students did, in 1985, and who also had SATM scores of 550 or more,

gave graduation rates as of 1990 as 62% for blacks, 58% for Hispanics, and 83% for

nonminority students (these high rates for all groups presumably result from engineering

being the science under investigation). Here, in very large samples going well past the third

semester, the majority-minority persistence difference reasserts itself, even in talented groups.

Whites and Asians in such selected groups will still have higher means on SAT scores and

high school grades, as they did in the Hilton et al. samples, and can be expected therefore to

persist more.

We believe, in short, that the Hilton et al. (1989) results are unusual: the facts that their

sample was truncated at the low end, and that their students attended a wide range of

institutions and were very early in their college careers when they responded, complicate

the comparison with other results, including our own.

GENERAL DISCUSSION

Though non-Asian minority students in this sample had strong interests in pursuing science

as a concentration, their persistence in that choice was below average, by a small amount for

Hispanics and a large one for blacks. It was the preadmission variables describing developed

ability—test scores and science grades—that accounted chiefly both for initial interest and

for persistence in science, though being black clearly added something to initial interest.

These results—the noneffects of ethnicity on persistence—echo those of Hilton et al. (1989)

and Astin and Astin (1993), who in predicting persistence using elaborate regressions with

large data sets found no significant ethnic effects. Even so, the persistence of blacks was in

our case very low.

Statements 59
Why are so many talented minority students, especially blacks, abandoning their initial

interests and dropping from science when they attend highly selective schools? The question

has many possible answers, but we will begin with the factor we think most important, the

relatively low preparation of black aspirants to science in these schools, hence their poor

competitive position in what is a highly competitive course of study. As in most

predominantly white institutions, and especially the more selective of them (Ramist,

Lewis, and McCamley-Jenkins, 1994), whites and Asians were at a large comparative

advantage by every science-relevant measure (see Table 2), and on the composite predictor,

the academic index, they were at a 1.75 S.D. advantage.

That it is the comparative rather than the absolute status of the qualifications is clear from

two strands of evidence. First, students at historically black colleges and universities

(HBCUs) have quite low average SAT scores and high school grades (The College

Handbook, e.g., College Board, 1988c, or any recent edition; Barron's Profiles of American

Colleges, e.g., 1988, or any recent edition), but they produce 40% of black science and

engineering degrees with only 20% of total black undergraduate enrollment (Cullotta,

1992; Phillips, 1991). For example, with SATM scores averaging about 400, half the

students at Xavier University are reported to be majoring in natural science (Cullotta, 1992);

with scores somewhat higher (about 450), Howard University is the top producer of black

undergraduate science and engineering degrees (Suter, 1993; Cullotta, 1992). It may be that

many of these students will not progress to higher degrees in science in the same

proportions that students with an Ivy League science education do; but it is a virtual

certainty that no one goes on in science without either majoring in it or taking a wellprescribed premedical (or predental or preveterinarian) science program. You can't play if you

don't stay, and leaving science or premed for education or history usually means leaving

science or premed forever.

And enough of the graduates of HBCUs do go on in science to establish an interesting and

significant fact: of the top 21 undergraduate producers of black Ph.D.s during the period

1986-1993, 17 were HBCUs and none were among the 30 or so most selective institutions

that so successfully recruit the most talented black secondary school graduates (Thurgood

and Clarke, 1995, Table 5). Cullotta (1992) quoted a biology professor from one of the

HBCUs: "The way we see it, the majority schools are wasting large numbers of good

students. They have black students with admission statistics [that are] very high, tops. But

these students wind up majoring in sociology or recreation or get wiped out altogether." In fact,

at our institutions, non-Asian minority students tend to shift out of science rather than to

drop out altogether.

We think it certain that more of the black students in our sample would have persisted in

science had they been, say, at Howard, but more of them would also have persisted at any of

several majority white institutions as well, and that brings us to the other strand of evidence

for the competition argument. It appears in Table 4, which we calculated from data tapes

kindly supplied to us by Warren Willingham from the data sets on nine private colleges he

studied for his book, Success in College (1985). We have added the data of two others. The

table shows how science degrees are distributed within each institution as a function of

terciles of the SATM distribution; institutions are listed in descending order of average

60 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
SATM score. Thus, in institution A, over 53% of all the science degrees given were earned

by students whose SATM scores were in the top third of its SATM distribution, averaging

753. A similar percentage of all the science degrees given in institution J were earned by

students in the top tercile of their SATM distribution, but the average of that tercile was

much lower, at 591. That figure lies just below the figure for black students in our sample

(Table 1), but it is also just above the score of 581 that characterizes the bottom tercile of

Institution A, where only 15% of the science degrees were awarded.

Institution % Degrees SATM % Degrees SATM % Degrees SATM

Institution A 53.4 753 31.2 674 15.4 581

Institution B 57.3 729 29.8 656 12.9 546

Institution C 45.6 697 34.7 631 19.7 547

Institution D 53.6 697 31.4 626 15.0 534

Institution E 51.0 696 34.7 624 14.4 534

Institution F 57.3 688 24.0 601 18.8 494

Institution G 62.1 678 22.6 583 15.4 485

Institution H 49.0 663 32.4 573 18.6 492

Institution I 51.8 633 27.3 551 20.8 479

Institution J 54.9 591 33.9 514 11.2 431

Institution K 55.0 569 27.1 472 17.8 407

Medians 53.6 31.4 15.4

TABLE 4. Percentage of Earned Degrees in the Natural Sciences as a Function of Terciles of

the SATM Distribution in 11 Institutions

Note: Percentages indicate the proportion of natural science degrees awarded to students as a

function of terciles of the SATM score distribution. SATM numbers are mean scores for each

tercile, which vary depending on the selectivity and general level of developed ability that

characterizes an institution. SATM is the score on the mathematical reasoning section of the

Scholastic Assessment Test.

Tercile 1 Tercile 2 Tercile 3

The table makes clear two things about these and presumably similar schools: first, the

the proportions of science degrees awarded, by terciles of the SATM distribution, are about

54%, 31%, and 15%. Second, the same SATM score may be associated with any of these

terciles, depending on the selectivity and general level of developed ability that may

characterize an institution. Put concretely, a student with an SATM score of 580 who wants

to be in science will be three or four times more likely to persist at institutions J and K,

where he or she is competitive, than at institutions A and B, where he or she is not.

Institutions F—K are only about half as likely to give science degrees—with only about

15% of their degrees in science—as institutions A—E, which average 28% science degrees.

Still, a 54% chance of getting one of the 15% of the degrees that are in science is nearly

twice as good as a 15% chance of getting one of the 28% of degrees that are in science. Our

institutions are collectively like A: 51.6% of the science degrees were given to top tercile

students, 31.5% to middle tercile students, and the rest, 16.9%, to the bottom tercile. The

associated mean SATM scores were, respectively, 753, 695, and 607, the last figure being

exactly the mean score for blacks interested in science in our sample.

The gap in developed ability between the white-Asian majority and non-Asian minorities,

especially blacks, especially in science, results from institutional policies of preferential

admission from pools differing in measures of developed ability and achievement at the

point of entry into higher education, as the Method section (see Subjects) made clear. These

Statements 61
policies subserve the several goals collectively categorized as diversity or affirmative

action goals, and these institutions are firmly committed to these admissions practices. That

being the case, non-Asian minority students initially aspiring to science will continue for

some time to bear a cost in lower grades and in altered academic and vocational goals. It

may well be a cost such students regard as worth bearing in return for benefits in quality of

education, variety of points of view, richness of social experience, prestige of degree, or

enhancement of career prospects. Still, it is a serious cost that should be acknowledged, and

minimized if possible.

There are several methods and combinations of methods that have been proposed to reduce

the gap, and they can be categorized into three general groups: direct inducements to, or

requirements for, greater study, more general support (mentoring, advising, group work and

meetings, internships, and monetary incentives), and the elimination of institutional racism.

It is possible that some features of some of the better-known intervention programs

designed to increase the number of minority scientists are transportable to highly selective

institutions. We discuss three of them briefly.

The Meyerhoff scholars program (Gibbons, 1992; Hrabowski and Maton, 1995; Mercer,

1994) at the University of Maryland, Baltimore County (UMBC), selects some 40 bright

African-American students (who must have a B average and, currently, a minimum SATM

of 600, and whose average SATM is 650) from among some 600 applicants from schools

throughout the state; offers tuition, fees, room and board, and a stipend; requires a 6-week

program of science and math courses in the summer prior to matriculation; requires a B

average to be maintained (this motivational device could not be employed at our schools,

which give only need-based aid); provides a program community, including group meetings

and common housing; encourages group study and the use of tutoring; links the students

with scientists and engineers as mentors; and provides summer internships in various labs.

The program appears to be very successful both in grade performance (no student had gotten

a grade below C) and persistence (only three had left the program, which began in 1989) as of

the June, 1994, report in the Chronicle of Higher Education by Mercer. A recent study of its

first three cohorts (Hrabowski and Maton, 1995) found the Meyerhoff scholars getting freshman

GPAs averaging 3.5, while a historical comparison group of black science students (most of

whom who had entered UMBC between 1980 and 1989), matched on SAT and high school

grades, averaged only 2.8, with the biggest part of the difference coming in science courses,

particularly calculus and chemistry. There are some problems with historical comparisons, as

the authors recognize. Also, Meyerhoff students may get special instruction in calculus and

chemistry in their summer program, and perhaps be graded somewhat less rigorously in

summer.

Still, it is easy to believe that the Meyerhoff scholars are doing well, and it would be easy to

believe that they are doing somewhat better than they would have done without the program

features that exercise and reward the further development of their talent for science. But

UMBC is not an unusually selective institution (the white students there average well below

650 SATM): an SATM average of 650 characterizes African-Americans at such places as

Harvard and MIT, but virtually nowhere else. So the competitive advantage of the Meyerhoffs

62 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
should not be taken lightly as a contributor to their success. The program is selective and

voluntary, which makes control for motivation by random allocation nearly impossible. The

hypothesis that the white-black performance gap, at least in the case of the Meyerhoff

scholars, has been eliminated at UMBC simply by eliminating any gap in entering developed

abilities cannot, therefore, be rejected on any evidence given so far.

One of the public technical schools vying for the enrollment of talented non-Asian minority

students is Georgia Institute of Technology (Georgia Tech), which also has a well-known

program, the Challenge Program, devoted to the recruitment and retention of black and

Hispanic scientists and engineers. In its present form, as described by Smothers (1994), this

voluntary program begins with a 5-week summer program of the study of calculus and

chemistry, with an option to take a credit course in psychology in order to reduce the regular

fall term course load. There are also provisions for mentoring and counseling, and an annual

awards banquet, but before the introduction of the summer program in 1990, these had done

little to improve grades and retention. A report of the program's results (Hume, 1994)

shows that the black participants now get grades that are better than those of their black

nonparticipating compeers, and nearly as good as those of all Tech students (primarily whites,

but including the minority students). Retention rates for classes entering in 1990 and 1991

appear to be higher than those of all Tech students entering in those years. For the Hispanic

students, the Challenge program has made little difference, but their grades and retention

rates appear to equal or surpass the average for the institution anyway. The advantage for the

program participants in GPA is highest in the first term, and drops off to varying degrees

thereafter, a fact that points to the summer session as perhaps the chief contributor to

program success. (The somewhat longer summer session of the Meyerhoff program may have

played a similar role in its effect on freshman grades, cited above. We do not know

whether the advantage conferred by that program, however large it might be, also fades

with time.)

Again, it is difficult to tell how much is contributed by the Challenge Program without

knowing the data on the level of developed ability brought to it by the various groups.

Because participation is voluntary, a random allocation study is unfeasible, so motivation

would remain uncontrolled; but a regression of retention or GPA on preadmission scores

and grades, with program status added as a predictor, might indicate how much might be

due to the program itself. It looks to us as if the largest effect in both of these programs,

Meyerhoff and Challenge, may be on retention. Why might that be?

A relatively ill-prepared student has a higher than average likelihood of getting one or more

shockingly bad grades, perhaps his or her first bad grades, in a rigorous college science

course in the first term. One response is to leave school or leave science. But if the

student has just finished a 5- or 6-week summer course emphasizing the very materials

offered in that first term, or making possible a reduced first term course load, there is less

chance for such failure, and less defection from science. The improvement in grades may

fade—after all, there will be no more preparatory summer programs—but the student will

have gotten over the first and most difficult hurdle. In data cited by Massey (1992), 40% of

black students entering college immediately after high school left in the first year, and the

figure for science aspirants may well have been higher. The summer sessions of these two

Statements 63
programs are ideally suited to provide help when it is most needed. An important feature of

them, emphasized by both sponsoring institutions, is that they demand hard work on collegelevel material.

How might such a program be adapted for our institutions? To require it of non-Asian

minority-aspiring scientists below some level of preparation would be coercive and might

be stigmatizing and unpopular. If the program were voluntary, and were minority only, it

might have some of the effect of the Challenge or Meyerhoff programs, though such

exclusiveness might be neither necessary nor wise. In our sample, the number of students

initially interested in science, and who had SATM scores less than 600, was 139-67

blacks, 42 whites, 23 Hispanics, and 7 Asians—or about 35 per institution. It might be

feasible to offer these students such a summer session, and if voluntary and multiracial, it

would scarcely be stigmatizing. There might be equity problems near the border—What

about students scoring 600 or 620 or even 640—but even if the cutoff were raised to 650,

there would be only 81 students eligible per institution (46% black and Hispanic), and

many would not come. At the higher cutoff, because of the increased numbers, there is

some tension between the ideals of compensation (minorities only) and integration (all

students who are eligible) when money is, as it usually is, tight, but the lower cutoff at 600

might serve most goals quite well. Similar calculations could be done by any majority white

selective school.

Most of the other features of the two programs considered seem to us less useful than

working on essential course material—nothing is quite so motivating to a student as

succeeding at the serious business of learning. For that reason, any method of encouraging

continued hard work would be important. One of the best-known methods of encouraging

hard work among minority students was devised by Treisman (1992; see Fullilove and

Treisman, 1990, for an evaluation), who recruited black and Hispanic students at Berkeley

and later at Texas to special sections of calculus classes where they put in an extra 4 hours

beyond what they would ordinarily have done, spent in small groups working on

challenging problems, inevitably teaching and learning from each other and doing whatever

remedial work might be necessary in that context. Calculus is prerequisite to most sciences,

so that its successful completion is critical to advancement in science.

