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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Section 1
Summaries of Convocation Sessions

Each session summary consists of an abstract of the panel and edited third-person transcripts of the speaker comments. The summaries present the views and opinions of the panelists and might not reflect the views of the committee or the National Academies. Slides presented by the panelists may be found on the convocation Web site, http://www7.nationalacademies.org/womeninacademe/Convocation.html.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL 1
COGNITIVE AND BIOLOGICAL CONTRIBUTIONS

   

 Panel Summary

 

 

   

  Gender Differences and Similarities in Abilities
Janet Hyde, Department of Psychology, University of Wisconsin at Madison

 

 

   

  Sexual Dimorphism in the Developing Brain
Jay Giedd, National Institute of Mental Health, National Institutes of Health

 

 

   

  Environment-Genetic Interactions in the Adult Brain: Effects of Stress on Learning
Bruce McEwen, The Rockefeller University

 

 

   

  Biopsychosocial Contributions to Cognitive Performance
Diane F. Halpern, Berger Institute for Work, Family, and Children, Claremont McKenna College

 

 

   

  Selections from the Question and Answer Session
Moderated by committee member Ana Marie Cauce

 

 

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL SUMMARY

The panel considered whether there are differences between males and females in brain development and in average performance on cognitive tasks and whether those differences account for the large discrepancies in male and female representation among academic scientists.

Janet Hyde, of the University of Wisconsin-Madison, proposed the “novel concept of gender similarities” in cognitive abilities, noting that the mathematical, verbal and spatial skills involved in scientific work are all gender-stereotyped. Meta-analyses of 100 studies of math ability involving 3 million persons, including nine state assessments, show that the highly touted and widely reported gender differences in mathematical ability are in fact small or insignificant.

Diane Halpern, of Claremont McKenna College, observed that men and women are in fact both similar and different and “what you see depends on where you look.” The differences or similarities found depend on which tests and measures are used. She also emphasized that nature and nurture form a “false dichotomy,” are not independent variables, and “do not just interact.” The factors are instead “inextricably intertwined” because experience alters the biological underpinnings of behavior, and the resultant biology influences the types of experiences people have. Instead of the old two-part paradigm, she proposed a biopsychosocial conceptualization of the issue and the recognition that even small differences may have large effects over time because small effects accumulate into large ones.

Jay Giedd, of the National Institute of Mental Health, presented data from magnetic resonance imaging (MRI) studies of brain structure and development during adolescence showing both gender differences in the trajectory of brain development and the strong and lifelong influence of experience on the brain. MRI studies show “gray boxes,” not individual neurons, and behavioral interpretations are therefore “speculative.” The sex hormones estrogen and testoster-one are present both in males and females, and play a role in brain development, although hormones are not sole factors driving sex differences in the brain. Male brains show more morphological variance than female brains, but observations are based on group averages and not individuals, and overall, the brains of males and females are more alike than different.

Panelist Bruce McEwen, of Rockefeller University, presented evidence of complex sex differences in nonhuman brain response to stress and of the brain’s high adaptability and plasticity throughout the lifespan. Males and female humans differ in the processes and priorities they use in processing information. Genes, hormones, and experience exert different influences on human males and females, he concluded, but the cognitive differences between men and women appear to involve differing strategies of information processing rather than different “abilities.”

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
GENDER DIFFERENCES AND SIMILARITIES IN ABILITIES

Janet Hyde

Department of Psychology, University of Wisconsin-Madison


Janet Hyde’s presentation emphasized what she called “the novel concept of gender similarities” and focused on mathematical, verbal, and spatial abilities as basic to science ability. Those abilities are “gender stereotyped,” with boys believed to excel on mathematics and spatial tests and girls on verbal measures.1

Hyde described the power of meta-analysis (see Box 1-1) and discussed a particularly large study of gender differences in mathematics performance that pooled the results of 100 studies that tested more than 3 million people and included a wide variety of data sources, such as assessments from nine states. Averaged over all samples of the general population, the d was equal to minus 0.05, “a tiny gender difference.” Another team of investigators obtained very similar results using somewhat different meta-analytic techniques.2

Might there be an increasing gender gap in performance with age? Second, do the mathematics tests tap lower level math computation, or a deeper conceptual understanding of mathematics and complex problem solving, which is needed to do science?

Using meta-analytic methods to investigate these questions, Hyde found that girls are better than boys at computation by a small amount in elementary and middle school. For the deeper understanding of mathematical concepts, she found no gender difference at any age level. Finally, at the highest cognitive level, complex problem-solving, she found no gender difference in elementary school or middle school, but a small difference among high school and college students. Although that difference deserves attention, it is not large.

The important point is that within-gender differences are enormous compared to between-gender differences.

—Janet Hyde

One explanation for the gender difference in problem-solving favoring high-school and college-age males is the difference in patterns of course taking. Girls have been less likely to take optional advanced mathematics classes in high school, although this gender gap has closed in the last five years. Girls now take calculus in high school at the same rate as boys. Nonetheless, they are less likely to take science courses in high school than boys, especially in chemistry and physics. This handicaps girls in pursuing science careers, and it also handicaps

1

For more details, figures, and references, see Janet Hyde’s paper in Section 2.

2

LV Hedges and A Nowell (1995). Sex differences in mental test scores, variability, and numbers of high-scoring individuals. Science 270:364-365.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

BOX 1-1

Meta-Analysis

Hundreds of studies examine gender differences in performance. Rather than conduct an additional study, one can synthesize the existing studies to find an overall outcome.

Meta-analysis refers simply to the application of quantitative or statistical methods to combine evidence from numerous studies. Meta-analysis can tell us, when we aggregate over all the available studies, whether there really is a gender difference in mathematical ability. It can tell us the direction of the difference: do males score higher on average or do females? And it can also tell us the magnitude of any gender difference.

The d statistic, or effect size, is used to measure the gender difference. To obtain d, the mean score of females is subtracted from the mean score of males in a particular study, and the result is divided by the pooled within-gender standard deviation. Essentially, d tells us how far apart the means for males and females are in standardized units. d can have positive or negative values. A positive value means that males score higher, and a negative value means that females score higher. To give a tangible example, the gender difference in throwing distance is + 1.98.

In a meta-analysis, d is computed for each study, and then ds are averaged across all studies. Because meta-analysis aggregates over numerous studies, a meta-analysis typically represents the testing of tens of thousands, sometimes even millions of participants. Thus, the results should be far more reliable than those from any individual study.

How do we know when a d, an effect size, is small or large? The statistician Jacob Cohen provided the guideline that a d of 0.20 is small, 0.50 is moderate, and 0.80 is large.

their performance on standardized mathematics tests, because students experience mathematical problem-solving in physics and chemistry classes.

Concerning gender differences in verbal ability, meta-analysis of 165 studies representing the testing of 1.4 million persons showed superior performance by females but the difference is very small (d = −0.11).3 The question of gender differences in spatial ability, a relevant skill in many fields of science and engineering, is complicated because there are many types of spatial ability and many tests to measure them. With regard to gender differences in three dimensional

3

JS Hyde and MC Linn (1988). Gender differences in verbal ability: A meta-analysis. Psychological Bulletin 104:53-69.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

mental rotation, which is crucial in fields such a engineering,4 two meta-analyses have been conducted. One found a large gender difference favoring males, and the other found a medium gender difference favoring males,5 both more substantial than for mathematical and verbal abilities. That does not mean that girls cannot succeed at engineering; research shows that spatial skills can be trained.6

One major factor in determining mathematics performance is student high school course choice. In investigating what factors influence adolescents’ choice of courses and careers, Eccles found that students value what they think they will learn in a course, and that is heavily influenced by intended career.7 Many occupations in the U.S. are highly gender-segregated. That makes it more likely that girls will not imagine themselves in science or engineering careers and therefore they will not value mathematics or physics courses as much as boys do.

Parents play an important role. Research shows that even in elementary school, parents estimate the math ability of sons to be higher than those of daughters, despite the absence of any gender difference in actual grades or test scores at this point. One particularly impressive longitudinal study found that mothers’ estimates of their 6th grader’s likelihood of mathematics success predicted the child’s actual mathematics career choice at age 25.8

Schools play a third important role on the gender difference in advanced mathematics and science performance. Research shows, for example, that hands-on laboratory experiences in the physical sciences improved the science achievement of girls but not of boys, and helped to close the gender gap in achievement.

Cultural influences at the broadest level also play a role. In a cross-national study of 5th graders’ math performance,9 one could focus on the small difference in performance between girls compared with boys. However, the bigger picture

4

M Hegarty and VK Sims (1994). Individual differences in mental animation during mechanical reasoning. Memory and Cognition 22(4):411-430.

5

MC Linn and AC Petersen (1985). Emergence and characterization of sex differences in spatial ability: A meta-analysis. Child Development 56:1479-1498; D Voyer, S Voyer, and MP Bryden (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological Bulletin 117:250-270.

6

Hyde referred to a study by Sheryl Sorby and her colleagues, who have developed a multi-media software program that improves the spatial performance of students and has improved the retention of women in the engineering major from 47% to 77%. See: N Boersma, A Hamlin, and S Sorby (2005). Work in progress—Impact of a remedial 3-D visualization course on student performance and retention. Presentation at 34th ASEE/IEEE Frontiers in Education Conference, October 20-23, 2004, Savannah, GA. http://fie.engrng.pitt.edu/fie2004/papers/1391.pdf.

7

JS Eccles (1994). Understanding women’s educational and occupational choices: Applying the Eccles et al. model of achievement-related choices. Psychology of Women Quarterly 18:585-610.

8

JE Jacobs and JS Eccles (1992). The influence of parent stereotypes on parent and child ability beliefs in three domains. Journal of Personality and Social Psychology 63(6):932-44.

9

M Lummis and HW Stevenson (1990). Gender differences in beliefs and achievement: A cross-cultural study. Developmental Psychology 26:254-263.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-1 Cross-cultural differences in fifth-grade mathematics performance.

SOURCE: M Lummis and HW Stevenson (1990). Gender differences in beliefs and achievement: A cross-cultural study. Developmental Psychology 26:254-263.

shows that girls in Taiwan and Japan dramatically outperform American boys. Many features probably account for this, among them differences in the way mathematics is taught, in cultural values attached to mathematics, and in different attitudes about the importance of ability vs. effort in producing excellent performance.

Another study looked at the magnitude of the gender difference in mathematics performance in different countries and correlated it with the United Nations standardized measure of gender stratification.10 The correlation between mathematics performance and the percentage of women in the paid workforce was an impressively large −0.55 across nations. Countries with the greatest gender stratification tended to have the largest gender difference favoring males.

All those findings led Hyde to propose the gender similarities hypothesis.11 She subjected 46 relevant meta-analyses to a meta-analysis. The studies spanned a wide range of psychological characteristics, including abilities, communication, aggression, leadership, personality and self-esteem. She found 78% of the gender differences effect sizes were small or close to 0. Psychologically, women and men are more similar than they are different. Large gender differences are found in a few cases, but the big picture is one of gender similarities.

10

DP Baker and DP Jones (1993). Creating gender equality: Cross-national gender stratification and mathematical performance. Sociology of Education 66:91-103.

11

JS Hyde (2005). The gender similarities hypothesis. American Psychologist 60:581-592.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

On the basis of these data, Hyde suggested some policy recommendations: (1) a spatial learning curriculum should be instituted in primary and secondary schools, (2) colleges of engineering should have a spatial skills training program for entering students, (3) four years of math and four years of science should be required in high school or at least for university admission, (4) the mathematics curriculum in many states needs far more emphasis on real problem solving, and (5) teachers and high school guidance counselors need to be educated about the findings on gender similarities in mathematics performance, or teachers will believe the stereotypes about girls’ mathematics inferiority that pervade our culture and those expectations will be conveyed to the students.

SEXUAL DIMORPHISM IN THE DEVELOPING BRAIN

Jay Giedd

National Institute of Mental Health, National Institutes of Health


Jay Giedd began by noting his focus on the adolescent brain. In child psychiatry nearly everything has different prevalences, ages of onset, and symptomatology between boys and girls and nearly every disorder is more common in boys. His studies use MRI, magnetic resonance imaging, which because it does not require radiation can be used in children to perform longitudinal studies.

To the MRI machine, the brain is boxes of gray or white measuring about 1 cubic millimeter. Within each of these boxes are millions of neurons and trillions of synaptic connections. Using much finer resolution microscopic techniques, one can see synapses and connections, but MRI currently cannot do that. MRI pictures and images can be quite colorful, but interpretations are necessarily speculative.

—Jay Giedd

What we call the gray matter consists mostly of the neuronal cell bodies, where the nucleus and the DNA are housed; the antenna-like dendrites reaching for connections to other brain cells; and the terminal branches of the axons, the location of the synapses, and the connections to other brain cells. The white matter is myelin, the insulation material wrapped around the axon that speeds communication between the brain cells.

Giedd and his colleagues performed longitudinal MRI scans of 2,000 subjects. They found that white matter volume increased at least through the fourth decade in women and through the third in men (Figure 1-2). At no time during development did white matter volume decrease.

The white matter has been of interest in the study of sexual brain-structure differences, or sexual dimorphism, because one of the first reports of a brain difference not related to reproduction concerned the corpus callosum, the white

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-2 Longitudinal development of white matter.

SOURCE: JN Giedd, J Blumenthal, NO Jeffries, FX Castellanos, H Liu, A Zijdenbos, T Paus, AC Evans, and JL Rapaport (1999). Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience 2(10):861-863.

matter tract connecting the two brain hemispheres. In over 100 published papers, the results are inconclusive—the corpus callosum of females is bigger than, smaller than, or not different from that of males. The key to understanding these results is in considering developmental windows. At young ages the corpus callosum is sexually dimorphic; between ages 9 and 14 it is not; and then it becomes so again. These changes happen throughout life.

Brain areas have intersecting developmental trajectories. This is a very important concept in how to interpret the findings. Often, the literature will combine data from people across seven or eight decades, and report that average as the difference between male and female brains.

—Jay Giedd

The most robust sex difference is total brain size. From autopsy studies, even when correcting for total body mass, male brains have been found to be about 10% larger than female brains, but bigger isn’t better and size is not related to intelligence. A lot of the literature is really murky on how to account for total brain size difference.

The other part that MRI can see—the gray matter—has a distinct developmental trajectory from that of white matter. Instead of a general linear increase in volume, gray matter has an upside down “U” path in development. Changes in cortical thickness are not due to an increase in the number of neuronal cells, but to an increase in arborization, or the number of branches, twigs, and roots of existing individual neurons. Although both progressive and regressive processes occur throughout life, during childhood there is a net increase in the degree of branch-

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

ing and during adolescence there is a net decrease. Growth reaches a peak in the frontal part of the brain at 11 in girls and 14 years in boys. Pruning then begins: the cells and connections that are used survive and flourish, and those that are not wither and die.

There is a lot of regional variation in the process. Maturation starts in the parts of the brain needed to keep us alive, such as those controlling heart rate and breathing. The next parts of the brain to mature are those involved in processing the five senses, followed by the parts of the brain that link together the primary senses. Then there is a cascade of hierarchies linking the linkings. The final stop is the frontal lobe, which doesn’t reach adult levels until about age 25.

By adulthood, once you correct for the total brain-size differences, the sex differences are quite subtle. But if you look at the path the brains took to get there, the differences are far more robust. It’s the journey, not the destination.

—Jay Giedd

The most variable parts of the brain seem to be those that mature last, and are the least heritable. The structure that we have examined thus far that is the most different between males and females is the cerebellum. Because it is one of the last brain areas to mature, the cerebellum is under the influence of the environment for a long period. Accounting for overall brain size increase, the cerebellum is larger and it reaches adult volume later in males than in females. Overall, male brains have a greater variation in cortical thickness; this is a very robust phenomenon that occurs throughout the brain.

Giedd summarized with two points: First, male and female adolescent brains are much more alike than different; there is enormous overlap. Second, with regard to developmental trajectories, there are more marked sex differences. Male brain structure appears more variable. Whether the variability is biological or social in origin, the data are robust. Work is underway on the effects of sex chromosomes and hormones. In ending, Giedd emphasized that differences are group average differences, and are not to be implied as constraints for individual boys or girls.

ENVIRONMENT-GENETIC INTERACTIONS IN THE ADULT BRAIN: EFFECTS OF STRESS ON LEARNING

Bruce McEwen

The Rockefeller University


Bruce McEwen presented data on sex-based differences in the effects of stress, which have implications for learning. He and his colleagues study brain regions that are involved in memory, emotions, and executive function or deci-

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

sion making. He commented on the translation of animal-model studies to humans, and complemented the discussion on the continuing interaction throughout the life course between genes, hormones, and environment/experience.12

The adult brain is a very adaptable organ, and through our adult life there is a continual functional and structural remodeling.

—Bruce McEwen

McEwen briefly summarized the plasticity literature. When the brain is damaged, there is collateral sprouting and functional reprogramming in many cases. Even without damage, there is continual remodeling of connections with use and disuse, which has been demonstrated for the visual system and also in the motor system in terms of practice effects, such as in playing musical instruments and doing repetitive motor tasks. There are progenitor cells and even some stem cells in the adult brain; and in the dentate gyrus of the hippocampus and the olfactory bulb there is a continuous replacement of nerve cells throughout adult life. There is remodeling of the dendrites—the tree-like structures of neurons— and of synaptic connections in animals undergoing both acute and chronic stress.