Such selected students had stated an interest in a science or math career, had been specially

invited to "honors" sections, and had accepted. Clearly they were more motivated than the

average student in their comparison groups, and they also had slightly but not significantly

higher SATM scores than those who elected not to participate, with both groups having

medians in the 470-540 range. That they did significantly better than their comparisons,

both in grades and in persistence, is no surprise. More persuasive of the program's power

is the evidence that the nonparticipant minority controls performed the same as all the

minority students (the comparisons reported were exclusively concerned with black

students) had done prior to the intervention, which means that the program was offering a

new way of enlisting the motivation and realizing the potential of at least some substantial

fraction of the black population.

64 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
A later evaluation of the method (Bonsangue, 1994), done on a largely Hispanic population of

beginning science students at California Polytechnic State University, arrived at similar

conclusions and added data on comparisons with white and Asian students not in the

program. Again, minority students who volunteered for the program did far better in the

first quarter of calculus, by close to a full grade, than nonprogram minority students with

similar SAT scores and high school grades. They also scored half a grade better than the

large group of whites and Asians taking calculus, even though the latter averaged 70 points

higher on SATM. Some of the gains faded in the second year, when the program group got

slightly lower calculus grades than the white-Asian group, but the 3-year persistence rate

of the program students was far better than that of any other comparison group.

The relevance of the Treisman model to highly selective institutions is uncertain. Certainly

the establishment of so-called "honors" sections exclusively for blacks and Hispanics would

have doubtful merit—the white-Asian "nonhonors" students in calculus would average over

700 on the SATM. But making available sections devoted to workshop problem solving

would be undoubtedly useful for those of any ethnicity who volunteered for them. We do

not feel that excluding all or most white or Asian volunteers from such groups is a good

idea, particularly at private institutions. Race relations are difficult enough without

keeping majority students from access to curricular methods of presumed efficacy. There

seems every reason to encourage, though little to require, students to attend such groups; they

would appear to be especially effective for students who are highly motivated and near some

threshold of advanced understanding.

In sum, we believe there are some grounds for considering that prematriculation summer

sessions, as described, and the provision of group problem-solving sessions associated with

calculus and perhaps other science courses, would palliate the effects of relatively poor

preparation for science. It seems especially important that these curricula be demanding and

not remedial. The white-black gap is sufficiently large and these interventions are

sufficiently small in scope and unproven in effect that we would anticipate continued large

differences in persistence, though a little smaller than what now obtains. In addition, we can

repeat a suggestion we gave in our report on science and gender (Strenta et al., 1994): Let

secondary schools know quite specifically what sort of preparation typical successful science

majors at these institutions have had. Black and Hispanic students in our sample took far

fewer AP courses in physics, chemistry, and calculus than did whites and Asians, and they

should learn early in their high school careers what they ought to be taking if they aspire to

study science in highly selective institutions.

Finally, with respect to the question of institutional or any other sort of racism, it was in our

sample remarkable for its absence. The only significant ethnic effect in our analyses of fullsample data was in initial interest, a measure that preceded matriculation. On a questionnairevi

answered by 33 black and 25 Hispanic science majors, and 36 black and 26 Hispanic

dropouts from science, only one (a defector from science alleging a lack of support for a

woman of color engineer) said anything about racism. Neither these comments nor

anything else in the questionnaire seemed to us to constitute even a small indictment of

these institutions as being inhospitable, much less racist. The chief problems for nonAsian minority students aspiring to science majors would appear to be not institutional

racism, but rather a relative lack of preparation and developed ability.

Statements 65
Acknowledgments. We especially thank John Jalowiec, Ph.D., who was the indispensable central figure in

organizing, coding, and entering the vast quantities of data that flowed into his files; and the deft constructor

of the tables and figures of this report. Many others provided essential assistance on this project: Oscar Larsen

(Cornell) and Mark Gloria (Brown) formatted data files at their respective institutions; Kathleen Gemmel

(Cornell) provided feedback on early versions of the questionnaire survey instrument; and George Wolford and

Jay Hull (Dartmouth) gave generously of their statistical advice. This work was supported by grants from the

National Science Foundation (RED 93 53 821) and from the Alfred P. Sloan Foundation.

NOTES

1. "Ethnic" includes "racial" in our discussion. We omit Native Americans as a group because there were too

few of them (34, with only 9 interested in science) for analysis. Also excluded were foreign students (N =

266) and "others" (N = 333).

2. The precise mix of Mexican-Americans, Cubans, Puerto Ricans, and others will usually not be known.

Because of the varying subgroup composition of Hispanic samples, their place in relation to other groups

will vary from study to study.

3. The same result was found when a MaxR2 stepwise regression model was employed. The variable "black"

entered after the six preadmission variables, was significant (p < .0001), and raised the R2 from .203 to .207.

Neither "Hispanic" nor "Asian" was significant.

4. MaxR2 regression analysis produced a similar result: in the nine-variable model (six preadmission variables

plus the three nonwhite ethnic groups), "black" was marginally significant (p < .10) and the other groups

were not.

5. This fact does not contradict the lack of an ethnic effect on persistence, since it is based on SATM alone,

with regard neither to initial interest nor to the several other predictors employed in that analysis.

6. The analysis of the questionnaire, contained in a report of these data to NSF, is available from the authors.

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Manis, J. D., Thomas, N. G., Sloat, B. F., and Davis, C. (1989). An Analysis of Factors Affecting Choices of Majors

in Science, Mathematics, and Engineering at the University of Michigan. Ann Arbor, MI: Center for Continuing

Education of Women, University of Michigan.

Massey, W. (1992). A success story and decades of disappointment. Science 258: 12001201.

Mercer, J. (June 22, 1994). Guiding black prodigies. Chronicle of Higher Education, pp. A22, A24.

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Printing Office (NSB 93-1).

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Washington, DC: National Science Foundation.

Oakes, J. (1990). Opportunities, achievement, and choice: Women and minority students in science and

mathematics. Review of Research in Higher Education 16: 153-222.

Phillips, T. R. (1991). ABET/EXXON Minority Engineering Student Achievement Profile. New York: Accreditation

Board for Engineering and Technology, Inc.

Ramist, L. (1984). Predictive validity of the ATP tests. In T. F. Donlon (ed.), The College Board Technical

Handbook for the Scholastic Aptitude and Achievement Tests (ch. 8, pp. 141-170). New York: College

Entrance Examination Board.

Ramist, L., Lewis, C., and McCamley-Jenkins, L. (1994). Student Group Differences in Predicting College Grades:

Sex, Language, and Ethnic Groups. New York: College Entrance Examination Board (Report No. 93-1).

Smothers, R. (June 29, 1994). To raise the performance of minorities, a college increased its standards. New York

Times, p. A21.

Stevens, J. (1992). Applied Multivariate Statistics for the Social Sciences. Hillsdale, NJ: Lawrence Erlbaum

Associates.

Strenta, A. C., Elliott, R., Matier, M., Scott, J., and Adair, R. (1993). Choosing and Leaving Science in Highly

Selective Institutions. Final Report to the Alfred P. Sloan Foundation. Hanover, NH: Department of Psychology,

Dartmouth College.

Strenta, A. C., Elliott, R., Adair, R., Matier, M., and Scott, J. (1994). Choosing and leaving science in highly

selective institutions. Research in Higher Education 35: 513-547.

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Government Printing Office (NSF 93-95).

Thurgood, D. H., and Clarke, J. E. (1995). Summary Report 1993: Doctorate Recipients from United States

Universities. Washington, DC: The National Academy Press. Tobias, S. (1990). They're Not Dumb, They're

Different: Stalking the Second Tier. Tucson, AZ: Research Corporation.

Treisman, U. (1992). Studying students studying calculus: A look at the lives of minority mathematics students in

college. College Mathematics Journal 23: 362-372.

White, P. E. (1992). Women and Minorities in Science and Engineering: An Update. Washington, DC:

National Science Foundation.

Willingham, W. W. (1985). Success in College: The Role of Personal Qualities and Academic Ability. New

York: College Entrance Examination Board.

Wilson, K. M. (1980). The performance of minority students beyond the freshman year: Testing a "late-bloomer"

hypothesis in one state university setting. Research in Higher Education 13: 23-47.

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two studies. Research in Higher Education 15: 351-375.

Statements 67
Thomas E. Fortmann

Mathematics is ruthlessly cumulative

—Steven Pinker

The Commission poses two questions about science, technology, engineering and

mathematics (STEM):

1. Why minority students disproportionately abandon their STEM aspirations,

2. Whether students in institutions matched to their own academic preparation are more

likely to remain and succeed in STEM, and to what degree affirmative action policies affect

this.

I will attempt to answer the first question and comment briefly on the second, based on my

STEM career and recent experience in K-12 education.

My background includes a physics degree from Stanford, a doctorate in electrical

engineering from MIT, four years of university teaching, and 24 years as a high-tech

engineer and executive. In recent years I have taught mathematics to minority high-school

students in Boston, founded a math institute for elementary teachers, and served on the

Massachusetts Board of Elementary and Secondary Education.

Accumulating Mathematical Proficiency

Many minority college students avoid or abandon STEM majors for the same reason as

nonminorities: insufficient math (and science) preparation in K-12. The disproportionality is

surely related to the well-documented lower quality of math/science (and all other)

instruction in minority and high-poverty schools. Does affirmative action in college

exacerbate that? Perhaps. But the problem begins long before college, and it is most acute in

math and math-related fields because math is more cumulative than, say, history or literature.

Steven Pinker made this point rather eloquently when he said:44

“Calculus teachers lament that students find the subject difficult not because

derivatives and integrals are abstruse concepts—they're just rate and accumulation—

but because you can't do calculus unless algebraic operations are second nature, and

most students enter the course without having learned the algebra properly and need

to concentrate every drop of mental energy on that. Mathematics is ruthlessly

cumulative, all the way back to counting to ten.”

44 Steven Pinker, How the Mind Works (Norton, 1977), p. 341

68 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
I would add that the same is true of algebra: students who don’t understand fractions and use

a calculator to multiply by ten can’t make progress with algebra problems because they’re

bogged down in the arithmetic (imagine factoring a polynomial if you don’t know your times

tables).

And so it goes, right down to first grade.

Preparation for STEM

We need more students of every classification in STEM, and in Massachusetts our STEM

Pipeline Initiative uses outreach, summer programs, and other marketing tactics to entice

more of them, especially minorities and females, into these fields. The problem with this

approach is that the “pool” of entering college students who are actually prepared for STEM

work is quite small. It would be more cost-effective to concentrate limited resources on

increasing the number of STEM-capable students rather than on recruiting harder from the

same small pool.

The small proportion of students entering college able to handle STEM courses and majors

reflects the dreadful state of mathematics learning in K-12, particularly among minorities.

Ask high -school teachers why this is so and they often point to middle school, while middle

-school teachers lament students’ poor preparation in elementary -school arithmetic. So far

no one has blamed the obstetricians.

Unfortunately, this cascade of blame is based in reality. The root problem, in my judgment, is

an appalling dearth of mathematics content knowledge among elementary and even middle

school teachers; until we solve that, improvements and innovations at the high -school and

college levels will have little effect.

Liping Ma was the first researcher to focus national attention on this issue.45 In fact, my

experience suggests that the problem is even worse than she describes. In a group of veteran

5th-6th grade teachers, for example, 57% were unable to answer “75 is 30% of what

number?” and 76% could not find two numbers between 1 and 2/5 and 1 and 41/100.

Teachers’ attitudes about mathematics range from trepidation to full-blown math phobia, a

disease that is highly contagious. This is not the fault of elementary teachers but of

preparation programs and certification systems that virtually ignore mathematics.46 47 And it

creates a vicious cycle in which each generation of teachers is recruited from a group that

leaves high school with weaker math knowledge than the last. Massachusetts has begun to

45 LIPING MA, KNOWING AND TEACHING ELEMENTARY MATHEMATICS (Lawrence Erlbaum Associates, 1999).

For a review and summary see www.aft.org/pubs-reports/american_educator/fall99/amed1.pdf.

46 NATIONAL COUNCIL ON TEACHER QUALITY, NO COMMON DENOMINATOR: THE PREPARATION OF

ELEMENTARY TEACHERS IN MATHEMATICS BY AMERICA'S EDUCATION SCHOOLS (June 2008):

www.nctq.org/p/publications/reports.jsp. 47 NATIONAL MATHEMATICS ADVISORY PANEL, FOUNDATIONS FOR SUCCESS (Final Report, March 2008):

www.ed.gov/about/bdscomm/list/mathpanel/report/final-report.pdf.

Statements 69
address this issue with regulation changes that require more college math courses and a math

test for elementary teacher certification.48

It’s well known that teacher quality is the most important factor driving student achievement,

and that teacher quality—including math content knowledge—is generally lowest in poor

urban districts serving minority populations. Thus the disproportionality that the Commission

cites is no surprise.

Affirmative Action

It seems self-evident, given the cumulative nature of mathematics, that affirmative action will

hinder some students’ STEM aspirations unless it is accompanied by vigorous and sustained

efforts to raise their mathematical capacities to the level of their classmates.

In the absence of effective remediation, should those students be placed in colleges where

their peers’ proficiency in mathematics is similarly lacking? Doing so may result in more

STEM majors, but it masks their (and their peers’) low achievement and limited career

opportunities. The place to address those crippling math deficits is back in K-12, where poor

instruction and math-challenged teachers, along with low standards and social promotion,

allow too many students to reach high school and graduate without the mathematical skills

and understanding they need.

In other words, affirmative action comes into play late in the game and doesn’t address the

underlying mathematical deficiencies that deflect minority (and other) students from STEM

majors and careers.

Recommendation

I encourage the Commission to investigate, as a civil rights issue,49 why so many minority

kids arrive in college unprepared for STEM majors—i.e., why they need affirmative action at

all, and what we can do about it. The answers—far beyond the scope of today’s briefing—

will get to the heart of education reform and teaching quality. There are numerous worms in

that can, including school choice, teacher preparation and certification, professionalization of

teaching, career ladders, differentiated pay scales and incentives, collective bargaining,

accountability, standards-based testing, and school leadership.

That is a tall order, but necessary in order to get beyond the symptoms and treat the disease.

48 Details are in the Commissioner’s Guidelines for the Mathematical Preparation of Elementary Teachers (July

2007): www.doe.mass.edu/mtel/MathGuidance.pdf

49 Robert Moses, voting-rights pioneer and founder of the Algebra Project, argues in his marvelous book

RADICAL EQUATIONS (Beacon Press, 2001) that math literacy is a civil right.

70 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Robin Willner

Let me congratulate the Commission for convening today’s discussion and focusing attention

on the very critical issue of minority participation in Science, Technology Engineering and

Math (or STEM) careers.