Examples from an ongoing study on the prefrontal cortex illustrate the latter point.13 In male rats that have been repeatedly stressed, neuronal dendrites become shorter and less branched and the number of synaptic connections is reduced. The overall reduction is as much as 30%, which has functional implications. However, in the amygdala, an area of the brain that is associated with fear, with aggression and emotional responses, repeated stress of the same kind causes neurons and dendrites to grow and increase their synaptic connectivity.14 That may explain why repeated stress causes animals to become more fearful and more aggressive.

The sex hormones testosterone and estradiol have effects throughout adult life and widespread influences throughout the brain.15 Receptors for both sex hormones are found in most brain areas, meaning that hardly any area of the brain is not influenced by circulating sex hormones. There is also evidence of a direct effect of the X and Y chromosomes on certain aspects of brain development and differentiation.

12

For an overview, see BS McEwen and EN Lasley (2005). The end of sex as we know it. Cerebrum 7(4):65-79.

13

JJ Radley, AB Rocher, M Miller, WG Janssen, C Liston, BS McEwen, and JH Morrison (2005). Repeated stress induces dendritic spine loss in the rat medial prefrontal cortex. Cerebral Cortex 16(3):313-320.

14

A Vyas, S Bernal, and S Chattarji (2003). Effects of chronic stress on dendritic arborization in the central and extended amygdala. Brain Research 965(1):290-294.

15

BS McEwen (1999). The molecular and neuroanatomical basis for estrogen effects in the central nervous system. Journal of Clinical Endocrinology and Metabolism 84(6):1790-1797.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Testosterone and estradiol and receptors for them are present in both males and females. Their effects in the two sexes are subtly different, depending on developmental programming. For example, estrogen affects motor coordination, vulnerability to seizures, aspects of the premenstrual syndrome or pre-menstrual dysphoric disorder, depression, vulnerability to stroke, and the amount of damage from stroke, pain mechanisms, cognitive function, and vulnerability for dementia. Estrogen influences functions both at the level of the cell nucleus through the traditional mechanism, but also through relatively newly discovered cell-surface signaling mechanisms. Similarly broad effects are seen with testosterone and other androgens in males.

There is virtually no function that is not influenced by reproductive hormones.

—Bruce McEwen

These broad effects should be kept in mind when thinking about how the male and female brain, with and without circulating sex hormones, responds to stressful experiences. We know that acute stress generally enhances the learning of survival-related information. Repeated stress results in adaptive plasticity. The resulting changes in dendritic branching and synaptic connectivity in areas like the amygdala, prefrontal cortex, and hippocampus, an area of the brain involved in memory, are largely reversible: when the stress ends, these effects disappear.

Recent evidence indicates that a single episode of traumatic stress results in a delayed and relatively prolonged increase in anxiety in the animal and actual growth of new synaptic connections in the amygdala and the prefrontal cortex. There is also evidence that repeated stress increases vulnerability to other traumas such as a stroke or a seizure.

In the response to stress, there are sex differences in brain remodeling. Female rats do not show the increased dendritic branching seen in the hippocampus of male rats. In contrast, dendritic branching in the amygdala appears to be enhanced by estrogen. When circulating estrogen in female rats is depleted by removing the ovaries, the stress response becomes similar to that in a male rat. Other studies have shown a greater initial effect of acute stress in the male on food intake and fear. It also appears that it takes longer for the female rat than the male rat to recover to baseline levels from a stressor.

Sex differences are neurobiologically and psychologically more complicated than we had thought. There are opposite effects in males and females of an acute stress on the conditioning of a classical Pavlovian response. Work of Gwendolyn Wood and Tracey Shors16 shows that conditioning in male rats is enhanced by

16

GE Wood and TJ Shors (1998). Stress facilitates classical conditioning in males but impairs classical conditioning in females through activational effects of ovarian hormones. Proceedings of the National Academies of Sciences 95(7):4066-4071.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

stress. Exactly the same stress regimen in female rats profoundly suppresses conditioning. These results can be reversed by manipulating hormonal sex early in development. More recently, Shors has shown that giving the male and female rat control over the amount of shock makes the sex differences disappear.

How might some of this translate from animals to humans? McEwen suggested the key may lie in behavioral strategy. Research on rats in a water maze, where they have to swim and find a hidden platform to rest on, shows that the male and females tend to use different exploratory strategies. Without spatial cues, male rats reach the platform faster. When spatial cues are provided, females decrease the time it takes to reach the platform and do as well as or better than males. Karyn Frick and colleagues put student volunteers into an outdoor spatial maze tested memory of local contextual cues.17 Men and women did not differ in their performance in the spatial maze but women had a better memory of objects and their location than men did.

Arguments go back and forth, and the data makes it much more complicated to reach some simple generalizations.

—Bruce McEwen

In summary, McEwen explained there are sex differences that are products of genes, of hormones, and of experience throughout the life span. Males and females do respond differently to stressors, although the differences are complex and depend on the kind of stressor and the circumstances. There appears to be modulation by circulating sex hormones, at least in the animal models. What is described in the animal literature, and also perhaps in some of the human literature, is that there are differences in processing—maybe in priorities and strategies—that are far more important than what are commonly called “abilities.”

BIOPSYCHOSOCIAL CONTRIBUTIONS TO COGNITIVE PERFORMANCE

Diane F. Halpern

Berger Institute for Work, Family, and Children, Claremont McKenna College


Diane F. Halpern began her presentation referring to a paper she had written several years ago, entitled, “What You See Depends on Where You Look.”18 Whether male and female cognitive abilities seem similar or different depends on

17

LJ Levy, RS Astur, and KM Frick (2005). Men and women differ in object memory, but not performance of a virtual radial maze. Behavioral Neuroscience 119(4):853-862.

18

DF Halpern (1989). The disappearance of cognitive gender differences: What you see depends on where you look. American Psychologist 44:1156-1158.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

which data are used. To address the question, whether fewer women than men have the ability to become scientists and engineers, requires an examination of how men and women are similar and different.19

We are not talking about whether men and women are similar or different, which is debatable, because in fact women and men are both similar and different. The real question is in what ways are men and women similar and different, and how to understand the relevance of the similarities and differences.

—Diane F. Halpern

Women are graduating in very high numbers with degrees in science fields, so women obviously have the innate ability to do science. But women are not graduating in equal numbers from all of the sciences. To explain this discrepancy, some people have said that women prefer biological sciences, whereas men prefer physical sciences. Alternatively, psychologists have said that women seem to prefer people-oriented careers and men prefer thing-oriented careers. Career choice and trajectory involves a complex of traits, including abilities, interests, personality variables, opportunities, and the knowledge of available career options.

Society has many sex differences. One is the wage gap, which is not just between men and women. Overwhelmingly women are poorer than men, but the largest wage differences are between women who have children and other people. Women have fewer leadership positions overall, not just in science, not just in academia, but in corporations. College students tell us gender differences are a thing of the past, but men in college spend several more hours a week playing video games than women, among many other differences.

We don’t like to talk about sex differences. Sex differences are simply not popular. It’s much more popular to talk about similarities, there is no doubt about that. But when we talk about differences, then at least we much prefer to acknowledge that they are embedded in environment. But this concept is embedded in the false idea that nature and nurture form a dichotomy. There is not a number out there that we can pin on nature or nurture. We have got to get away from the idea of a nature/nurture dichotomy and interaction, because nature and nurture are not independent variables, and they do not merely interact. We need to replace that whole idea with a model that is biopsychosocial. Nature and nurture are inextricably intertwined; they cannot be separated.

—Diane F. Halpern

19

For more details, figures, and references, see Diane Halpern’s paper in Section 2.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-3 Biopsychosocial model.

SOURCE: DF Halpern (2000). Sex Differences in Cognitive Abilities. 3rd Ed. Mahwah, NJ: Erlbaum.

Experience alters the biological underpinnings of behavior which in turn influences the experiences to which we are exposed. A graphic model of biopsychosocial interactions is presented in Figure 1.3.

Some cognitive tasks show sex differences. Some of these differences are lost in aggregated data. Halpern disagreed with Janet Hyde regarding assigning values to small and large effect sizes, stating that small differences in fact accumulate to make very large differences.20


Some differences that favor females:

  • Rapid access to and use of phonological, semantic, episodic information and long-term memory.

  • Production and comprehension of complex prose.

  • School grades and tests closely aligned to school curricula.

  • Fine motor tasks and speech articulation.

  • Perceptual threshold tasks.

20

V Valian (1999). Why So Slow: The Advancement of Women. Cambridge, MA: MIT Press.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Some differences that favor males:

  • Visual transformations and visuospatial working memory.

  • Moving objects and aiming at targets.

  • Fluid reasoning tasks

  • Novel tasks unrelated to things that are taught in school.

Males are overrepresented in both extremes of performance—among the retarded and the gifted. That finding has been used to explain why there are fewer females in science and mathematics, but does not explain why there are fewer females in these professions overall. Not just are there fewer gifted women in science and mathematics, there are just fewer women.

International data also show sex differences. The PERLS reading study shows statistically significant effects on reading literacy at age 15, favoring girls. The mathematics test score difference is rather unimpressive and tends to be insignificant. The science test score difference at 8th grade tends to favor males and gets larger in college and graduate school as the student samples become more selective.