I’m honored and pleased that you have asked IBM to participate today. And while I would

not hazard to speak for an entire industry or the private sector, I do believe that my comments

would gain a good deal of support from my colleagues. There is widespread concern about

the future labor needs in the growing areas of the economy -- every major corporate leader

recognizes that the U.S. labor force must continue to provide the talent and leadership that

we need for a robust economic future and to remain competitive in a global economy. I also

want to take this opportunity to tell you about a recent initiative at IBM that focuses on the

Hispanic community and share what we’ve learned about both the challenges and potential

solutions.

Before addressing today’s topic, let me briefly provide some important context. While it has

always been important for business to nurture and prepare a workforce in the U.S. with the

necessary skills, there have been profound changes in the global economy that make this

more important than ever before. In a global economy, the world is not only smaller; it’s full

connected, or, if you will, networked.

There will always be some businesses that will not need to worry about what is happening

around the world, more and more, successful businesses will take the form of what we at

IBM call the Globally Integrated Enterprise. U.S. companies like IBM create great

opportunities for American workers and generate important economic return in the U.S.

precisely because we are globally integrated and functioning on a global scale.

In a connected world, we have access to huge new markets. We also can organize our

business around the globe to optimize operations. If everything is connected, then work flows

throughout the network. And the most important consideration is TALENT. Localities, states

and nations are striving to become places where knowledge is generated and transformed into

new commercial and societal value. They recognize that, of course, we need employees with

basic skills; but more importantly, we need employees who can innovate. A knowledgebased society creates jobs, raises living standards and generates growth that competitors can’t

duplicate rapidly.

The real wealth generators in today’s global economy are technical people. A recent report

by the U.S. Labor Department suggests that over the next 10 years, the need for technical

people in this country is going to grow by 50 percent.

At the same time, there is a serious shortage of professionals and students studying the fields

of science, technology, engineering and mathematics. I won’t repeat the detailed statistics

that you’ve heard from other speakers and that your own preparatory research uncovered. But

let me be very clear on this point. There are plenty of reasons to make sure that every child in

Statements 71
this country has the opportunity and access to be prepared to be an engineer, scientist or

mathematician or whatever their dreams dictate. But more importantly, this is an issue of our

economic survival. If the key to prosperity is having the right talent, then we must take

advantage of the gifts and promise of every child. We ignore any community at our peril. If

the U.S. is to remain competitive, we need children from every ethnic and economic

background prepared for STEM studies and potential careers in the STEM disciplines.

In our efforts to nurture all of this nation’s talent, we need to attend to students from every

minority group and young women as well. American ingenuity has always been the product

of our rich and diverse heritage and the foundation for our economic strength. Each group

has distinctive challenges and opportunities, and IBM has a range of programming to serve

the full range of students. However, with our Latino population, we have the classic paradox

of challenge and opportunity. Or, as our engineers describe it, “the tyranny of large and small

numbers.” And let me use a few compelling statistics to explain.

Over the next 40 years, the United States will be the only developed country that will grow

its population. Much of that growth will come from the Latino community, who are

estimated to constitute 25 percent of the total U.S. population – a growth rate of 30 percent.

This segment of the population will certainly be relied upon, heavily, to help drive our

nation’s economic future.

However, current numbers of Latinos in STEM degree attainment and careers show that they

are grossly underrepresented. According to the National Action Council for Minorities in

Engineering (NACME), Latinos accounted for only 4.2 percent of engineering degrees

awarded in 2005, and merely 1.5 were awarded doctorate degrees. Dropout rates among

Latino youths are the largest at 24 percent compared to 12 percent for African-Americans

and 7 percent for non-Hispanic whites.

The reasons behind these statistics are extremely complex and deeply entrenched.

That is why IBM, along with Exxon Mobil and Lockheed Martin and 150 leaders from

education, business and the community, convened at the America’s Competitiveness:

Hispanic Participation in Technology Careers Summit in May. The objective was to address

this once-hidden, but now clearly visible crisis and, more important, to take action. We also

commissioned a number of research papers from Public Agenda and The Tomas Rivera

Policy Institute to enhance our understanding and help shape our agenda for action.

Perhaps the most compelling information came from Public Agenda, after conducting a

series of interviews with national leaders from every sector. The title of their report tells the

story: “Out Before the Game Begins.”

“Nearly all of the interviewees said that when it comes to Hispanic and Latino students, the

educational pipeline is all but broken. Respondents across the board believed that the current

educational system is not serving the Hispanic population well. This failure extends to all

subject areas, not just science and math. Before these specific subjects can be taught well,

most said, the nation needs to bring basic education up to par. According to nearly all of

72 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
those we spoke with, the overall poverty of Hispanic-Americans is perhaps the largest

contributing factor to poor quality education; Hispanics tend to live in areas of concentrated

poverty with struggling public schools and a less-than-adequate tax base for funding them. A

wide swath of the Hispanic population also lacks the necessary English language skills.”

As a first step, we need more teachers that are qualified to teach math and science. For

example, Education Trust-West found that 44 percent of math courses at high-poverty-level

high schools – where there are large concentrations of underrepresented groups - were led by

teachers without mathematics certification. Given this, it's no surprise that these schools are

not offering the challenging math and science preparation that students need. In 2006, IBM

announced Transition to Teaching, our initiative to address the K-12 STEM teacher pipeline

issue by leveraging our greatest asset – IBM employees.

But it’s not just an educator problem. The absence of role models for Latino students is a

major inhibitor, according to our research. Parent involvement is a factor as well. Immigrant

parents face several obstacles that include long work hours, language barriers, lack of

sufficient formal schooling, and cultural attitudes carried over from home countries that

hinder a parent’s ability to be an advocate for their child.

IBM has made a commitment to focus a variety of education initiatives on schools and

communities serving Latino students -- for example, offering free automatic translation

software to any school district to improve the communication between Spanish-speaking

parents and English-speaking teachers, and increasing our mentoring programs so students

can interact with role models. I’d be happy to discuss any of these in more detail, and I’ve

provided more information with my written testimony. But, these are problems that cannot be

solved by one company or one sector alone. Clearly the private sector, no matter how much it

contributes, is only one part of the solution. There were four key recommendations from the

meeting.

The first recommendation is to recruit, prepare and retain qualified math and science

teachers. We need to create and fund new career paths that encourage the best and brightest

to leverage industry experience to enhance their classroom skills and vice versa while

developing more competitive salaries with a cross-industry career. In the short term, we need

more second career teachers from the ranks of our math and science professionals. The

private and public sectors must collaborate to develop financial incentives for tuition, inservice professional development and competitive salaries. At the same time, we need to

redesign current teacher preparation programs, encouraging – indeed, demanding that –

universities, state education departments, school districts and teacher unions work together to

prepare and support excellent teachers.

The second recommendation is to find ways to reduce undergraduate attrition rates for

Hispanics in STEM majors. We need to focus on those young people who have expressed an

interest in STEM careers and made it as far as a community college, college or university

program and surround them with the necessary mentors, support services and financial aid to

stay the course and succeed. Other supports could include internships that expose them to

Statements 73
STEM careers, job placement services and other connections into the private sector to start

their careers.

The third recommendation is to increase the popularity of STEM careers in the Hispanic

community. The public and private sector should sponsor a major marketing campaign that

educates the Latino community on exciting and lucrative STEM careers, along with

information on how to attain them.

The fourth recommendation is to increase the Hispanic high school graduation rate prepared

for STEM career training. Every high school must offer the same challenging curriculum we

offer at the most successful schools, and all of the students must participate. As part of this,

we must ensure that STEM education starts early and continues throughout a student’s

schooling. One compelling idea is to establish a formal certification for schools that offer an

effective STEM program and meet a standard for student achievement across all socioeconomic and ethnic groups. Public recognition and financial incentives would encourage all

high schools to strive to secure the certification. Middle and high school students should have

mentors from industry who embody the best that STEM has to offer, as well as internship

opportunities that encourage students to dream big and work hard.

Finally, we must find ways to eradicate cultural barriers – such as language – that prevent

Latino parents from participating in their children’s education.

America’s goal must continue to be to raise the standard of living for our children. To do so,

we must take aggressive action. We must capture more minds, more hearts, more souls, more

passion for the STEM disciplines if we are to retain our competitiveness and attain greater

heights of leadership. It is an economic imperative as well as a moral imperative. Whether

you are in business, education or a community leader, I encourage you to get involved today.

74 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Speaker Biographies

Richard Sander

Professor Sander received his bachelor’s degree from Harvard and a law degree and

doctorate in economics from Northwestern. He has taught at UCLA's School of Law since

1989, where he does empirical research on social policy. Sander has done major studies of

inner-city banking, housing segregation, central city poverty, and living wage laws. He is

probably best known for his research on legal education; in this area, Sander has studied

academic support programs, class-based affirmative action, the third year of law school, the

market for lawyers, and, most recently, the systemic effects of racial preferences in legal

education and law firms. Sander has worked to improve the enforcement of fair housing laws

in southern California, and helped to start a program that substantially increased the

participation of low-income Los Angeles workers in the Earned Income Tax Credit program.

Richard Tapia

Dr. Tapia currently serves as the Maxfield-Oshman Professor in Engineering at Rice

University. While at Rice, he has directed or co-directed more underrepresented minority and

women doctoral recipients in science and engineering than anyone in the country. He has

received numerous national awards, including the National Science Foundation's inaugural

Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring for

his work with these students. Dr. Tapia is recognized as a national leader in diversity and for

many years has received dozens of requests to give invited addresses, serve on university

diversity committees, and provide leadership at a national level. Leading professional

organizations have recognized Dr. Tapia’s contributions to diversity by naming two

professional conferences in his honor, describing him as a seminal figure who inspired a

generation of African-American, Native American and Latino/Latina students to pursue

careers in mathematics.

Rogers Elliott

Dr. Rogers Elliot is Professor Emeritus of Psychological and Brain Sciences at Dartmouth

College. He has served as Chairman of the Department of Psychological and Brain Sciences

(1983-86), Chairman of the Department of Education (1975-1980), and as Chairman of the

Master of Arts in Liberal Studies Program (1990-1992). He retired from the College in 2001,

but has continued to teach a course each year, alternating between psychology and law and

individual differences in abilities, with an active appointment as Research Professor. He is

the author of Litigating Intelligence, which addressed legal challenges to intelligence tests.

With colleagues such as A.C. Strenta, he has studied the issue of student interest in and

persistence in science, as functions of gender and race/ethnicity. Dr. Elliot went on to finish

his Juris Doctor degree in 1986.

Speaker Biographies 75
Thomas Fortmann

Tom Fortmann received a B.S. in Physics from Stanford University and a Ph.D. in Electrical

Engineering from M.I.T. After four years teaching at Newcastle University in Australia, he

spent 24 years as a high-tech engineer and executive at BBN Technologies in Cambridge,

MA. Since his retirement from BBN, he has spent over a decade teaching mathematics as a

volunteer in two Boston high schools, founding a math content professional development

program for elementary teachers, and working on math/science policy issues in the

Commonwealth of Massachusetts. He was appointed to the Massachusetts Board of

Elementary and Secondary Education in 2006. He was instrumental in modifying state

regulations to require a mathematics test for elementary certification, and he wrote the state

guidelines specifying college mathematics courses for elementary teacher candidates. He is

the author of an undergraduate textbook on linear control systems, a graduate textbook on

multitarget/multisensor tracking, and numerous papers and articles.

Robin Willner

Robin Willner is Vice President of Global Community Initiatives for the IBM Corporation.

She joined IBM in March 1994 to design and implement Reinventing Education, a

philanthropic initiative in K-12 school reform. This $75 million global program now includes

25 grant partnerships with school districts and states throughout the United States plus 12

other countries, each focusing on a collaborative effort to develop new applications of

technology to overcome common barriers to school improvement and increase student

achievement. In addition, Ms. Willner oversees a range of global philanthropic and volunteer

programs, including the Global Citizens Portfolio, Corporate Service Corps, World

Community Grid, Transition Programs, online mentoring, literacy and work force

development projects, school-to-career programs and other efforts to apply technology to

specific societal issues. She also manages IBM’s humanitarian response to disasters,

including IBM’s response to the China earthquakes, 9/11, the December 2004 tsunami in

south Asia, Hurricane Katrina and dozens of others. Prior to joining IBM, Ms. Willner served

for three and a half years as Executive Director for Strategic Planning for the New York City

Public Schools. In that position, she was the chief policy advisor to Chancellor Joseph A.

Fernandez and oversaw all evaluation, research, testing and data collection activities in the

nation’s largest school district. As Deputy Executive Director of INTERFACE, a New York

City-based not-for-profit agency, for more than a dozen years, she directed over 100 research

reports on public policy in the areas of education, job training and child welfare. Ms. Willner

serves on the Boards of Directors of Grantmakers for Education and the Center for Education

Policy, and the National Academy of Engineering’s K12 Task Force.

76 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Commissioner Statements and Rebuttals

Statement of Commissioner Gail Heriot

The assumption behind the fierce competition for admission to elite colleges and universities

is clear: The more elite the school one attends, the brighter one’s future. That assumption,

however, may well be flawed. The research presented at this briefing provides strong reason

to believe that attending the most competitive school is not always best--at least for students

who aspire to a degree in science or engineering.50

Majoring in science or engineering can be difficult.51 As one Yale University student told the

Wall Street Journal, the science course he took “scared the hell out of me.” “In other classes,

if you do the work, you'll get an A,” he complained. “In science, it just doesn't work that

way.”52

Well ... yes ... the feeling that one is flailing about in science or engineering courses can be

very disconcerting. Many students who start out with such a major switch to something

easier. Others drop out or even flunk out. And it should surprise no one that those who fail to

attain their goal of a science or engineering degree are disproportionately students whose

entering academic credentials put them towards the bottom of their college class.53 Not all

stereotypes about science and engineering students are accurate. But the basic notion that

they tend to be highly-credentialed and hardworking is largely on target. They have to be.

50Apart from the considerations discussed in this report, there may indeed be something special about the

education available from America’s most academically competitive colleges and universities. It should be

noted, however, that some of the most sophisticated research available suggests that when it comes to increasing

one’s income, elite schools are not exactly the ticket. See Stacy Berg Dale & Alan B. Krueger, Estimating the

Payoff to a Highly Selective College, 117 Quarterly J. Econ. 1491 (2002). Graduates of Ivy League institutions

are indeed high earners. But, if this research is correct, this is simply a reflection of the fact that very talented

students attend those schools. If the same students had attended less prestigious schools, they would have done

on average just as well financially–or so this research suggests.

In any event, the competition for admission to elite colleges and universities is not a bad thing in itself.

To the contrary, students who work hard to hone their skills in order to get into their first-choice school have

improved their skills even if ultimately they are not admitted to that school. But occasionally the competition

can be over-the-top. Some parents, for example, are willing to fork over as much as $40,000 for advice from socalled experts in getting their son or daughter into an Ivy League school. Susan Berfield & Anne Tergeson, I

Can Get Your Kid into an Ivy: Michele Hernandez Boasts that 95 percent of Her Teenage Clients are Accepted

by Their First-Choice School. Her Price: As Much as $40,000 a Student, Business Week (October 22, 2007).

51 In general, when I refer to science and engineering in this statement, I mean to include science, technology,

engineering and mathematics, which are collectively referred to as “STEM” in the summary of the proceedings.

The exception is when I discuss the findings of individual empirical studies. There I use terms as they are used

in the particular study being discussed.

52 Dana Milbank, Education: Shortage of Scientists Approaches a Crisis As More Students Drop Out of the

Field, Wall Street Journal (September 17, 1990).

53 See infra at Part C.

Commissioner Statements and Rebuttals 77
What some do find surprising is this: Part of the effect is relative.

54 An aspiring science or

engineering major who attends a school where his entering academic credentials put him in

the middle or the top of his class is more likely to succeed than an otherwise identical student

attending a more elite school where those same credentials place him towards the bottom of

the class. Put differently, an aspiring science or engineering major increases his chance of

success not just if his entering credentials are high, but also if those credentials compare

favorably with his classmates’.55

The reasons for this comparative effect are doubtless complex. But they are based on a

common everyday observation: A good student can get in over his head and end up learning

little or nothing if he is placed in a classroom with students whose level of academic

preparation is much higher than his own, even though he is fully capable of mastering the

material when presented at a more moderate pace. Discouraged, he may even give up–even

though he would have persevered had he been in a somewhat less competitive environment.56

Science and engineering are ruthlessly cumulative. A student who has difficulty with the first

chapter in the calculus textbook is apt to have difficulty with the second, third and fourth

chapters. Indeed, the subsequent courses in the mathematics curriculum may be a problem.

By contrast, an English literature student who simply fails to read the Chaucer assignment is

not necessarily at a serious disadvantage when it comes to reading and understanding George

Eliot. Since quitting science and engineering is easy–ordinarily all one has to do is switch

majors–the attrition rate is quite high. By senior year, there are significantly fewer science

and engineering majors than there were freshmen initially interested in those majors.

54 See infra at Part C. 55 As one early researcher on this topic put it, there is an academic advantage to being a “big frog” in the “frog

pond.” James A. Davis, The Campus as a Frog Pond: An Application of the Theory of Relative Deprivation to

Career Decisions of College Men, 72 Am. J. Socio. 17 (July 1966). This article was written well before the

concept of mismatch came to be associated with the controversy over affirmative action and was not focused

specifically on science and engineering. Davis found that college GPA is more strongly correlated with career

choice than is quality of institution. In other words, while students take both their college grades and the

academic quality of the school they are attending into account in evaluating their career choices, they tend to

place more emphasis on college grades than is justified. A student at the bottom of his very elite class will

discount his abilities more than is called for, while a student at the top of a class at a mediocre school will overestimate his ability. Davis concludes: “[T]hese ideas have some implications for educational policy. At the level

of the individual, they challenge the notion that getting into the ‘best possible’ school is the most efficient route

to occupational mobility. Counselors and parents might well consider the drawbacks as well as the advantages

of sending a boy to a ‘fine’ college, if, when doing so, it is fairly certain he will end up in the bottom ranks of

his graduating class.” Id. at 30-31.

56 While the observation that a student is more likely to learn in a classroom where his academic credentials are

not at the bottom of the class is common sense, it is not necessarily true in all contexts. Take, for example, a

school with 100 first graders. If one were to divide the class into thirds according to their achievement test

scores, it is not necessarily the case that all three groups would learn more than if they were divided into three

groups at random. Students with behavioral problems may tend to be over-represented in the group of students

with the lowest scores for the simple reason that their behavior has interfered with their own learning.

Concentrating them in one group may create havoc in the classroom that interferes with the ability of all

students, not just those with behavioral problems, to learn.

78 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Some call this comparative effect the “mismatch” effect.57 And although there is reason to

believe that it applies to other kinds of learning, science & engineering examples are perhaps

the easiest to imagine: I have every confidence that I can learn basic physics, despite the fact

that I have never taken a course in it and my mathematics skills are a little rusty. If I ever lose

my job as a law professor, I suspect that I am fully capable of re-tooling as a physics teacher

if that is where the available jobs turn out to be. But if I were thrown into the Basic Physics

course at Cal Tech, with many of the very best science students in the world, I would be lost

and likely learn little if anything. I would be mismatched.58 On a good day I might make a

few lame jokes about my unhappy situation; on a bad day I might even get a little testy about

it. But I would be unlikely to come out of that class as competent in the basic principles of

physics as I would have in a less high-powered setting.59

That doesn’t mean, however, that those who aspire to a career in science or engineering must

graduate from high school already prepared for the rigorous science curriculum at the

world’s most competitive science-oriented university. There are many careers in science and

engineering. Many have been filled by latecomers to these fields. It simply means that for

those who are not already well-prepared when they begin to study science or engineering in

earnest, the best strategy may be to avoid going immediately head-to-head with better

prepared students.

The interest of the Commission in mismatch centers mainly on its effect on members of

underrepresented racial minorities–primarily African-Americans, Hispanics and American

Indians. Since admissions standards are frequently relaxed in order to admit a more diverse

student body, minority students constitute a disproportionate share of the students with

entering academic credentials towards the bottom of any particular class.60 Obviously,

57 See, e.g., Thomas Sowell, Inside American Education: The Decline, the Deception, the Dogmas (1993). 58 Mismatch may be positive or negative. If a typical Cal Tech freshman were to take a Basic Physics class

designed for law professors like me, many of whom have never excelled at science, she would likely learn less

than she would have in a class with her fellow Cal Tech students. Coasting through a “Basic Physics for

Dilettantes” course, she would be the victim of positive mismatch, while I am negatively mismatched in the

hypothetical.

59 The empirical studies discussed in this statement, see infra at Part C, do not distinguish among the reasons

that mismatched students might drop out of science and engineering more often than non-mismatched students

with similar credentials. They simply record that they disproportionately do so. Is it just because they perceive

that they aren’t doing well relative to other students and hence lack confidence in themselves? Or are they

actually learning less than their similarly-credentialed counterparts who persevere in science or engineering at

somewhat less elite institutions? Or both? There is, at present, no national examination for science and

engineering achievement that would allow researchers to determine whether college students who were

mismatched and dropped out of science or engineering actually learned less than their counterparts at less elite

schools who took similar courses. The intuitive answer is that they did and that their self-confidence was also

shaken in the process. But it is unnecessary at this point to draw a distinction. The law school experience is

clearer, since law students must pass a bar examination in order to practice law. There is empirical evidence that

mismatched law students are less likely to pass the bar examination than their non-mismatched counterparts at

less elite schools. Richard Sander, A Systemic Analysis of Affirmative Action in American Law Schools, 57

Stan. L. Rev. 367, 393 (2004).

60 While the Supreme Court case of Gratz v. Bollinger, 539 U.S. 244 (2003), was pending before the Supreme

Court, much publicity was centered around the fact that the University of Michigan routinely added the

equivalent of an entire letter grade to the admissions index of underrepresented minority students. An AfricanCommissioner Statements and Rebuttals 79
however, there are other categories of students, such as athletes, children of alumni and other

special admittees, who should also be mindful of the risk of mismatch that comes with

preferred treatment in admissions.

All such students have a dilemma to face. Should they accept the supposed “leg up” they

have been offered? Or should they reject it and attend a school at which that leg up would

have been unnecessary? The answer is likely to vary from student to student and may be a

question of priorities. Which is more important–that student’s desire to attend the most elite

school or his or her desire to be a physician, engineer, or scientist?

The problem is that few students who receive a preference realize that their entering

academic credentials are well below the institutional median. Fewer still realize that

relatively low academic credentials are likely to handicap their ability to earn a degree in

science or engineering there and that their odds would be better elsewhere. Instead, they are

recruited, indeed romanced, by colleges and universities who allow the scramble for a

racially diverse campus (or a winning football team or happy alumni) to overcome their

commitment to full and fair disclosure.

It is for this reason that the Commission has recommended that colleges and universities

inform the students they are attempting to recruit of the mismatch issue and its potential

impact. Tuition for the 2010-11 academic year at Duke University, the University of San

Diego and Yale University, for example will be $36,065, $36,950 and $38,300 respectively.

That, of course, does not include room and board, books or various student fees. Many

students are willing to incur such debt because they envision that their future career will be in

a well-paying field like medicine, dentistry, or nuclear engineering. When they graduate four

years later with a degree in a soft major, they may be saddled with a much larger debt than

they would have been willing to undertake had they understood that the odds were stacked

against their success in science or engineering. But no one told them.

American student with a high school grade point average of 2.95 would thus be preferred to an Asian American

student with a high school grade point average of 3.94 (just shy of straight As) all other things being equal. The

Gratz case rejected such a formulaic approach, but it did not reject the size of the preference granted to minority

students. And indeed, the evidence suggests that the size of the preference grew at the University of Michigan in

the period following the Gratz decision. See infra at n. 39.

Michigan’s affirmative action policies were not more over-the-top than those of other universities.

Lawsuits filed against the University of Georgia, the University of Texas and the University of Washington

prior to the Supreme Court’s decision in Gratz brought to light similar practices. Hopwood v. Texas, 78 F.3d

932 (5th Cir. 1996), cert. denied 518 U.S. 1033 (1996)(law school); Smith v. University of Washington, 233 F.

3d. 1188 (9th Cir. 2000)(law school); Johnson v. Board of Regents, 106 F. Supp. 2d 1362 (S.D. Ga. 2000),

aff'd, 263 F.3d 1234 (11th Cir. 2001)(undergraduate admissions policies). See also Robert Lerner & Althea

Nagai, Racial and Ethnic Preferences in Undergraduate Admissions at Six North Carolina Public Universities,

Center for Equal Opportunity (May 28, 2007)(finding similar preferences at competitive universities in North

Carolina), available at http://www.ceousa.org/content/view/442/100/.

Some of the most discriminatory policies are at professional schools. At law schools, for example, the

average black student has an academic index that is more than two standard deviations below that of his average

white classmate. Richard Sander, A Systemic Analysis of Affirmative Action in American Law Schools, 57

Stan. L. Rev. 367, 393 (2004).

80 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
At minimum, this is an issue that students should be informed of so that they, with assistance

from their parents, high school teachers and guidance counselors and other advisors, can

decide for themselves how to proceed. But let’s look at the evidence step by step.

A. Minority Students Are Indeed Underrepresented in Science and Engineering.

There is no segment of the labor force that proportionally reflects the nation’s demographic

profile. Physicians are disproportionately Jewish. Jockeys are disproportionately Hispanic.

The wine industry employs more than its share of Italian Americans. Even within

professions, disproportionality is the rule, not the exception. Among lawyers, litigators are

often Irish-American. Among physicians, radiologists are disproportionately Subcontinent

Indian-American.

Lack of proportionality is not necessarily the result of systematic discrimination. There are

many ways in which one’s family background, language, and cultural traditions directly or

indirectly affect career choices. As a result, it would be hard to find a single profession or

occupation that looks, as it is often put, “like America.” The world is always more complex

than that.

But science and engineering are special. For one thing, they are not single fields. Instead,

obtaining an initial degree in a field of science or engineering is the gateway to a large

number of respected professions and occupations--aviation inspector, bio-chemist, computer

software engineer, dentist, electrical engineer, forester, geophysicist, hematologist, insurance

actuary, jet propulsion engineer, lighting engineer, mathematics teacher, nuclear engineer,

optometrist, pharmacist, quantitative analyst, radiologist, science teacher, thoracic surgeon,

urologist, veterinarian, waste engineer, x-ray engineer, and zoologist. These fields represent a

significant portion of the most lucrative and dynamic sectors of the world economy. If

African-Americans, Hispanics and American Indians are facing significant impediments in

entering these fields, that is a situation that calls for attention.61

Using data from the National Survey of College Graduates conducted by the U.S. Census

Bureau, UCLA law professor Richard Sander and senior statistician Roger Bolus have

calculated the following racial gap in science among college graduates, including immigrants

educated or partly educated abroad, age 35 and under:

61 In addition, many have asserted that there is a shortage of Americans trained in science and engineering and

that this shortage will likely get worse. If a particular segment of the population is underrepresented in these

fields, it is only prudent for colleges and universities, employers and government to look into what can be done

to increase their participation. National Science Foundation, Future Scarcities of Scientists and Engineers:

Problems and Solutions (1992).

Commissioner Statements and Rebuttals 81
Table I: How Significant is the Racial Gap in Science?

62

Frequency Relative White Black Hispanic Asian

to Population

Gen. Pop. 100 100 100 100

Bachelor’s Degree Science 100 36 41 454

As the chart indicates, blacks and Hispanics are only 36 percent and 41 percent respectively

as likely as whites to have a bachelor’s degree in science or engineering. An Asian, by

contrast, is more than four and a half times more likely than a white to hold such a degree.

Blacks are only 15 percent as likely as whites and Hispanics are only 26 percent as likely as

whites to have a Ph.D. in science. Asians, on the other hand, are more than seven times as

likely as whites. The underrepresentation of blacks and Hispanics in science and engineering

is real (although these figures are in part a reflection of the immigration of highly-qualified

individuals from abroad).63

Of course, concern over underrepresentation in science and engineering is not new. On

November 13, 1992, the popular magazine Science issued a special news report entitled

“Minorities in Science.” In it, the editors lamented:

For 20 years, science has been wrestling with “the pipeline problem”: how to

keep minorities from turning off the obstacle-strewn path to careers in science,

mathematics, and engineering. Thousands of programs have been started since

the late 1960s to bring diversity to the scientific work force. But their results

have been dismal....64

One thing, however, is clear. The problem has not been an unwillingness to spend money. By

1992, the National Science Foundation had already spent over $1.5 billion on programs

designed to increase the number of minorities in science or engineering. Officials at the

National Institutes of Health estimated that they had pumped an additional $675 million into

the system. Uncounted state, local, foundation and industry programs contributed millions

more.65

But the consensus of opinion has been that much of the money had been spent unwisely. In

their eagerness to qualify for the vast grants available to educate future minority scientists

and engineers, many colleges and universities admitted minority students with little

62 Richard Sander & Roger Bolus, Do Credentials Gaps in College Reduce the Number of Minority Science

Graduates, Working Paper 2 (Draft July 2009)(using data from 2003)(hereinafter “Sander & Bolus”).