A test-grade disparity is part of the puzzle. Girls get higher grades in school in every subject, even when they are getting lower grades on the achievement tests. Women are graduating at a substantially higher rate than males from college, 133 women for every 100 men.

Despite those successes, women score significantly lower on many tests of science and mathematics, particularly on tests that have questions not closely related to materials taught in school. This discrepancy leads some to ask whether teachers in schools are biased against boys or whether achievement tests are biased against girls.

Cognitive processes are involved. As Bruce McEwen discussed, some have suggested that males and females are using different problem-solving strategies. Like Janet Hyde, Halpern called for education in visuospatial skills. But in trying to answer the underlying question, are there too few women with the highest levels of ability to be scientists and engineers, Halpern pointed beyond cognitive processes to a larger framework in academe: the tenure system. Marriage and having children have an adverse effect on the research productivity of women in academia.

That tenure clocks and biological clocks run in the same time zone is the more likely and proximal cause for some of these problems than cognitive differences.

—Diane F. Halpern

The take-home message: females and males are similar and different, depending on what is measured. The types and sizes of cognitive differences vary between men and women. Some of the measures favor females, some favor males.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

There are consistent differences internationally. Halpern called for a biopsychosocial model to replace the nature/nurture dichotomy and for consideration of the larger academic and societal context.

SELECTIONS FROM THE QUESTION AND ANSWER SESSION

DR. AGOGINO: Hi, I’m Alice Agogino from the University of California at Berkeley. I have a question about how authentic these assessments or these features are in terms of actual practice and success. Janet, you mentioned the Linn Peterson study, a meta-analysis on spatial reasoning and found the greatest differences were for three-dimensional rotation, as measured by the Shepherd Test. I worked with Marcia Linn when I taught a Mechanical Engineering freshman design class where spatial reasoning skills were important. We looked at expert spatial reasoners in industry and found that they did even worse on some of those tests than the students at the lowest end of the scale. The big difference was timing. If we added 30 seconds onto a test, we got rid of a lot of the differences. We did a two hour workshop and developed strategies that improved the performance of both men and women and got rid of all the gender differences in performance on these tests. My question is, before we start creating courses, do they really matter in terms of success, and their authenticity for success in practice?

DR. HALPERN: People often ask that question. Spatial reasoning is correlated with grades in engineering schools; it’s been used in dental schools as a grade predictor; and the ability to see things from multiple angles is used in imagining what a molecule will look like if you rotate it in space. In some of my own work recently we have found that males were imaging a lot of the material when they were reading it, and some of the females also. While we are teaching people how to read, we’re teaching people how to do math. Cognitively this is another one of those dimensions that we have just not paid attention to in the educational system.

DR. BICKLE: Janet Bickle, formerly of the Association of American Medical Colleges, and now a career development coach. I wonder if anyone else noticed this week, a very small article in the Post that was a study of monkeys, finding that male monkeys were more likely to play with cars, and the female monkeys were more likely to play with dolls, including looking at the dolls’ bottoms. And the males actually playing with the cars the way little boys do. I was wondering what sense the panelists could help us make of this type of finding.

DR. HYDE: I think partly because I’m a meta-analyst, I’m very keenly aware of how many behavioral studies in psychology don’t replicate. And so, I would really want to see that study replicated before I made any interpretations, because studies like that are so quickly picked up by the media. Everybody loves them. And then there are 10 failures to replicate, and they never get attention. I think we really have to ask for the standard of replicability in a lot of these phenomena.

DR. MCEWEN: I might add that while I have no comment about that particular study, it’s well established in animal behavior studies on both rodents and on

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

rhesus monkeys that there is an androgen-dependent rough and tumble play behavior which is very typical of the male of both species, and can be influenced by testosterone, and can be produced by exposure of females at the right time of development to testosterone. So, there is a phenomenon there. How it has to do with playing with any particular toy, I have no idea.

DR. GIEDD: If the studies are done well, it is a great insight into the role of socialization and media exposure and all these other sort of things, and the biology itself. So, I think it’s a very worthwhile direction to pursue, if it’s done well.

DR. WEYUKER: I’m Elaine Weyuker. I’m at AT&T Labs, and I’m a member of the committee. In terms of the swimming rats, one of the things I was struck by was the female rats’ strategy was to swim along the edge, whereas the male strategy was to go down the middle and to look. But one of the other things I noticed was that you stuck the platform in the middle. And so, had you stuck the platform at the edge, it sounds to me like the female rats would have been the stars. Are we using as measures of “success” the things that the women don’t do as well?

DR. MCEWEN: The point you make gets back to this idea of strategy, and obviously, the way you set up the task can give you different results. I can give you more kinds of experiments not involving that swimming task, where again, you can establish that there are not only sex differences, but also giving estrogen to ovariectomized female rats actually improves their choice of a place strategy over a response strategy, perhaps by enhancing the function of the hippocampus over the function of other brain areas.

DR. WEYUKER: And what the measure of success is.

DR. MCEWEN: Yes, that’s a good point. But like the example from Karyn Frick’s studies, when you are looking at the memory of location and identity of objects, on the average the women did better than the men in remembering these things. That may contribute to the success of women in handling certain kinds of spatially-related, contextual tasks where they have to remember locations of things in order to make choices.

DR. GARMIRE: I’m Elsa Garmire from Dartmouth College. The subject of this convocation is women in academe. From my point of view, I would imagine that most of women in academe would be in perhaps let’s say the top 20% of whatever group that you are investigating. And what I want to know particularly in the meta-analyses, which seem to give you the average of all humans, have there been studies that have looked at the top 20%, and compared the top 20% of males to the top 20% of females in any of these studies?

DR. HYDE: There is a series of studies originally begun at Johns Hopkins by Julian Stanley and Camilla Benbow of gifted youth. They recruit mathematically precocious children in the seventh or eighth grade who score 700 or more on the mathematics SAT. Stanley and Benbow do find a disproportionate number of boys in their group compared with girls. I have never been able to pin down exactly how they recruit them though, because for example, if it’s partly by

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

teacher recommendation, then you wonder if teachers don’t tend to see more mathematical talent in boys, even when it’s present in girls as well.

DR. GARMIRE: Yes, but they have started out already selecting. What I’m suggesting is in all of these studies, if one went back and said, okay we are not going to look at the average for everyone, we’re going to fit everyone to a bell curve, and then take the top 20% of that data, I think you could do a meta-analysis without any pre-selection of people and analyze exactly how males and females compare in the upper reaches.

DR. CAUCE: Those are a series of studies that I’m fairly familiar with. Part of what is interesting is that there are many more men in both tails of the performance distribution. But what is interesting is that even though you have more men than women in the tails, if you look at the differences in the career trajectories of the men and women in the upper tail, so we are talking about the upper 1% in terms of mathematics talent and ability, a much higher percentage of those men follow the trajectory into mathematics and science. Women are much more likely to go into particularly medicine and law than in science. I’m not aware of any studies that have tried to particularly truncate at about 20 or 25%.

DR. VOGT: Hi, Christina Vogt, National Academy of Engineering. I think that we need to look a little bit more at social determinants of engineering and science careers than spatio-visualization skills.

DR. HYDE: I agree, and I think some of the panels later today are going to be getting at some of the factors like that, so it’s definitely important.

DR. CAUCE: I couldn’t agree with you more. There is no question but that workplaces and how people react to them are different. But then also there is some work that suggests there might be some biologically based differences in motivations, so, that women would be motivated more towards going into social careers, which are defined, and I would say erroneously, as being non-science careers.

DR. SAENZ: My name is Delia Saenz. I’m a social psychologist at Arizona State University, and I do work on tokenism. Much of that work, at least in the early part of my career, demonstrated that tokens suffer cognitive deficits. I remember when I found the first result, I wanted to hide the research, because I thought, okay, nobody is going to want to hire women or minorities, because they will bring them in, and they will do poorly, not because of their capacity, but rather because of the environmental configuration that is having them concerned with self-presentation. One of my best friends said, you know what? You got the same finding for males and for white males. So, it’s not a matter of who you are, but the context.