63 Unlike African-Americans, Hispanics in science and engineering do not appear to be underrepresented

relative to Hispanics in other college disciplines, such as the humanities. Id. Relative to their initial interest,

however, they are underrepresented. Ordinarily one would expect a language minority to be overrepresented in

science and engineering, since those disciplines do not require the same language skills as the humanities.

64 Elizabeth Culotta & Ann Gibbons, Minorities in Science: Two Generations of Struggle: Special Report

Overview, 258 Science 1176 (November 13, 1992).

65 Calvin Sims, What Went Wrong: Why Programs Failed, 258 Science 1185, 1185 (November 13, 1992).

82 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
background in science or mathematics. In the early days of affirmative action, “colleges took

any person of color who wanted to become an engineer, regardless of their background,” said

Mary Perry Smith, a former Oakland schoolteacher and founder of California’s Mathematics,

Engineering, Science Achievement (MESA) program, which promotes minority student

participation in those fields. “They tried to turn students who barely knew algebra into

engineers and it was a total failure.”66

“The country cannot repeat the experiment of the last 20 years,” said Luther Williams in

1992, then the assistant director of education and human resources at the National Science

Foundation. Williams, who later went on to become provost of Tuskegee University, a

historically black university with a reputation for emphasizing a science and engineering

curriculum, was blunt: Those vast expenditures were “an incredible waste of financial and

human resources.”67

Was Williams being too harsh? Perhaps. Progress has been made and it will continue–even

though it is not as much progress as we would like. But if the problem is going to be solved,

it will not be solved by more of the same thinking that has characterized the efforts of the last

forty years. A re-examination of the assumptions behind those efforts is in order–even if it

will step on a few well-entrenched toes.

B. There is No Problem with Lack of Interest in Science and Engineering Among Minority

Students. It is Disproportionate Attrition that is the Cause for Concern.

The problem with minority underrepresentation in science and engineering is not the result of

lack of interest among college-bound African-Americans, Hispanics and American Indians.

Study after study has found just the opposite.68 Indeed, if anything, such students are slightly

more interested in pursuing science and engineering degrees than white students. For

example, Professors Alexander W. Astin & Helen S. Astin of UCLA’s Higher Education

Research Institute examined a sample of 27,065 students enrolling as freshmen at 388 fouryear colleges in 1985. They found that the rate of initial interest in majoring in a biological

science, a physical science or engineering was, in descending order, 52.6 percent for Asians,

35.7 percent for Chicanos, 34.5 percent for American Indians, 34.2 percent for AfricanAmericans and 27.3 percent for whites.69

These findings were consistent with later efforts to study the issue. When Dartmouth College

psychology professor Rogers Elliott and his co-investigators looked at a sample of 4,687

students enrolling at four elite colleges and universities in 1988, they found that 55 percent of

66 Id. at 1187. 67 Id. 68 Frederick L. Smyth & John J. McArdle, Ethnic and Gender Differences in Science Graduation at Selective

Colleges with Implications for Admission Policy and College Choice, 45 Res. Higher Ed. 353, 357 (2004)

(calling this finding “consistent” and citing a number of studies dating back to the late 1970s) (hereinafter

“Smyth & McArdle”).

69 Alexander W. Astin & Helen S. Astin, Undergraduate Science Education: The Impact of Different College

Environments on the Educational Pipeline in the Sciences 3-9, Table 3.5 (1993), available at

http://www.eric.ed.gov/PDFS/ED362404.pdf (hereinafter “Astin & Astin”).

Commissioner Statements and Rebuttals 83
the Asians, 44.2 percent of the African-Americans, 44 percent of the Hispanics, and 41.4

percent of the whites were initially interested in majoring in science.70 Similarly, Richard

Sander & Roger Bolus, in analyzing all students enrolling in the University of California

between 2004 and 2006, found that 57.1 percent of Asians, 40.5 percent of AfricanAmericans/Hispanics and 34.7 percent of whites declared an intention to major in science or

engineering.71

To my knowledge, no one who has examined the evidence disputes these figures. They are as

solid as any figures in social science. If there is a problem with lack of interest in science and

engineering, it is with college-bound whites, not African-Americans, Hispanics and

American Indians.

To be sure, that doesn’t mean that there is no point in encouraging even more

underrepresented minorities to aspire to careers in science and engineering. Programs that are

proven to encourage such interest may well be money well spent. But if one wants to

understand the root of the problem, one must look elsewhere.

And some researchers have. Their work has shown that the problem for minority college

students comes a little further down the pipeline. While African-Americans, Hispanics and

probably American Indians have high rates of initial interest relative to whites, they are less

likely to follow through with that interest. Somewhere in college, the intention to graduate

with a degree in science or engineering dies. Alexander & Helen Astin report, for example,

that while 68 percent of Asians and 61 percent of whites in their sample followed through on

their intention to major in biological science, physical science or engineering four years later,

only 47 percent of African-Americans and 37 percent of Hispanics did the same. The rest had

apparently changed majors, dropped out, or flunked out.

Consequently, while one might expect, given their level of interest, that African-American

college students would be somewhat over-represented among science and engineering

college graduates, they turn out to be underrepresented instead. Hispanics are a special case.

With them, English mastery is sometimes a problem. One would therefore expect very high

perseverance in science and engineering, since transfer to a discipline that requires verbal

skills in English can be daunting. All other things being equal, over-representation in science

and engineering should be expected for a language-based minority. But for Hispanics

attrition rates in science and engineering were also unusually high.

Similar results were obtained by Rogers Elliott and his co-investigators. In their study, they

found that 70 percent of Asians persisted in their ambition, while 61 percent of whites, 55

70 Rogers Elliott, A. Christopher Strenta, Russell Adair, Michael Matier & Jannah Scott, The Role of Ethnicity

in Choosing and Leaving Science in Highly Selective Institutions, 37 Res. Higher Ed. 681, 692-93

(1996)(hereinafter “Elliott”).

71 Sander & Bolus, supra n. 13 at 3. Sander and Bolus also report that among the University of California

students enrolling from 1992 to 2006, 52.6 percent of Asians declared an intention to major in science and

engineering, as did 37.5 percent of Blacks/Hispanics and 34.7 percent of whites.

84 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
percent of Hispanics and 34 percent of blacks did.72 Others had similar findings.73 Again, I

am aware of no contrary evidence.

C. Students with Low Entering Credentials in Science, Both in Absolute and in

Comparative Terms, Are More Likely to Leave Science & Engineering.

It is tempting to ask the question “What accounts for disproportionate minority attrition?”

first. But that temptation should be avoided. Instead, the first question should be “What

accounts for student attrition in general?” Once that preliminary question is answered, the

question about disproportionate minority attrition essentially answers itself.

It is no secret that entering science credentials–like Math SAT score and the number and

grades received for high school courses in mathematics and science–are strongly correlated

with persistence in science.74 Since African-American, Hispanic and American Indian

students tend as a group to have lower entering science credentials, they are almost certain to

have a higher attrition rate from science and engineering.75

It would be nice if the disparities among the races, including the disparities between Asians

and others, could be eliminated overnight by improving the performance of underrepresented

minorities.76 For that matter, it would be nice if disparities between individuals could be

eliminated and everyone could perform better in mathematics, science, and all subjects.

72 Elliott, supra n. 21, at 694. See also National Science Foundation, Women, Minorities, and Persons with

Disabilities in Science and Engineering (NSF Report 99-338) (1999); National Science Foundation, Future

Scarcities of Scientists and Engineers: Problems and Solutions (1990)(finding persistence rates of 43 percent for

majority students and 21 percent for minority students); T.L. Hilton, J. Hsia, D.G. Solorzano, & N.L. Benton,

Persistence in Science of High Ability Minority Students (1989) ( reporting that 54 percent of Asian, 44 percent

of white, 36 percent of black and 29 percent of Latino high school seniors who had intended to attend college

and major in science or engineering were doing so two years later).

73 Smyth & McArdle, supra n. 19, at 361-63. 74Astin & Astin, supra n. 20, at 3-9, Table 3.5; Elliott, supra n. 21, at 694; Smyth & McArdle, supra n. 19, at

357; Sander & Bolus, supra n. 13.

75 See id. See also William G. Bowen & Derek Bok, The Shape of the River: Long-Term Consequences of

Considering Race in College and University Admissions (1998).

76 Sadly, some of the most promising avenues for K-12 improvement are not being pursued. Consider the D.C.

Opportunity Scholarship Program, which is (or more accurately was) the District of Columbia’s federallyfunded school voucher program, providing $7,500 in tuition per year to low-income students to attend private

schools. The overwhelming majority of its beneficiaries were African-Americans or Hispanics. At the height of

the program, it allowed over 1,700 students to escape the grasp of D.C.’s dysfunctional public school system

and attend quality private schools.

The best hope that one day racially preferential admissions policies will be a quaint relic of the past

comes from programs like it. Careful social science research, led by Dr. Patrick Wolf of the University of

Arkansas College of Education and Health Professions, concluded that, after three years of study, students

receiving these scholarships had improved reading skills–equivalent to 3.1 additional months of study--relative

to their counterparts, who had remained in D.C. government schools. In other words, bit by bit, the achievement

gap was closing.

The program enjoyed the warm support of D.C. Mayor Adrian Fenty and D.C. Public Schools

Chancellor Michelle Rhee–both reform-minded Democrats. It was also supported by almost 70 percent of D.C.

residents. But teachers’ unions let it be known they opposed it–as they do all school choice programs. Buried in

Commissioner Statements and Rebuttals 85
There is no doubt that improvements can be made even within the constraints of the current

system. Dr. Thomas Fortmann testified before the Commission, for example, that more needs

to be done to ensure that mathematics and science classes at the elementary and secondary

levels are being taught by qualified teachers. The Commission has responded by

recommending that K-12 schools “recruit qualified math and science teachers using, if

necessary, pay adjustments and incentives.”77

But if there is one thing that we have learned during the many decades that this problem has

been receiving attention, it is that few improvements can be made quickly. The mismatch

problem, however, may be a partial exception. Matching students to the right college or

university for their level of developed academic ability could increase the number of science

and engineering majors in fairly short order.

As three independent studies have now concluded, absolute credentials are not the only thing

that matters in keeping college students in science and engineering. Relative credentials are

also important. A student whose entering credentials are at the bottom of the class at the

school he attends is less likely to persevere in his quest for a degree in mathematics or

engineering than a student with identical credentials who attends a school where those

credentials place him higher in the class.

The first of these studies was that published by Rogers Elliott and his co-investigators in

1996.78 The single most important culprit they found was the “relatively low preparation of

black aspirants to science in these schools.”79 The Elliott team was careful to put the

emphasis on “relatively.” It wasn’t just entering credentials demonstrating highly developed

ability at science that mattered, but comparatively high credentials. A student who attended a

school at which his Math SAT score was in the top third of his class was more likely to

follow through with an ambition to earn a degree in science or engineering than was a student

with the same score who attended a school at which his score was in the bottom third. The

following chart was presented:

the 1,000-page spending bill for 2010, was language that closed down the program to new students. The

program was effectively gutted when President Obama signed the bill into law in December.

Three months later, Senator Joseph Lieberman (I-CT), joined by co-sponsors Robert Byrd (D-WV),

Susan Collins (R-ME), John Ensign (R-NV), Dianne Feinstein (D-CA), Jon Kyl (R-AZ), and George Voinovich

(R-OH), led a valiant effort to revive the program. Without support from the Administration, however, their

effort was defeated by a vote of 55 to 42. The Washington Scholarship Fund, which administers the D.C.

Opportunity Scholarship Program, closed its doors at the end of the school year in 2010.

77 Dr. Fortmann testified: “The root problem, as I’ve seen and as I say I’ve been working intimately with some

of these people is the dearth of mathematics content knowledge among elementary teachers. It’s really quite

appalling and it extends to many middle school teachers as well. And until we solve that, improvement and

innovations at the high school and college levels really can’t have much effect. And the reason they can’t have

much effect is the cumulative nature of mathematics that I just mentioned.” Tr. at 47-48. Dr. Fortmann also

directed the Commission’s attention to evidence that fifth and sixth grade teachers responsible for teaching

students mathematics were themselves not competent at arithmetic. Tr. at 38-49.

78 Elliott, supra n. 21, at 681. 79 Id. Among the credentials that mattered most were number of science courses taken, average grades in high

school science courses and SAT-Math score.

86 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Table II: Percentage of Earned Degrees in the Natural Sciences as a Function of

Terciles of the SAT-M Distribution in 11 Institutions80

Tercile 1 Tercile 2 Tercile 3

Institution % Degrees SAT-M % Degrees SAT-M % Degrees SAT-M

Institution A 53.4 753 31.2 674 15.4 581

Institution B 57.3 729 29.8 656 12.9 546

Institution C 45.6 697 34.7 631 19.7 547

Institution D 53.6 697 31.4 626 15.0 534

Institution E 51.0 696 34.7 624 14.4 534

Institution F 57.3 688 24.0 601 18.8 494

Institution G 62.1 678 22.6 583 15.4 485

Institution H 49.0 663 32.4 573 18.6 492

Institution I 51.8 633 27.3 551 20.8 479

Institution J 54.9 591 33.9 514 11.2 431

Institution K 55.0 569 27.1 472 17.8 407

Medians 53.6 31.4 15.4

According to the authors, the bottom line was this: A student with an SAT Math score of 580

“who wants to be in science will be three or four times more likely to persist at institutions J

and K, where he or she is competitive, than at institutions A and B, where he or she is not.”81

For some this is counter-intuitive. The more prestigious the school, they believe, the more

adept it should be at graduating future physicians, scientists, and engineers, no matter what

their entering credentials. But instructors everywhere must pitch the material they teach at a

particular level. They can pitch to the top of the class, to the middle or to the bottom, but they

can’t do all three at the same time. At elite colleges and universities pitching to the bottom of

the class is uncommon–especially in the science and engineering departments. The whole

point of these institutions is to teach to the top. That is the reason that students, who may

80 Id. at 701. 81 Id. at 702. This estimate, of course, was based on the assumption that the student started out with a desire to

major in science or engineering. Whether a student with no particular plans to major in science or engineering is

more likely to graduate with a science or engineering degree if he attends a school at which he is properly

matched is a more complex matter. As the Elliott team demonstrated, students with higher SAT Math scores are

more likely to begin college with a desire to major in science. Consequently, institutions A-E likely have more

students interested in pursuing science than Institutions F-K and thus would naturally be expected to award a

higher proportion of science degrees, since that is what their students desire. And indeed they did. The Elliott

team reported that Institution A-E were about twice as likely to award science degrees as Institutions F-K, with

about 28% of the first group’s bachelor’s degrees being in science and about 15% of the second group’s.

Nevertheless, as they point out, “a 54 percent chance of getting one of the 15 percent of the degrees that are in

science is nearly twice as good as a 15 percent chance of getting one of the 28 percent of degrees that are in

science.” Id. at 702.

Commissioner Statements and Rebuttals 87
have been positively mismatched in high school, are willing to travel thousands of miles and

incur significant debt to attend them. If they were to abandon that practice and resolve to

teach to the bottom of the class, they would no longer be elite institutions.82

The extraordinary record of Historically Black Colleges and Universities was one source of

evidence cited by the Elliott team in favor of their conclusion. With only 20 percent of total

African-American enrollment, these schools produce 40 percent of the African-American

students graduating with natural science degrees according to the National Science

Foundation. These students frequently go on to earn Ph.D.s from mainstream universities.

The National Science Foundation reports, for example, that of the approximately 700

African-Americans who earned a doctorate in science or engineering between 1986 and

1988, 29 percent earned their undergraduate degree from an HBCU. For biologists, the figure

was 42 percent and for engineers it is was 36 percent.83 Even those who have mixed feelings

about HBCUs (and I am such a person) must admit this is impressive.

Why have HBCUs been so successful? Unlike at mainstream institutions with their high

levels of affirmative action, African-American students at HBCUs are not grouped at the

bottom of the class. Roughly half of African-American students at HBCUs will be in the top

half of the class. Many will be honor students. As a result, systematic mismatch is just not an

issue.84

The problem is not that there are no minority students capable of doing honors work at

mainstream college and universities. There are many. But there are not enough at the very

top tier to satisfy the demand for diversity. And when elite universities like Cal Tech, MIT or

the Ivies lower their academic standards in order to admit a more racially diverse class,

schools one or two tiers down feel they must do likewise, since the minority students who

might have attended those schools based on their own academic record are instead attending

the more elite schools. The problem thus cascades downward to the fourth and fifth tiers,

which respond similarly. As a result, a serious gap in academic credentials between minority

and non-minority students is created at all competitive levels at mainstream universities–a

82 In theory, intensive remedial instruction is supposed to bridge the gap between the top and the bottom. But

not every theory works out in reality. The educational experience at elite institutions is meant to be a full-time

job and then some. With only twenty four hours in a day, something has to give. Every hour a minority student

spends in a remedial classroom, sometimes struggling to stay on top of material other students are having less

trouble with, is an hour other students can spend getting a deeper understanding of that material. The game of

catch-up is thus never-ending.

83 Elizabeth Culotta, Black Colleges Cultivate Scientists, 258 Science 1216 (November 13, 1992)(hereinafter

“Culotta”).

84 The Elliott team members were particularly impressed that HBCUs are able to graduate large numbers of

students in science and engineering despite entering credentials that were significantly lower than those

ordinarily found at elite institutions. Students at Xavier University, for example, were reported to have SAT

Math scores averaging around 400, yet half of the class was majoring in science. If elite schools could do the

same with minority students (or with students in the bottom third of the class generally), it would be

astonishing. In fact they do the opposite. They are able to award far fewer science or engineering degrees to

African-Americans than one would expect given the number of African-American students in their classes.

Elliott, supra n. 21, at 700.

88 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
gap that results in seriously disappointing grades for many minority students, especially in

science and engineering classes where good grades are hard to come by.

At least one HBCU faculty member–Professor Walter Pattillo, Jr. of North Carolina Central

University–intuitively grasped the mismatch problem even before the Elliott team was able to

demonstrate its existence empirically. As then-chairman of the biology department, he vented

his frustrations to Science magazine in 1992: “The way we see it, the majority schools are

wasting large numbers of good students. They have black students with admission statistics

[that are] very high, tops. But these students wind up majoring in sociology or recreation or

get wiped out altogether.”85

Neither Professor Pattillo nor the Elliott study received attention from mainstream college or

university administrators. Admissions policies at competitive schools continued to emphasize

the importance of recruiting minority students even if their entering credentials would put

them towards the bottom of the class.86 Instead, emboldened by their perception that the

Supreme Court had given a constitutional green light to racially preferential admissions

policies in Grutter v. Bollinger (2003),87 selective college and universities ramped up those

policies.88 The supposed beneficiaries of these policies–minority members aspiring to

become physicians, engineers and scientists–were not informed.

Around that time, however, the tide of opinion among social scientists studying the issue was

beginning to turn, even as is remained frozen among college and university administrators.89

One of the milestones was the publication of Increasing Faculty Diversity: The Occupational

Choices of High Achieving Minority Students in 2003. The long-term project was funded by

the Mellon Foundation, which had been and remains one of the nation’s most zealous

institutional backers of race-based admissions policies. The authors’ mission was to

determine why more minority students are not attracted to careers in academia. Their

conclusions, reached after extensively questioning 7,612 high-achieving undergraduates at 34

colleges and universities, pointed to mismatch as a significant culprit:

The best-prepared African-Americans, those with the highest SAT scores,

are most likely to attend elite schools, especially at the Ivy League. Because

of affirmative action, these African-Americans (those with the highest scores

on the SAT) are admitted to schools where, on average, white students’

85 Cullotta, supra n. 34, at 1218. 86 Indeed accreditation authorities have often demanded it. See, e.g., Gail Heriot, Affirmative Action in Law

Schools, 17 J. Contemp. Legal Issues 237 (2008)(symposium issue)(discussing the American Bar Association

diversity requirements for law schools and its efforts to pressure law schools into increasing minority

representation). See also Susan Welch & John Gruhl, Affirmative Action and Minority Enrollments in Medical

Schools and Law Schools 80 (1998).

87 539 U.S. 306 (2003). 88 Althea K. Nagai, Racial and Ethnic Preferences in Undergraduate Admission at the University of Michigan,

Center for Equal Opportunity (October 17, 2006), available at

http://www.ceousa.org/content/blogcategory/78/100/. See also Fisher v. University of Texas, 645 F. Supp. 2d

587 (W.D. Tex. 2009).

89 Russell K. Nieli, The Changing Shape of the River: Affirmative Action and Recent Social Science Research,

17 Academic Questions 7 (2004).

Commissioner Statements and Rebuttals 89
scores are substantially higher, exceeding those of African-Americans by

about 200 points or more. Not surprisingly, in this kind of competitive

situation, African-Americans get relatively low grades. It is a fact that in

virtually all selective schools (colleges, law schools, medical schools, etc.)

where racial preferences in admission is practiced, the majority of AfricanAmerican students end up in the lower quarter of the class....

African-American students at the elite schools (the liberal arts colleges

and the Ivy League) get lower grades than students with similar levels of

academic preparation (as measured by SAT scores) than AfricanAmerican students at the nonelite schools (state universities and HBCUs).

Lower grades lead to lower levels of academic self-confidence, which in

turn influence the extent to which African-American students will

persist with a freshman interest in academia as a career. AfricanAmerican students at elite schools are significantly less likely to persist

with an interest in academia than are their counterparts at nonelite

schools.

90

To say that the Mellon Foundation was not happy with the conclusions of its grant recipients

would be an understatement. Soon after publication, the Chronicle of Higher Education

reported that the foundation was “trying to distance itself” from the book’s findings.91 Unlike

similar projects with Mellon funding, this one did not receive a publicity push from the

foundation.

Dr. Cole told the Chronicle that there was “no chance” that he would receive money again

from the Mellon Foundation. “And I don’t care,” he said. “I was trained at a time before

social science became so politicized.” “I believe that social science should be objective and

value-free, and you should design a study to answer a question and whatever the answer is,

that's what it is.”92

A year after Cole & Barber’s research became public, a second study on the science and

engineering mismatch issue was published. University of Virginia psychologists Frederick L

Smyth and John J. McArdle used a very different methodology and a different database from

those of Elliott and his co-authors. But they reported findings that “are consistent” with the

earlier article’s conclusion that “race-sensitive admissions, while increasing access to elite

colleges, was inadvertently causing disproportionate loss of talented underrepresented

minority students from science majors.”93

90 Stephen Cole & Elinor Barber, Increasing Faculty Diversity: The Occupational Choices of High Achieving

Minority Students 124, 212 (2003)(citations omitted)(emphasis supplied).

91 Robin Wilson, The Unintended Consequences of Affirmative Action, The Chronicle of Higher Education 10

(January 31, 2003).

92 Id. 93 Smyth & McArdle, supra n. 19, at 373.

90 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Indeed, Smyth & McArdle went further. They developed a model that attempts to measure

how many more minority students would have succeeded in the goal of a science or

engineering degree if colleges and universities had employed race neutral admissions criteria.

They wrote:

“According to our model ..., if all the [Science-Mathematics-Engineering]-

intending underrepresented minority students had enrolled in similarly

functioning colleges where their high school grades and math test scores

averaged at the institutional means among [Science-MathematicsEngineering] intenders, 72 more of the women and 62 more of the men would

be predicted to persist in [Science-Mathematics-Engineering] (45 percent and

35 percent increases, respectively).”94

Smyth & McArdle’s recommendation was very clear: “Admission officials are advised to carefully

consider the relative academic preparedness of science-interested students, and such students

choosing among colleges are advised to compare their academic qualifications to those of

successful science students at each institution.” Again, few college or university administrators

were listening.

The latest contribution to the literature on mismatch in science and engineering is Do Credential

Gaps in College Reduce the Number of Minority Science Graduates?95 Using a number of

sophisticated methodologies, Sander & Bolus arrive at conclusions like those of Smyth & McArdle

and the Elliott team.

Sander & Bolus studied data obtained from the multi-campus University of California. All

campuses of the University of California are quite selective. But some are more selective

than others. The flagship campus at Berkeley is highly selective as are the UCLA campus

and the more science-oriented UC-San Diego. At the other end of the spectrum, the campuses

at Riverside and Santa Cruz are easier to gain admittance to, but nonetheless hardly “easy.”

Employing what they call the “distance method,” Smyth & Bolus measured the distance

between each student’s entering academic index and the median academic index of all

science and engineering-interested students at that campus. This allowed the authors not just

to compare students with equal academic indices attending different University of California

campuses, but also to make comparisons based on the magnitude of mismatch. Since the UC

campuses differ in their median academic index, students with equal academic indices but

attending different campuses will differ in their level of mismatch.96

They found that students who are “mismatched” at one University of California campus are

at a greater risk of failing to attain their initial goal of a science or engineering degree than

otherwise identically-credentialed students attending a less selective campus of that same

94 Id. at 373. 95 Sander & Bolus, supra n. 13. 96 Sander & Bolus, supra n. 13, at 14-20.

Commissioner Statements and Rebuttals 91
university at which they were not mismatched. And the greater the mismatch, the greater the

problem.

Not satisfied with confining their analysis to the “distance method,” Sander & Bolus also

employed what they dubbed the “first choice/second choice” method. This approach involves

looking at pairs of students who were admitted to two different UC campuses, one more elite

and the other less elite. In each pair, one student chose to attend the more elite school and the

other the less elite. The results were the same: Mismatched students are at a disadvantage in

science and engineering.97

“Minority attrition in science is a very real problem, and the evidence in this paper suggests

that ‘negative mismatch’ probably plays a role in it,” they wrote. The approaches they took

yielded consistent results: “[S]tudents with credentials more than one standard deviation

below their science peers at college are about half as likely to end up with science bachelor

degrees, compared with similar students attending schools where their credentials are much

closer to, or above, the mean credentials of their peers.”98

D. Conclusion.

Decades ago, well-meaning administrators at selective college and universities resolved to

“do the right thing” by extending preferential treatment to underrepresented minorities in

admissions. One of the consequences of that policy has been systematically low college

grades for the supposed beneficiaries of that preferential treatment.99 No, it doesn’t apply to

all such students, but it is nevertheless a widespread phenomenon. And the reason is simple:

While some students will outperform their entering academic credentials, just as some

students will underperform theirs, most students will perform in the range that their entering

credentials predict.

No serious supporter of affirmative action denies this. William G. Bowen and Derek Bok,

authors of The Shape of the River: Long-Term Consequences of Considering Race in

College and University Admissions and long-time advocates of race-based admissions

policies, candidly admit that the credentials gap has serious consequences: “College grades

[for affirmative action beneficiaries] present a ... sobering picture,” they wrote. “The grades

97 Sander & Bolus, supra n. 13, at 20-23. 98 Sander & Bolus, supra n. 13, at 23-24. 99 The figures for law schools grades are available and particularly instructive: In elite law schools, 51.6 percent

of African-American law students have first-year GPAs in the bottom 10 percent of their class as opposed to

only 5.6 percent of white students. Nearly identical gaps exist at law schools at all levels (with the exception of

historically minority schools). At mid-range public schools, the median African-American student’s first-year

grades corresponded to the 5th percentile among white students. For mid-range private schools it was 7th. With

disappointingly few exceptions, African-American students were grouped towards the bottom of their class.

Moreover, contrary to popular belief, the gap in grades did not close as students continued through law school.

Instead, by graduation, it had gotten wider. Richard Sander, A Systemic Analysis of Affirmative Action in

American Law Schools, 57 Stan. L. Rev. 367, 427-36, Tables 5.1, 5.3 & 5.4 (2004). I am not aware of anyone

who disputes these figures, and indeed some critics of Sander’s work appear to have conceded their accuracy.

See Ian Ayres & Richard Brooks, Does Affirmative Action Reduce the Number of Black Lawyers?, 57 Stan. L.

Rev. 1807, 1807 (2005) (“Richard Sander’s study of affirmative action at U.S. law schools highlights a real and

serious problem: the average black law student’s grades are startlingly low”).

92 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
earned by African-American students at the [schools we studied] often reflect their struggles

to succeed academically in highly competitive academic settings.”100

The long-term social and educational consequences of decades of race-based admissions

policies and the artificially low grades for minorities those policies produce are only now

beginning to be studied. The evidence examined by the Commission on Civil Rights focuses

only on the effects on science and engineering majors. It suggests that, as a result of racebased admissions policies, we now have fewer, not more, physicians, dentists, engineers,

scientists and other science-oriented professionals than we would have had under a policy of

color-blindness.

While there are still a few unanswered questions, it is time for students to be advised of the

issue and allowed to make their own decision about their future. Indeed, it is long past time.

If higher education were held to the same standards of consumer disclosure as other

businesses–from securities brokerage houses to children’s toy manufacturers–disclosure

would have come long ago.

Statement of Commissioner Ashley L. Taylor, Jr.