I agree with what you all suggested earlier, that if you match the person to the task, and you have a good fit, things will go better. And in fact, my more recent work on tokenism suggests that there are cognitive surfeits if you are a token. So, because you are concerned with self-presentation, you’re better able to take perspectives, and you are good at negotiating, which is a good thing, and it happens

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

for women and minorities, as well as for males and whites. That’s very exciting. So, we will get to the point where we are not just focusing on differences in ability, but differences in outcome, differences in being able to make a living and having your contributions validated.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL 2
SOCIAL CONTRIBUTIONS

   

 Panel Summary

 

 

   

  Implicit and Explicit Gender Discrimination
Mahzarin Rustum Banaji, Department of Psychology, Harvard University and Radcliffe Institute for Advanced Study

 

 

   

  Contextual Influences on Performance
Toni Schmader, Department of Psychology, University of Arizona

 

 

   

  Interactions Between Power and Gender
Susan Fiske, Department of Psychology, Princeton University

 

 

   

  Social Influences on Science and Engineering Career Decisions
Yu Xie, Department of Sociology, University of Michigan

 

 

   

  Selections from the Question and Answer Session
Moderated by committee member Alice Agogino

 

 

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL SUMMARY

The panel examined the role of bias, discrimination, and personal preference in cognitive performance, evaluation of ability, and career preferences. Mahzarin Rustum Banaji, of Harvard University, used an audience-participation technique based on her widely utilized, computer-based data collection techniques to demonstrate the unconscious, automatic, and unintentional nature of implicit biases and their dissociation from conscious beliefs. An audience composed overwhelmingly of female scientists, scholars, and government and university administrators displayed biases widespread in the culture that assume that science and mathematics are masculine and home and family feminine. The pervasiveness of such unconscious or implicit bias is important because a meta-analysis indicates that biases predict action. Biases are nonetheless malleable, Banaji continued, with the science now providing insight into how even implicit stereotypes can be changed.

Toni Schmader, of the University of Arizona, presented data on stereotype threat, the negative effect of stereotyping on test performance. Context, such as framing a test as a measure of ability or reminding test-takers of gender, can trigger stereotype threat that lowers performance and self-confidence and can discourage women and minority-group members from seeking mathematics and science careers or leadership roles important to career success. Reducing stereotype threat can release cognitive resources needed for peak performance.

Susan Fiske, of Princeton University, explored the interaction between power and gender as revealed in modern gender bias, which is automatic, ambiguous, and ambivalent. Ambiguity reveals itself in several ways: in shifting standards; in the short-list problem, in which women are nominated but not selected for high posts (giving decision makers “moral credentials” for short listing the women even if she was not chosen); and in women’s alleged “lack of fit” for posts traditionally considered male. The traditional gender role of female subservience is not only descriptive but also prescriptive, and women in the workplace who defy its limits are punished. Objective standards are needed to deal with ambiguous bias. Ambivalence reveals itself in two types of sexism— hostile and benevolent— which correlate, respectively, with the stereotype of nontraditional women as “not nice” and traditional women as “not competent”; this leads to the Catch 22 that women are either liked and not respected or respected and not liked. To overcome ambivalent bias, women must focus on gaining respect, often with costs to their rated likeability.

Explaining the discrepancy between men and women in science requires giving up the “naïve idea of finding simplistic explanations,” according to Yu Xie, of the University of Michigan. The life-course approach—a perspective that recognizes interactive effects, individual variations and the cumulative nature of these effects—forces rejection of several commonly offered explanations. The “critical filter” hypothesis that inadequate high-school mathematics training

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

handicaps women or the fact fewer women than men score in the upper percentiles in mathematics ability does not explain why fewer women than men major in science. The metaphor of the science career as a pipeline also falters because it incorrectly assumes that one can only leave science and not come back to it. The so-called “productivity puzzle,” which argues that women scientists are systematically less productive than men, vanishes if contextual factors are held constant. The factor most likely to prevent a woman with science training from pursuing a scientific career is children. The discrepancy between men and women in science has deep social, cultural, and economic roots.

IMPLICIT AND EXPLICIT GENDER DISCRIMINATION

Mahzarin Rustum Banaji

Department of Psychology, Harvard University and Radcliffe Institute for Advanced Study


Mahzarin Banaji focused her presentation on an invisible form of bias— implicit bias—and her work using the Implicit Association Test (IAT). She began by quoting a colleague who had said, “Women are not being kept out of science by force, so they must be choosing not to enter, presumably because they don’t want to, presumably because by and large, they don’t like these fields, or on average don’t tend to excel in them, which is nearly the same thing.”

Psychologists have spent careers in trying to understand the meaning of words like choose, want, and like. They are complicated. Much of the way we behave happens outside conscious awareness. Many of our thoughts and feelings arise in an automatic and unintentional fashion.

Our evolutionary history sets us up to have a particular way of looking at things. We are immersed in a larger culture that teaches us the associations between large categories and particular attributes. We need a much finer-grained understanding of what we mean by environment.

—Mahzarin Banaji

Banaji and her colleagues have done experiments using the IAT in which they ask people to look at pictures and say what they see.21 Gender is not verbalized, but it affects decisions about the next object viewed. Gender is evoked quite outside conscious awareness and is associated with the image object. Banaji also has used the IAT to research the strength of the association between sex and

21

For more on the Implicit Association Test, see https://implicit.harvard.edu/implicit/.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

categories such as mathematics and science vs. the humanities. Both men and women show high association between self and their gender group. For men, there is a positive association between maleness and mathematics. For women, there is a negative association between femaleness and mathematics. Furthermore, stronger me-female connections are correlated with stronger female-does-not-equal-mathematics connections.22

There is a large difference between perceived or believed difference and actual difference in mathematics performance. The bias associating maleness with mathematics has a d of 1.5-2. The performance differences meta-analyses reported by Janet Hyde show a d of 0.05. These biases are large and pervasive.

A signature of implicit biases is that they contradict conscious beliefs. It is not that a person does not know that mathematics is stereotyped as male, and that home is stereotyped as female. Rather, people taking the IAT who try explicitly to associate each sex equally with each category cannot. This contradiction is of interest for a variety of reasons. Most interesting, it shows the deviation from where we want to be.

Implicit biases have predictive power. A meta-analysis of close to 100 IAT studies showed that the magnitude of the bias demonstrated in experimental conditions accurately predicts a person’s behavior in nonexperimental situations.23

This kind of test tends to predict attitudes toward affirmative action. It tends to predict whether one will hire somebody who is a female or not, and so on. We need more science to show us how these kinds of associations affect our behavior.

—Mahzarin Banaji

The optimistic part of this message is that these biases are malleable—in ways that many of us never could have imagined. Put girls and boys into a room where there are signals that make the association between mathematics and women. The biases will change so that girls will make the association between women and mathematics within a period of a few minutes, overcoming temporarily what has been learned over a long period.

Attitudes and beliefs are malleable and easy to change if we know what to do. It may not take much effort to fix the problem once we know what to do.24

22

BA Nosek, MR Banaji, and AG Greenwald (2002). Math = male, me = female, therefore math me. Journal of Personality and Social Psychology 83(1):44-59.

23

W Hofmann, B Gawronski, T Gschwendner, H Le, and M Schmitt (2005). A meta-analysis on the correlation between the Implicit Association Test and explicit self-report measures. Personality and Social Psychology Bulletin 31(10):1369-1385.

24

For example, see J Kang and MR Banaji (2006) Fair Measures: A behavioral realist revision of “affirmative action.” California Law Review 94:1063-1118.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
CONTEXTUAL INFLUENCES ON PERFORMANCE

Toni Schmader

University of Arizona


Toni Schmader followed up on pervasive, implicit biases and focused on the social context in which contending with these biases can shape women’s performance on many of the types of tasks that were presented in the first panel discussion.

One of the lessons that we have learned from social psychology is that we have a tendency to look at what a person does and to assume that the main variable responsible for their behavior is them.

—Toni Schmader

In a classic study, observers watched as one participant struggled to answer esoteric trivia questions asked by another participant.25 The observers knew that the two participants had been randomly assigned to either ask or answer questions. They also knew that the questions were unreasonably difficult, but they still had a bias toward assuming that the person answering the questions was less competent and less intelligent than the person asking them. These data make the point that we tend to want to infer people’s ability from their performance even when we know that the social context stacks the deck against them. To what degree do these implicit biases and gender stereotypes that assert women’s incompetence in mathematics, science, and engineering undermine women’s ability to perform?

Stereotype threat applies as well to women performing on a difficult mathematics test. In one of Schmader’s recent studies,26 men and women in one condition were told that their task would yield a diagnostic measure of mathematics ability that would be used to compare men’s and women’s scores; in this condition, there was a gender gap similar to that seen in SAT scores shown by Diane Halpern. But in a second condition, a second group of students given the same set of word problems were told that it was just a problem-solving exercise, with no mention of a test, mathematics, or ability; here, women’s performance on the test was significantly better and not different from that of their male peers regardless of whether differences in SAT were controlled for (Figure 1-4).

Results like those should make us question whether the kinds of differences we see in performance measures can be adequately accounted for by underlying

25

L Ross, TM Amabile, and JL Steinmetz (1977). Social roles, social control, and biases in social perception. Journal of Personality and Social Psychology 35:485-494.

26

M Johns, T Schmader, and A Martens (2005). Knowing is half the battle: Teaching stereotype threat as a means of improving women’s math performance. Psychological Science 16:175-179.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

BOX 1-2

Stereotype Threat

In 1995, Claude Steele and Josh Aronsona published an influential article in which they demonstrated a phenomenon they called stereotype threat. Stereotype threat occurs when people feel that they might be judged in terms of a negative stereotype or that they might do something that might inadvertently confirm a stereotype about their group.

When any of us find ourselves in a difficult performance situation, especially one that has time pressure involved, we might recognize that if we do poorly, others could think badly about our own individual abilities. But if you are a woman or minority-group student trying to excel in science, there is the added worry that poor performance could be taken as confirmation that group stereotypes are valid.

In their first series of studies, Steele and Aronson set out to ask whether you could change a minority-group student’s ability to perform on a difficult intellectual task by simply changing the context, for example, how the task is described. They had white and black college students at Stanford University come into a laboratory to complete a set of difficult questions taken from the Graduate Record Examination (GRE). Half the participants were told that the test would measure verbal ability—the same kinds of instructions that students might expect to get before taking the GRE. They found the same type of race gap in test scores that is often seen on standardized tests. For a second group of students, the same task was described as a laboratory exercise. Under these more neutral conditions—in which no reference was made to race, ability, or a test—African American students performed significantly better; their performance was not different from that of their white peers.

  

aCM Steele and J Aronson (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology 69:797-811.

differences in ability. If differences in ability explained the gender gap or the race gap, as least with these kinds of samples, it should not be so easy to erase or reduce that gap by simply changing how the test is described.

We know that contextual cues, such as how a test is described, can be one type of variable that can lead to stereotype threat. Research suggests that other types of situational cues that can lead to the same processes. For example, something that merely reminds people of their gender or race can be enough to produce

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-4 Gender differences in mathematics performance.

SOURCE: M Johns, T Schmader, and A Martens (2005). Knowing is half the battle: Teaching stereotype threat as a means of improving women’s math performance. Psychological Science 16:175-179.

these processes.27 In some experiments, simply having a woman answer a questionnaire about gender issues before taking a mathematics test leads to a significant reduction in performance.28

It is true that a lot of these experiments have been done with college-aged populations, but the effects have been replicated in younger age groups as early as elementary school.29 Replications are also seen in more natural settings such as classroom environments.30

These data tell us that context can shape performance on test scores. But

27

CM Steele and J Aronson (1995), Ibid; M Inzlicht and Ben-Zeev (2000). A threatening intellectual environment: Why women are susceptible to experience problem-solving deficits in the presence of men. Psychological Science 11:365-371.

28

M Shih, TL Pittinsky, and N Ambady (1999). Stereotype susceptibility: Identity salience and shifts in quantitative performance. Psychological Science 10:80-83.

29

N Ambady, M Shih, A Kim, and TL Pittinsky (2001). Stereotype susceptibility in children: Effects of identity activation on quantitative performance. Psychological Science 12:385-390.

30

J Keller (2002). Blatant stereotype threat and women’s performance: Self-handicapping as a strategic means to cope with obtrusive negative performance expectations. Sex Roles 47:193-198.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

what about other types of variables? Does women’s or girls’ preference or interest in mathematics reveal conscious choice? Research indicates that implicit biases can shape what students believe about what they are capable of and then what they are interested in.

In a study at the University of Arizona, Schmader and colleagues asked female science majors to rate the degree to which they agreed with statements about inherent differences in abilities between men and women.31 Most students tended to reject beliefs about inherent sex differences in abilities, but some wondered whether such innate differences might exist. In her data set, students who tended to agree with statements about inherent sex differences reported having less confidence in their own abilities in their science majors, lower self-esteem about their performance, and less interest in attending graduate school in their major field.

Where do the stereotypes come from? Even if parents and teachers are well intentioned and try to guard their students against these kinds of beliefs, children from a very early age are bombarded by messages that say what a feminine woman should be like. Recent evidence suggests that even experimental exposure to these mass media affect a woman’s stated interest in pursuing a career in science or engineering. Female college students were shown television commercials that were neutral or that portrayed women as stereotypically feminine. After exposure to the stereotypic ads, women reported less interest in science and mathematics careers than in language-based careers. In a later study, after exposure to the stereotypic ads, women also reported less interest in taking on a leadership role and instead preferred a more subordinate role in which they would be taking direction from others.32

Together, those data suggest that the context, namely stereotypes that exist in the environment, can lead to lower test performance and maybe shape lower confidence, can lead some women to develop less interest in pursuing science- and mathematics-based careers even when they major in those fields, and maybe can shape students’ interest in taking on the leadership roles that are necessary for success in academic research.

Having provided some evidence that context can shape performance, how do we go about closing the gender gap? Context can be changed through a combination of social policy designed to create threat-free environments and educational strategies to try to teach both students and mentors about the kinds of circumstances in which bias can exist. The mere presence of successful and competent

31

T Schmader, M Johns, and M Barquissau (2004). The costs of accepting gender differences: The role of stereotype endorsement in women’s experience in the math domain. Sex Roles: A Journal of Research 50:835-850.

32

PG Davies, SJ Spencer, DM Quinn, and R Gerhardstein (2002). Consuming images: How television commercials that elicit stereotype threat can restrain women academically and professionally. Journal of Personality and Social Psychology 33:561-578; PG Davies, SJ Spencer, and CM Steele (2005). Clearing the air: Identity safety moderates the effects of stereotype threat on women’s leadership aspirations. Journal of Personality and Social Psychology 88:276-287.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

women in science and engineering can send a signal that women can be capable in these fields. In controlled laboratory experiments, there is a gender gap in mathematics test scores when a study is run by a competent man; when the study is run by a competent woman, that gender gap is reduced.33

In addition to changing the gender composition of faculty leadership positions, we can change the gender composition of the classroom. We can try to close the gap through education. We need to teach our educators to be wise mentors, to speak out against the stereotypes in front of students. Research suggests that stigmatized students are most likely to be motivated to work on their mistakes and grow from past experiences if they receive feedback that provides a combination of high standards for performance and communication from the educator that students are capable of meeting them.34

We can emphasize skill over ability and frame learning as part of the incremental process where tests measure progress towards goals. We can try to foster a sense of belonging among young women in the sciences. Often, when members of stigmatized groups face difficulty or challenges, they take it as a sign that they are in the wrong place, that they don’t belong. By helping students to see that learning and diversity are natural parts of the educational process, we can help them to adjust their interpretation of the situations they encounter.

—Toni Schmader

A year-long intervention study tested the effectiveness of those kinds of educational messages.35 College students mentored three groups of 7th-grade students. One group was taught by the college students over the course of the school year that intelligence is an incremental skill that grows with effort. The second group was taught that experiencing difficulties is a normal part of educational growth. And the third group, a control group, was given anti-drug messages. At the end of the school year, there was a statistically significant gender difference in mathematics test performance only among the students who were in the control group. There was no measurable gender difference in test performance in the two groups that received the educational messages.

Another way to inoculate students through education is by unveiling the effects that implicit biases and stereotype threat can have on a woman’s performance and anxiety. When women are facing difficulty in a specific performance

33

DM Marx and JS Roman (2002). Female role models: Protecting women’s math test performance. Personality and Social Psychology Bulletin 28:1183-1193.

34

GL Cohen, CM Steele, and LD Ross (1999). The mentors’ dilemma: Providing critical feedback across the racial divide. Personality and Social Psychology Bulletin 25:1302-1318.

35

C Good, J Aronson, and M Inzlicht (2003). Improving adolescents’ standardized test performance: An intervention to reduce the effects of stereotype threat. Applied Developmental Psychology 24:645-662.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

situation such as taking a standardized test, they may interpret that difficulty as a sign that they are not capable.

By being able to externalize anxiety, women might by able to free up the cognitive resources that are necessary to focus on the task at hand.

—Toni Schmader

In the earlier-described math test36 one group of students were told that their task would yield a diagnostic measure of mathematics ability that would be used to compare men’s and women’s scores, and a second group of students were told that the task was just a problem-solving exercise. There was a third condition to that experiment. Students were told that the test they were taking was a diagnostic measure of mathematics ability, and that their performance would be used to compare men’s and women’s scores—the same conditions that led to performance decrements in the first group. However, they were also informed about stereotype threat and reminded that if they were feeling anxious while taking the test, it might be a result of external stereotypes and not a reflection of their ability to do well. Under those conditions, women’s performance was significantly increased and not significantly different from that of their male peers (Figure 1-5).

We need additional research and additional funding to identify the precise mechanisms that account for the effects of stereotypes. But we also need funding to develop more field-based interventions that would put into practice some of the available ideas to test their effectiveness in closing the gap.

In closing, Schmader discussed the implications of the contextual approach for such policy issues as affirmative action. She spoke about the need to create more diverse learning environments, to make sure that there are women and minority group members both in the student body and on faculty. To the degree that affirmative-action policies can help to ensure that we have that kind of diversity of representation, they can create not only a threat-free environment for women and others who are socially stigmatized in science and engineering but also a more diverse learning experience for everyone.

In light of implicit biases and contextual effects on performance, affirmative action can do more. If the difference that we see in standardized test scores can be explained by contextual factors that are systematic and that affect men and women differently, it seems reasonable for admissions committees to take that into account when they evaluate student applications.