It is my sincere hope that readers of this report picked up on a significant yet subtle message

in the second paragraph of the Executive Summary clarifying that this topic was limited to

the acceptance of minority students to very rigorous academic programs at elite, selective

institutions where the institution is very unlikely to provide any remedial assistance to

overcome K-12 academic deficiencies. This report is not intended to address the admissions

or success of all minority students who pursue a science, technology engineering or math

(STEM) course of study at all universities. It is a narrow look at the fate of the students who

find themselves selected by an institution into a course of study for which they are

underprepared or have little support.

The STEM disciplines are difficult for all students, but especially for students whose K-12

experience, both in the school and at home, left them lacking critical academic skills or

critical study skills. Unlike the humanities, arts, literature, even business courses of study, the

STEM disciplines build quickly from one level to the next leaving little time or room to play

“catch up” for a student who starts the program at a disadvantage. Unfortunately, there

remains a persistent gap between non-Asian minorities and whites in K-12 preparation

insofar as it relates to the profile of students admitted to elite institutions. It is that small but

critically important high performing minority slice of the student population which needs

information that can assist them in choosing the right college to attain their future goal.

I particularly support the first two recommendations of this report from a consumer

protection standpoint. Minority students who are applying to or being recruited by elite

institutions for STEM programs need to know certain fundamental realities. There is a

100 William G. Bowen & Derek Bok, The Shape of the River: Long-Term Consequences of Considering Race in

College and University Admissions 72 (1998).

Commissioner Statements and Rebuttals 93
delicate balance between full disclosure and outright discouragement of students’ ambitions.

But, there is a higher price paid by the student (and the student’s family) who drops out of a

STEM program than is paid by the institution, and for that reason I prefer to err on the side of

full disclosure.

That said, I believe that every student should be viewed as an individual. We should never

place people in typecast such that we eliminate their opportunity to expand and excel.

Students should be given every opportunity to do so, and we shouldn't make assumptions

about any individual. That is the beauty of our country -- we don't do that. We don't have

scripts for people depending on what class of society they come from. It is also important,

however, that the student be made aware of the facts. Those facts could be brutal, those facts

could be demoralizing and I understand the reluctance and hesitation of presenting those

facts to an 18 year-old young adult who may not have the capacity to properly process and

assimilate that information.

The schools have a duty to provide the support for every student they admit. Unfortunately, I

believe that the schools focus a lot more on admissions and matriculation and not enough on

graduation and success upon graduation. When the school doesn't uphold its end of the

bargain, students doesn't know how much force they are going to have to apply to the

situation or how much harder they are going to have to work than the person sitting beside

them. I believe that the students we are talking about in this report would apply that pressure

if they knew it was needed.

In life, the only way you can know how much pressure to apply to a situation is if you know

what you are up against. I am very concerned that some minority students are walking into

certain academic environments where the school fails to provide that support naturally. To

those students who are in those difficult situations and are aware of the uphill climb, I want

to encourage them. I want them to know there are people and resources that can help them if

they seek it.

On a final note, I have intentionally elected not to use the term “mismatch” which was

presented during the briefing and is used in the report. The word, in my view, carries

connotations which may be easily misconstrued.

Dissent of Commissioners Michael Yaki and Arlan D. Melendez

We strongly dissent from this Report and most of its Findings and Recommendations for

several reasons. Specifically, we dissent from: 1) Part A; 2) Findings 2, 3, 4, 5, 6, and 7; and

3) Recommendations 1, 2, 3, and 4. Our principal objection to this Briefing and Report is that

they were fundamentally not about encouraging minorities to pursue careers in STEM fields.

Rather, the major focus of the briefing and report was to promote Rogers Elliott, Richard

Sander and their “mismatch” theory.

94 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
As was noted at the Briefing Hearing, the panel was unbalanced and stacked in favor of

“mismatch” proponents.101 Even Mr. Elliott conceded that his comments were substantially

similar to those of Mr. Sander.102 In addition to being mostly a reaffirmation of Mr. Sander’s

conclusions, Mr. Elliott’s testimony was based on his paper which was already well over a

decade old by the time of our Briefing Hearing.

Mr. Sander’s efforts to promote the theory of “mismatch” with regard to law school and the

legal profession103 have been soundly debunked in a sustained manner.104 Mr. Sander’s

attempts to address his critics and salvage his initial claims105 have resulted only in further

critiques that have supported the initial critiques and have pointed out that Sander’s selfdefense has resulted in self-undermining.106 Perhaps in response to the discrediting of his

initial claims concerning the effect of “mismatch,” Sander himself has avoided using the term

“mismatch” in his most recent work.107

The Report’s recommendations are largely premised on claims regarding the effect of socalled “mismatch.” This effect has been exaggerated by both Elliot/Sander and their admirers

on the Commission.108 We are concerned that the recommendations, grounded as they are in

these out-sized claims, would have the effect of discouraging minorities from pursuing

careers in STEM fields. This outcome would be diametrically opposed to the stated purpose

of this report.

101 United States Commission on Civil Rights, STEM Briefing Transcript, p. 146 (Commissioner Yaki

speaking).

102 Id. p. 34. 103 Richard H. Sander, A Systemic Analysis of Affirmative Action in American Law Schools, 57 STAN. L. REV.

367 (2004).

104 See, e.g., Ian Ayers & Richard Brooks, Does Affirmative Action Reduce the Number of Black Lawyers?, 57

STAN. L. REV. 1807 (2005); David B. Wilkins, A Systemic Response to Systemic Disadvantage: A Response to

Sander, 57 Stan. L. Rev. 1915 (2005); Daniel E. Ho, Scholarship Comment, Why Affirmative Action Does Not

Cause Black Students To Fail the Bar, 114 YALE L.J. 1997 (2005). 105 Richard H. Sander, A Reply to Critics, 57 STAN. L. REV. 1964 (2005); Richard H. Sander, Mismeasuring the

Mismatch: A Response to Ho, 114 YALE L. REV. 2005 (2005). 106 See, e.g., David L. Chambers, Timothy T. Clydesdale, William Kidder & Richard Lempert, The Real Impact

of Eliminating Affirmative Action in American Law Schools: An Empirical Critique of Richard Sander's Study,

MICH.L&ECON WORKING PAPER NO. 05-007 (2005), available at

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=730506##; David L. Chambers, Timothy T. Clydesdale,

William Kidder & Richard Lempert, Affirmative Action in American Law Schools: A Critical Response to

Richard Sander's "A Reply to Critics", MICH.L&ECON WORKING PAPER NO. 06-001, available at

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=886382; Katherine Y. Barnes, Is Affirmative Action

Responsible for the Achievement Gap Between Black and White Law Students?, 101 NW U. L.REV. 1759

(2007).

107 Richard H. Sander & Jane Yakowitz, The Secret of My Success: How Status, Prestige and School

Performance Shape Legal Careers, (2010), available at

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1640058.

108 Admittedly, the exact nature and extent of this “mismatch” effect has been obscured by resort to vague

language in the recommendations, such as “large deficit.” It should be noted that initial approval of this report’s

recommendations was scuttled when a majority of Commissioners were unwilling to endorse this imprecise

language. See USCCR Business Meeting Transcript June 11, 2010, pp. 27-34.

Commissioner Statements and Rebuttals 95
Additionally, we object to the non-deliberative manner by which the Findings and

Recommendations were drafted and adopted. As has been become the norm with the

Commission, Commissioner-drafted alternatives to staff-issued findings and

recommendations are only being provided to all Commissioners less than a day before votes

are scheduled on the findings and recommendations. In some cases, alternate findings and

recommendations have been issued the night before a Commission meeting, only to be

superseded by even newer drafts issued the morning of a meeting or during the meeting

itself.

Joint Rebuttal of Commissioners Gail Heriot, Peter Kirsanow and

Todd Gaziano

Commissioners Yaki and Melendez take the position that the 1996 article by Dartmouth

College psychology professor Rogers Elliott and his co-authors is “over a decade old” and

hence in their view too old to be valuable.109 Perhaps they regard the 2009 article by UCLA

law professor Richard Sander and UCLA Medical School senior statistician Roger Bolus as

tainted because it is somehow too new.110 But, if so, that would still leave the 2004 article by

University of Virginia psychology professors Frederick L. Smyth and John J. McArdle.111

Not all these empirical studies can be dismissed so casually.

All three reach the same conclusion: Mismatch likely puts affirmative action beneficiaries

who plan to major in science or engineering at special disadvantage. More specifically, all

three agree that a student whose entering credentials put him towards the bottom of his

college class is less likely to follow through with plans to major in science or engineering

than a student with the same entering credentials attending a less elite school where those

credentials put him in the middle or towards the top of the class.112

109 Rogers Elliott, A. Christopher Strenta, Russell Adair, Michael Matier & Jannah Scott, The Role of Ethnicity

in Choosing and Leaving Science in Highly Selective Institutions, 37 Res. Higher Ed. 681 (1996).

110 Richard Sander & Roger Bolus, Do Credentials Gaps in College Reduce the Number of Minority Science

Graduates?, Working Paper (Draft July 2009).

111 Frederick L. Smyth & John McArdle, Ethnic and Gender Differences in Science Graduation at Selective

Colleges with Implications for Admission Policy and College Choice, 45 Res. Higher Ed. 353 (2004).

112 It should be noted that the work of these three investigative teams does not come out of nowhere. It is

consistent with a long history of research that dates back to the 1960s. That literature includes the work of

Elinor Barber and Stephen Cole, which found that affirmative action beneficiaries at elite schools are less likely

than similarly-credentialed minority students attending less elite schools to desire to become college professors.

See Elinor Barber & Stephen Cole, Increasing Faculty Diversity: The Occupational Choices of High Achieving

Minority Students (2003). It also includes a wealth of literature like James A. Davis’s The Campus as A Frog

Pond: An Application of the Theory of Relative Deprivation to Career Decisions of College Men, which does

not deal with race-conscious admissions practices directly, but which nevertheless sheds light on the processes

at work at schools where those practices are employed. Davis found that, for better or worse, among the college

students he studied, students who get good grades at less competitive schools will think more highly of their

own academic skills than otherwise identical students who attend more competitive schools and thus earn lower

grades. He further found that good self-opinion influences career choices. James A. Davis, The Campus as a

Frog Pond: An Application of the Theory of Relative Deprivation to Career Decisions of College Men, 72 Am.

J. Socio. 17, 30-31 (1966)(“[T]hese ideas ... challenge the notion that getting into the ‘best possible’ school is

the most efficient route to occupational mobility. Counselors and parents might well consider the drawbacks as

96 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Is it possible that Drs. Elliott, Strenta, Adair, Matier, Scott, Smyth, McArdle, Sander, and

Bolus are nevertheless incorrect? Of course it’s possible. That is why more research would

be useful. At this point, however, the evidence is going strongly in favor of their conclusions.

And that is important to recognize.

The Commission has nevertheless taken a cautious approach. It is not calling upon Congress

or state legislatures to prohibit racially-preferential admissions policies for students who

intend to major in science or engineering. Nor is it calling on colleges and universities to

abandon racial preferences altogether, at least not in this report. The Commission’s

recommendation is modest. What we are asking is that college applicants be made aware of

the potential for a mismatch effect. Students should be given the facts, so that they, in

consultation with their parents, teachers and other advisors, can decide for themselves how to

proceed.113

It is difficult to understand why Commissioners Yaki and Melendez object to disclosure.

Next to homeownership, a college education is typically the largest investment an American

makes during his or her lifetime. The law requires that manufacturers of breakfast cereals

inform consumers of the ingredients and nutritional content of their products as well as warn

of any known health hazards associated with them. Here we are simply calling for

disclosures by the institutions themselves. Is the value of a college degree less important than

corn flakes?

The dissenters could argue that the Commission should wait until all the evidence is in before

they make any recommendation, even a recommendation of disclosure.114 But in issues of

well as the advantages of sending a boy to a ‘fine’ college, if, when doing so, it is fairly certain he will end up in

the bottom ranks of his graduating class.”). See also Marjorie Seaton, Herbert W. Marsh & Rhona G. Craven,

Big-Fish-Little-Pond Effect: Generalizability and Moderation: Two Sides of the Same Coin, 47 Am. Educ. Res.

J. 390 (2010); Herbert W. Marsh, Ulrich Trautwein, Oliver Ludke, Jurgen Baumert & Olaf Koller, The BigFish-Little-Pond Effect: Persistent Negative Effects of Selective High Schools on Self-Concept After

Graduation, 44 Am. Educ. Res. J. 631 (2007); Herbert W. Marsh, Chit-Kwong Kong & Kit-Tai Hau,

Longitudinal Multilevel Models of the Big Fish Little Pond Effect on Academic Self-Concept:

Counterbalancing Contrast and Reflected Glory Effects in Hong Kong Schools, 78 J. Personality & Soc. Psych.

337 (2000).

113 Commissioners Yaki and Melendez are less cautious. Three years ago, in connection with the Commission’s

Report on Affirmative Action in Law Schools, they were utterly disdainful of the mismatch theory and quite

certain that the issue was the invention of sinister forces. They asserted “[t]he proof that affirmative action

works in law schools is overwhelming” and that “the success of the policy” is “unmistakable.” See U.S.

Commission on Civil Rights, Briefing Report: Affirmative Action in Law Schools, Joint Dissent of

Commissioner Arlan D. Melendez and Commissioner Michael Yaki at 188 (2007). So certain were they that

mismatch was not an issue in law school or anywhere else that they dissented even from the Commission’s

recommendation that more research be conducted—hardly the cautious course of action. Now they argue with

equal certainty that “[t]his effect has been exaggerated” in the science and engineering context. This statement

is curious given that the current evidence in the science and engineering context points in only one direction. In

the future, it could always turn out that researchers were mistaken about the mismatch effect. Or it could turn

out that the effect was larger or smaller than they now believe it to be. But at present there is no basis upon

which to conclude that it “has been exaggerated.” To baldly assert otherwise is to substitute swaggering

certitude for rational analysis.

114 As far as I know, no one has ever made such an argument in the context of products liability. In that area, for

example, a manufacturer can be held liable if it fails to warn of a “foreseeable” risk. See Restatement (Third) of

Commissioner Statements and Rebuttals 97
public policy, the evidence is never all in. Decisions must be made based on the available

evidence, not the evidence that would exist in a perfect world. At present, the evidence that

students intending to major in science and engineering can be worse off if they are

mismatched is fairly strong—much stronger than the evidence that underlies most public

policy decisions. Indeed, it is considerably stronger than the evidence that raciallypreferential admissions policies benefit minority students in any context, science-related or

not. 115

Torts: Products Liability section 2. To exempt manufacturers from liability in cases in which the evidence of

risk was not yet utterly conclusive would be an extraordinary (and in my view inappropriate) change of policy.