—Toni Schmader

36

M Johns, T Schmader, and A Martens (2005). Knowing is half the battle: Teaching stereotype threat as a means of improving women’s math performance. Psychological Science 16:175-179.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-5 Teaching about stereotype threat inoculates against its effects.

SOURCE: M Johns, T Schmader, and A Martens (2005). Knowing is half the battle: Teaching stereotype threat as a means of improving women’s math performance. Psychological Science 16:175-179.

INTERACTIONS BETWEEN POWER AND GENDER

Susan Fiske

Department of Psychology, Princeton University


Susan Fiske discussed the relationship between gender stereotyping and various manifestations of power in the context of women moving into science careers, particularly the effects of ambiguous and ambivalent biases.

Modern forms of gender bias are not your grandmother’s version of gender bias.

—Susan Fiske

Several studies have shown how gender stereotypes and prejudice are ambiguous. One is from Monica Biernat’s work on shifting standards.37 Her work showed that people will say that a candidate is “really good for a woman,” but

37

M Biernat and ER Thompson (2002). Shifting standards and contextual variation in stereotyping. European Review of Social Psychology 12:103-137.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

when comparing the woman to a man, find her lacking. Such judgment depends on whether standards are subjective or objective. A number of validated judgment dimensions need to be considered in the standards that people use.

Terri Vescio has demonstrated the related “short list” problem.38 Women may be nominated and appreciated and put on short lists for opportunities, but when a choice has to be made, women are not picked. People gain moral credentials for developing unbiased short lists, but in making a final decision they weight things in favor of the status quo.

Madeline Heilman’s work on lack of fit has demonstrated that if the predominant model is that managers are male or scientists are male, then women somehow don’t fit if they seem “like women.”39 But, if women try to fit by acting like men, they are not liked very much, and that doesn’t work either.40

It comes down to what Barbara Gutek has called sex-role spillover: people have implicit expectations that men are going to act like men and women act like women in the workplace. She shows this assumption can lead to sexual harassment.41 When women are agentic—assertive and controlling—and do not act like traditional women in the workplace, there is backlash, as shown by Alice Eagly and Laurie Rudman.42

Gender stereotypes are not just descriptive, they are prescriptive. It’s not just how women are, it’s how women are supposed to be. And women who behave out of role are punished for it.

—Susan Fiske

Gender stereotyping is ambiguous. People cannot easily know when they are the objects of gender stereotyping nor, for that matter, when they are perpetuating stereotypes. It is very hard to be on a committee that is making a decision and to decide whether the decision is biased or not, because stereotyping is ambiguous. It is no longer somebody saying a woman cannot be hired. It is much more subtle. That is why the numbers are important. We have to look at the education and

38

M Biernat and TK Vescio (2002). She swings, she hits, she’s great, she’s benched: Shifting judgment standards and behavior. Personality and Social Psychology Bulletin 28:66-76.

39

M Heilman (2001). Bias in the evaluation of women leaders. Description and prescription: How gender stereotypes prevent women’s ascent up the organizational ladder. Journal of Social Issues 57(4):657-675.

40

Price Waterhouse v. Hopkins, 490 U.S. 228 (1989).

41

BA Gutek and B Morasch (1982). Sex-ratios, sex-role spillover, and sexual harassment at work. Journal of Social Issues 38:55-74.

42

LA Rudman and P Glick (2001). Gender effects on social influence and hireability: Prescriptive gender stereotypes and backlash toward agentic women. Journal of Social Issues 57(4):743-762; AH Eagly (2004). Few women at the top: How role incongruity produces prejudice and the glass ceiling. In Identity, leadership, and power, Eds. D van Knippenberg and MA Hogg. London: Sage Publications.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

workforce pyramid: many women major in science and engineering, fewer women go to graduate school, fewer become assistant professors, still fewer become tenured professors, and even fewer become full professors and deans. Women are bailing out at every stage. The incoming cohorts, while they are making a difference, are not going to make up for this loss of talent.

What’s so special about sex? The things I’ve been mentioning are true for other kinds of stereotypes. They are true for racial stereotypes, too, for the most part. The difference is that men and women are wonderfully and horribly, depending on the circumstances, intimately interdependent. That is the source of great joy and great personal tragedy. Men and women have personal power in their interdependence, but it’s a different kind of power from the societal power that men have in general. And that leads to profound ambivalence in gender prejudice.

—Susan Fiske

Fiske and Peter Glick have developed a theory of ambivalent sexism, which is built upon the concepts of hostile and benevolent sexism. Male dominance leads to the possibility of hostile sexism, which is what people commonly associate with the term “sexism.” Hostile sexism is targeted particularly at non-traditional women, that is, women who are perceived to challenge men and male dominance. But a different kind of sexism had not been identified before in the psychology literature. Intimate interdependence leads to benevolent sexism, attitudes that are experienced as favorable toward women serving in traditional roles, such as homemakers.43

Together, hostile sexism and benevolent sexism maintain the status quo. Both can be measured with the Ambivalent Sexism Inventory, validated with people all over the world. What Fiske and Glick find is that hostile sexism correlates with negative stereotypes of nontraditional women and benevolent sexism correlates with positive stereotypes of traditional women. Benevolent sexism predicts positive evaluations of homemakers and negative evaluations of career women. Across many countries, men score higher on hostile sexism than women do. Women do not score zero; they can be sexist, too. But on average, hostile sexism is stronger for men. With benevolent sexism, the difference is much smaller. Levels of hostile and benevolent sexism are correlated with United Nations indices of human development.44

43

P Glick and ST Fiske (1996).The Ambivalent Sexism Inventory: Differentiating hostile and benevolent sexism. Journal of Personality and Social Psychology 70:491-512.

44

United Nations Human Development Programme (1995). Human Development Report 1995. New York: Oxford University Press, http://hdr.undp.org/reports/global/1995/en/; P Glick, S Fiske, A Mladnik, JL Saiz, D Abrams, et al. (2000). Beyond prejudice as simple antipathy: Hostile and benevolent sexism across cultures. Journal of Personality and Social Psychology 79:763-775.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-6 Fiske et al.’s Stereotype Content Model applied to subtypes of women.

SOURCE: T Eckes (2002) Paternalistic and envious gender stereotypes: Testing predictions from the stereotype content model. Sex Roles 47(3-4):99-114.

The tension between being liked and being respected—homemakers are liked but disrespected and career women are respected but disliked—maintains inequality by confining women’s roles, as shown by Thomas Eckes.45 Combining his work with Fiske and Glick’s stereotype content model, as shown in Figure 1-6, shows housewives categorized as incompetent along with disabled people, senior citizens, and unemployed people. Career women and feminists are categorized as competent with managers, politicians, and millionaires. The liked but disrespected homemakers are protected and helped, but also excluded and neglected. With career women, who are respected but disliked, others will cooperate, associate, and go along to get along when they have to. But when the chips are down, career women are more likely than men to be attacked and sabotaged.

Fiske emphasized the need to recognize the tightrope that women are walking not to be too feminine, not to be too masculine, but somehow managing to juggle these gender tensions. With respect to ambivalence, most out-groups really do not care if you like them or not. They want to be respected, so that they can be

45

T Eckes (2002). Paternalistic and envious gender stereotypes: Testing predictions from the stereotype content model. Sex Roles 47(3-4):99-114.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

promoted. Fiske suggested establishing careful standards by which people are evaluated to mitigate the effects of automatic, ambiguous, and ambivalent gender bias.

SOCIAL INFLUENCES ON SCIENCE AND ENGINEERING CAREER DECISIONS

Yu Xie

Department of Sociology, University of Michigan


Yu Xie based his presentation on a book he researched and wrote with Kimberlee Shauman, an associate professor of sociology at the University of California, Davis.46 He highlighted major findings from the book.47

Earlier studies on sex differences in career trajectories examined only subsets of scientists and engineers, such as high school students, college students, graduate students, and practicing scientists. Xie and Shauman analyzed 17 large, nationally representative datasets that spanned the career. They adopted a life-course approach, which recognizes interacting effects across multiple domains in a life, such as education, family and work. What we do in one domain of life affects what we do in other domains, so these factors are interrelated and cumulative. What happened before affects what happens now. What is happening to you now affects what will happen later. We call this path dependence.

To implement a life-course perspective on the study of gender in science, it is necessary to pay attention to data. Ideally, we would have data that span the entirety of a career from early ages to retirement. Not only do we want to have a dataset so expansive in scope, we also would like to have longitudinal data that follows the same individuals over their life course. Because scientists are only a small proportion of the labor force in the population, it is not possible to do that. To make up for the deficiency in data sources, Xie and Shauman painted a composite picture, using some data sources from (1) students in grades 7-8, (2) high school students, (3) college students, (4) graduates who attain bachelor’s degrees and master’s degrees in science and engineering, and (5) individuals who work in the labor force as scientists. This approach is called a synthetic cohort analysis.