A large proportion of the warnings on pharmaceutical products are for risks that have not yet been conclusively

proven to exist. Science, like life, is full of uncertainties. In this case, the risk is not only foreseeable, it has

actually been foreseen by a number of commentators of which Drs. Elliott, Strenta, Adair, Matier, Scott, Smyth,

McArdle, Sander, and Bolus are just a few. Moreover, it is not simply foreseen, it has been tested empirically

and strong evidence of its existence has been found in three independent studies.

115 Interestingly, rather than discuss that evidence or indeed anything directly related to the current report, the

dissenting commissioners prefer to discuss an earlier Commission report—one in which the issue was the effect

of affirmative action in law schools rather than its effect on science and engineering students at the

undergraduate level. See United States Commission on Civil Rights, Report on Affirmative Action in Law

Schools (2007). In that report, the Commission examined research by Dr. Richard Sander that appears to show

that mismatched law students are less likely to complete law school and pass the bar than are identicallycredentialed students who attend law schools at which they are not mismatched. See Richard Sander, A

Systemic Analysis of Affirmative Action in American Law Schools, 57 Stan. L. Rev. 367 (2004).

Commissioners Yaki and Melendez take the position that this research has been “soundly debunked in a

sustained manner.” I can only imagine that they have not read the articles they cite. For the most part, I will rely

on my analysis in my Commissioner’s Statement to the Report on Affirmative Action in Law Schools Report,

since I have already dealt with most of the criticisms they cite. See also Gail Heriot, Affirmative Action in Law

Schools, 17 J. Contemp. Legal Issues 237 (2008)(another version of same essay).

A few points should nevertheless be made here either because they are new or in need of repetition to

give the reader of this report a taste of the evidence examined in the earlier report:

1. The evidence behind Sander’s conclusions in his law school study is not yet conclusive. Nor does

the Commission report claim that it is. More research needs to be done and that is a significant part of what the

Commission recommended. Some of the dissenting commissioners’ citations, however, are quite misplaced. For

example, the article by David Wilkins does not dispute Sander’s conclusion that there are today fewer, rather

than more, African-American attorneys as a result of racially preferential admissions policies. Instead, Wilkins

argues that even assuming mismatched African-Americans leave law school or never pass the bar at higher rates

than they would under race-neutral admissions policies, those who do make it get the benefit of having the

opportunity to network with more elite law students. David B. Wilkins, A Systemic Response to Systemic

Disadvantage: A Response to Sander, 57 Stan. L. Rev. 1915 (2005).

2. The dissenting commissioners cite Katherine Y. Barnes, Is Affirmative Action Responsible for the

Achievement Gap Between Black and White Students?, 101 Nw. U. L. Rev. 1759 (2007), as part of a second

wave of criticism of the Sander study. Scholars, however, have been unable to replicate Dr. Barnes’ results. See

Doug Williams, Does Affirmative Action Create Educational Mismatches in Law School, Draft at 9 (January,

2010)(presented at the 20th Annual Conference of the American Law and Economics Association). Efforts to do

so by Williams “produce[d] results generally consistent with the mismatch hypothesis.” Id. Indeed, Dr. Barnes’

own efforts to replicate her original findings have produced very different results from those in the original

article—results that provide some support for Sander. For example, in her original article she reported that

students in the 5th percentile nationally for entering academic credentials passed the bar after attending a

historically black law school at a rate of only 12.9%. Her revised is 77.9%. In a correction and update that has

98 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
Commissioners Yaki and Melendez argue that the panel at the briefing was “stacked in favor

of ‘mismatch’ proponents.”116 Since no researcher has taken a position contrary to that of our

witnesses, Dr. Elliott and Dr. Sander, on the issue of mismatch in science and engineering, it

is difficult to understand who Commissioner Yaki believes should have been called as a

witness. The Commission cannot call witnesses that do not exist.

been submitted to the Northwestern University Law Review, she reports that her new results do indeed indicate

that HBCUs “boost graduation and bar passage rates for students with low credentials”—although she is not yet

willing to concede that the total pattern of results supports mismatch. Katherine Y. Barnes, Correction and

Update to Is Affirmative Action Responsible For The Achievement Gap Between Black And White Law

Students?, forthcoming in the Northwestern University Law Review. Dr. Barnes agrees with the Commission

that more research is necessary and that the Bar Passage Study database is not adequate for that research.

3. The Williams article provides general support for Sander. “Although the results here are not

conclusive,” he writes, “I find much more evidence for mismatch effects than previous research, which has been

dismissive of the mismatch hypothesis.” Significantly, Williams goes on to explain that the Bar Passage Study,

from which the data for Sander’s and his studies were obtained, does not categorize law schools by academic

tier. Consequently, Williams points out, it is difficult to find evidence of mismatch even if a serious mismatch

problem really is there. Williams urges that further studies be conducted on bar passage data from large states

like California, Florida or Texas so that the mismatch theory in law schools can be confirmed or refuted

Williams at 34. Williams’ recommendation is thus in accord with the Commission’s.

4. Surely all fair-minded scholars would agree that obtaining data with which to confirm or refute

Sander’s conclusions concerning law schools is worthwhile and important. But if one were to expect those who

critiqued the original study uniformly to be fair-minded scholars, one would be disappointed. William Kidder,

one of the team of David Chambers, Timothy Clydesdale, William Kidder & Richard Lempert, whose critique

of the Sander study is cited by Commissioners Yaki and Melendez in their Footnote 6, wrote to the State Bar of

California’s Committee of Bar Examiners urging that the committee deny Sander and his co-authors access to

the California Bar Examination data—probably the richest and best source available upon which to test the

hypothesis further. Among other things, Kidder argue that disclosure of the data “risks stigmatizing AfricanAmerican attorneys regardless of how successful they may be in legal practice.” Sander, of course, had not

requested names or any information that would allow him to identify particular persons. At the time he coauthored the article cited by the dissenters, Kidder was employed as a researcher with the Equal Justice Society,

an organization that describes its mission as to “marshal our forces to defeat the right wing assault on social and

racial justice.” More recently, he has been employed as an administrative staff member at the University of

California. See United States Commission on Civil Rights, Report on Affirmative Action in Law Schools,

Statement of Commissioner Gail Heriot at 148 (2007). Similarly, David Chambers was the former president of

the Society of American Law Teachers, which also wrote a letter to the State Bar of California opposing

scholarly access to the data. That letter raised the specter of litigation if the data is disclosed. Id.

5. Commissioners Yaki and Melendez seem to suggest that there is something strange about the fact

that the word “mismatch” does not appear in Dr. Sander’s most recent article. Richard H. Sander & Jane

Yakowitz, The Secret of My Success: How Status, Prestige and School Performance Shape Legal Careers, Draft

(August 9, 2010), available athttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=1640058. The reason for this

choice of words is easy to explain: The paper isn’t about mismatch, but rather about how law school grades

have more impact on future success in the legal profession than the prestige of the law school a lawyer attended

(controlling for other factors like LSAT). The study did not make a distinction between students who were

mismatched and those who were not. The fact that the word “mismatch” was not used is thus no more

significant than the absence of the word “elephant” from the article.

116 Dissent Statement of Yaki and Melendez at 1; Transcript at 146.

Commissioner Statements and Rebuttals 99
Nonetheless, extraordinary efforts were made to call either (1) any witness who had

expressed doubts about the problem of mismatch in any context or (2) any witness who had

expressed strong support for race-based admissions as a means of increasing the number of

minority members in science & engineering.117 Among those contacted were: Gibor Basri,

Vice Chancellor for Equity and Inclusion at the University of California at Berkeley; Ted

Greenwood, Program Director at the Alfred P. Sloan Foundation; Freeman A. Hrabowski III,

President of the University of Maryland (Baltimore County); Christopher Jencks, Professor

of Social Policy at Harvard University; Paul Joskow, President of the Alfred P. Sloan

Foundation; Thomas Kane, Professor of Education at Harvard University; William Kidder,

Special Assistant to the Vice President for Student Affairs, University of California; Tom

Loveless, Senior Fellow in Governance Studies at the Brookings Institute, Tom Luce, CEO

of the National Science and Math Initiative; and Kenneth Maton, Professor of Psychology at

the University of Maryland (Baltimore County).

Commission staff members also invited Ann Mullen, Associate Professor of Sociology at the

University of Toronto; Meredith Phillips, Associate Professor of Public Policy & Sociology

at UCLA, Jesse Rothstein, Associate Professor of Public Policy at Princeton University;

Marta Tienda, Professor of Sociology & Public Affairs at Princeton University; Philip Uri

Treisman, Professor of Mathematics & Public Affairs at the University of Texas; and Sarah

Turner, Professor of Economics & Education at the University of Virginia.118

All declined to testify. Of course, if Commissioners Yaki and Melendez could have

suggested additional potential witnesses. Indeed, they were asked to by the staff--in writing

117 My own view is that it is naïve to expect the Commission staff to please all Commissioners as to “balance”

when they invite experts to testify at a briefing. No matter how well-balanced the panel is or is not, someone

will complain. Any procedure that places the responsibility for balance on the Commission staff’s shoulders is

thus begging for controversy. Instead, that responsibility should be on the Commissioners, each one having the

right to call an expert witness to a briefing (if he or she feels the panel is unbalanced). That way if a panel does

indeed fail to reflect the spectrum of responsible opinion on an issue, the Commissioners have no one to blame

but themselves.

Sadly, it has been observed by the Commission staff that when witnesses generally congenial to

Commission Yaki’s point of view agree to testify, they sometimes mysteriously withdraw shortly after their

identities are made available to the members of the Commission. Commissioner Yaki can then berate the staff

for failing to properly balance the panel and complain that the Commission’s report is somehow illegitimate.

Again, the solution is to alter the Commission’s procedures. If the Commissioners were responsible for

identifying and securing witnesses, there would be no occasion for concerns of this type.

It is well worth noting that Congress does not charge some “neutral” staff with the responsibility for

balancing opinion at Congressional hearings. Instead, the majority chooses a number of witnesses and the

minority is permitted to choose a somewhat smaller number. Under the circumstances, neither party can

complain about whether the full spectrum of opinion was reflected in the panel. Instead, disagreements are

limited to the more mundane question of whether the minority has been accorded the right to call an adequate

number of witnesses. I would amend our procedures to conform to Congressional practice. I believe this would

eliminate some of the controversy over panel balance that periodically rears its head at our briefings.

118 Also contacted for advice on speakers was Peter Henderson, Director on the Board of Higher Education and

Workforce of the National Academy of Sciences and Sigal Alon, Senior Lecturer in the Department of

Sociology at Tel Aviv University.

100 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers
and more than once. But they did not respond with recommendations—even though there is

no question that any such recommendations would have been followed.

The peculiar thing about the complaint of the dissenting commissioners is that ultimately the

panel was fairly well-balanced. Commission staff members were able to identify and secure

the testimony of a qualified witness, Rice University Professor of Mathematics Richard

Tapia, a long-time forceful advocate of increasing the number of minority students in science

and engineering at highly competitive institutions.119 Still, Commissioner Yaki at least

appeared disappointed rather than pleased and complained of lack of balance anyway. His

reaction when Fisk University President Hazel O’Leary (former Clinton Administration

Secretary of Energy) abruptly cancelled her testimony on the eve of the briefing (not long

after the identities of the witnesses were announced to the Commissioners) was equally if not

more telling: Commissioner Yaki declared that he was “kind of glad she did” and implied

that the Commission’s calling of President O’Leary to testify on the successes of HBCUs in

graduating African-American science and engineering majors was somehow inappropriate.120

Finally, the objections of Commissioners Yaki & Melendez to what they regard as the “nondeliberative manner by which Findings and Recommendations were drafted” are surprising.

In fact, what they are objecting to is the deliberative character of our negotiations rather than

their non-deliberative character. The Commission members who make up the majority that

adopted these findings and recommendations take them seriously. We are not potted plants.

We do not show up once a month to sign on the dotted line where staff members tell us to,

and then collect a stipend and a free lunch. We sometimes have been negotiating with each

other over the language of the findings and recommendations in a report long prior to their

adoption. But given that all of us have full-time jobs and most of us must travel distances to

get to our meetings, these negotiations take a while. Sometimes changes are still being

suggested both shortly before a meeting and during the meeting. If Commissioners Yaki and

Melendez would like to take part in those negotiations, they would certainly be welcome to,

but thus far they have shown no desire to do so. To the contrary, Commissioner Yaki has

declared the opposite intention in an open meeting, “I will not be a party,” he said to

Chairman Reynolds, “to contributing to your ability to get things done.”121 In any event, the

Chairman has always been willing to postpone consideration of findings and

recommendations when Commissioners Yaki or Melendez have requested such a delay, so it

is difficult to understand what motivates their argument.

Part of the reason Commission members must spend a good deal of time hammering out

findings and recommendations lies in the Commission’s ill-considered procedures. The staff

119 According to the magazine Science, Dr. Tapia’s graduate program in mathematics at Rice University has

graduated far greater than the average number of underrepresented minorities than is the national average,

causing the National Research Council to cite his program’s success in one of its reports. Paul Selvin, Math

Education: Multiplying the Meager Numbers, 258 Science 1200, 1201 (November 13, 1992).

120 STEM Testimony at 146. 121 Meeting of November 20, 2009, Transcript at 8-9. See Rebuttal Statement of Commissioner Gail Heriot to

Report on Historically Black Colleges and Universities (issued in conjunction with this report) at n.1

(cataloguing occasions upon which Commissioner Yaki has walked out of ordinary business meetings to defeat

a quorum or joined a meeting only when a quorum is already established.)

Commissioner Statements and Rebuttals 101
members who are assigned to write the first draft of them seldom get as much time as I

would like to confer with Commission members about the kinds of recommendations those

Commission members want to make. In part this is a result of poorly-designed internal

procedures, which deliberately isolate them from the Commission. Sometimes staff members

end up making guesses about what the Commission’s majority wants, and sometimes those

guesses turn out to be incorrect. They learn. Ultimately, however, it is for the Commissioners

and not for the staff members to issue the reports. That is what it means to be the

Commissioners instead of the staff. As the statute that chartered the Commission makes

clear, the Commission is made up of the eight Commissioners; it is not made up of the

staff.122 The findings and recommendations of Commission reports must reflect that.

122 See 42 U.S.C. 1975(b): “The Commission shall be composed of eight members.” The subsection then goes

on to describe how members of the Commission will be appointed by the President and Congress. But it is silent

on the subject of staff.

102 Encouraging Minority Students to Pursue Science, Technology, Engineering & Math Careers



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