The short version of the conclusion of this study is really one word: complexity. There are no simple answers.

—Yu Xie

46

For more details, figures, and references, see Yu Xie’s paper in Section 2.

47

Y Xie and K Shauman (2003). Women in Science: Career Processes and Outcomes. Cambridge, MA: Harvard University Press.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Xie and Shauman rejected several widely held hypotheses and claims, with which the data were not consistent.

The first rejected hypothesis was the critical filter hypothesis, which states that women are handicapped or disadvantaged because they are not good at mathematics in high school. The gender gap in average mathematics achievement is small and has been declining, as Hyde discussed earlier. However, males are more dispersed in the high and low ends of the achievement spectrum. The representation of girls is lower than the representation of boys in the top 5% of achievement. However, gender differences in average mathematics achievement and in high level mathematics achievement do not explain gender differences in majoring or degree attainment in science.

The second hypothesis was the pipeline paradigm, which assumes that we can only leave science and not come back. That is not accurate. Career processes are fluid and dynamic. Entry, exit, and re-entry are all possible. Participation gaps are greatest at the transition from high school to college. A substantial percentage of males and females express the desire to become science and engineering majors, according to attitudes assessed in high school. Some will change their mind and major in nonscience fields in college, but a fraction of them obtain science degrees. The most critical juncture is the transition between high school and college. Not only do fewer high school girls expect to major in science in college, but from this point to the first year in college, fewer females are likely to realize their expectation than males. After the first year in college, there is little difference in persistence to a degree attained.

The third hypothesis was the productivity puzzle. Xie and Shauman looked at practicing scientists employed as faculty members in colleges and universities. A standard claim has been that women publish slightly more than half as many papers as men. Cole and Zuckerman looked at the historical trend and at everything they could find to explain this gap, and could not explain it away. Scott Long reaffirmed the conclusion. In their reanalysis, Xie and Shauman had two major findings. First, looking at research productivity over the time from the late 1960s all the way to 1993, one sees a steady increase in women’s productivity relative to men’s. The steady improvement in women’s research productivity suggests something deeper and broader than biology alone. Second, most of the observed sex difference in research productivity even in the earlier years can be attributed to sex differences in background characteristics, employment positions and resources, and children.

The fourth and hypothesis examined was that a family life hampers women scientists’ careers. They found that married women with children were less likely than men or other women to pursue science careers after the completion of science or engineering education; they are less likely to persist in science; they are less likely to be in the labor force or employed and they are less likely to be promoted. These women have already attained education in science, so it is not that they cannot do the work, pass the examinations, and learn the material.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Is there a family effect? We find that marriage itself does not seem to matter much. Married women are disadvantaged only if they have children.

—Yu Xie

If you compare single men with single women, you do not see differences in the likelihood of whether they work or not, whether they go to graduate school rather than work, whether they are in graduate school, whether they are in science, or if they work, whether they are in science or not in science. You see the biggest gender gap when women are married and have children. Married women with children are more likely to stay out of graduate school and work. If they go to graduate school, they are less likely to stay in science and engineering. If they work, they are less likely to work in science and engineering.

In summary, Xie and Shauman

  • Did not find that the “mathematics gap” is important.

  • Found that career processes are fluid and dynamic.

  • Found that being married and having children put women at a disadvantage.

  • Found that sex differences in research productivity decline and can be attributed to differences in personal characteristics and structural features of employment.

Let me just emphasize this point: we have a temptation to try to find a single, simple explanation. There are two tendencies in finding simplistic explanations. Some scholars claim that everything is biology. Others claim that everything is discrimination. I think we should give up the naive idea that there is a single explanation.

—Yu Xie

SELECTIONS FROM THE QUESTION AND ANSWER SESSION

DR. KAMINSKI: Hello, I’m Deborah Kaminski from Rensselear Polytechnic Institute. I was fascinated by your idea that people could inadvertently decide not to perform as well on an exam because of the stereotypes. I’m wondering if that happens at the genius level as well? Perhaps there are so few women in the genius category, because genius is supposed to be male.

DR. SCHMADER: Yes, that’s a very good question. And part of the theoretical assumption is that these effects might be most profound or strongest for people who care the most about excelling in the domain. So, for those women who care the most, we should see the strongest effects. And if the women who care the most are the women who do the best, then it could explain why you see a

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

gap at the highest levels of achievement. There haven’t been studies that have systematically addressed that question.

DR. SPALTER-ROTH: Hi, I’m Roberta Spalter-Roth from the American Sociological Association. First, we have a poster at this meeting suggesting that there is a real relationship between productivity and motherhood, and that family leave policies are granted to those women who are already more productive. So, leave is given as a reward for productivity, rather than as it was designed, as a needs-based policy. Hence, it reinforces the cycle of high and low productivity.

The second thing is that implicit assumption test we took, I found that really strange. I’m not sure what the study does.

DR. BANAJI: Okay, fair enough. So, the first thing to point out is that the test has nothing to do with the accuracy with which you put things into the right category. We worked very hard to make it very clear what belongs where. To classify a name like Mary as female and Peter as male is not the hard part.

The test measures the difference in the time that it takes to make the association of gender group with a particular attribute in the first round [male-science, female-home], where it is mentally compatible in the directional stereotype. The second round is the less compatible one [female-science, male-home], because that’s not the stereotypic association.

With this group, not unlike others, the time interval difference between the first and second round was 700 to 1,000 milliseconds. That is a large statistical effect. That difference in time was substantial. It’s big enough that we don’t need a computer to measure it, a sundial will do. That’s how big these biases are. And it just shows something very simple, that two things that have come to be paired repeatedly in our experience are going to be responded to as if they were one.

DR. CHUCK: My name is Emil Chuck. I’m at Duke University and I’m also involved in the National Postdoctoral Association. One of the things we found is that expectations regarding mentoring are really, really important, whether it’s graduate students, postdocs or undergraduates, and play a significant role in whether people want to remain in the sciences. What do you think would be an effective means of reversing implicit biases in academe?

DR. FISKE: One of the things that we find in our broader work on stereotyping is that when people are in positions of power, they are very vulnerable to making prejudiced decisions about other people, because there is no feedback and very few consequences. I would argue that what you need to do is to build in accountability, so that training people effectively is part of how people are evaluated. You need to build people’s sense of being interdependent with their subordinates, and not just having total, absolute power over them. And you need to reinforce people’s values so that they are fair and unbiased. These three kinds of things about the relationship and the accountability and the values do help to overcome some of the implicit biases.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

DR. SCHMADER: It is really easy to set up mentoring programs that women are “forced” to be a part of. We have to be cautious that these programs are framed in a voluntary supportive way, as opposed to saying, we know you’re going to be having problems, and so here’s a mentor that can help you. Mentors are really important, but in some sense the presence and welcoming open kind of environment mentors create is maybe more important than having it done in a very institutionalized way that sends this subtle, subversive message that it’s expected that you will need mentorship.

DR. BANAJI: From what we have learned, the most important thing that we conclude is awareness. And not awareness in the old-fashioned sense that we need to go through diversity training once a year to know how to behave. If environments matter—and we have shown that implicit biases can be shaped by something as simple as who you see in front of you—then the mode for changing behavior needs to be changed.

Frank Dobbin, a sociologist at Harvard, has written a paper in which he analyzes 800 organizations from the 1970s on, and looks to see what happens to the diversity of the workforce in companies after diversity training was implemented. It turns out that the workforce becomes less diverse. There are many different reasons why this might happen. There are people who argue that this could be a backlash. Others, like me, think that it’s a sense of, we checked the box off. I went to diversity training. And as a result, you don’t bring to bear that particular lesson when making evaluations, because training and evaluations are mentally separate, physically separate, socially and psychologically removed.

Bias needs to be thought of in the same as we think about our physical selves. We know that exercising a lot the day after Thanksgiving dinner is not going to be sufficient. The change in body shape comes from this slow, hard work. And I think that the removal of bias needs to be thought of in this kind of incremental way, rather than the single one-shot thing.

Frank Dobbin found that mentoring programs work somewhat, and networking works somewhat, unlike diversity training. But what really works is an ombudsperson whose job it is to hold people accountable, and to ask the questions, and then old-fashioned affirmative action.

DR. VOGT: Christina Vogt, National Academy of Engineering. We know stereotype threat exists also between groups of males. Some groups will threaten white males. There is always a pecking order.

DR. SCHMADER: Stereotyped threat effects are situational. What that means is that any one of us in this room could experience stereotype threat if put in the right type of situation. You only have to think about what kind of group membership you might have that in a certain context would make you negatively stereotyped. So, as was mentioned, white men can show lower performance on a math test if they are told that the purpose of the test is to compare how whites do relative to Asians. Stereotype threat is a contextual effect, it is just that for women and minorities the context is more often chronically present.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

DR. MANDULA: Barbara Mandula, EPA. This is a question for Toni about one of her early graphs. What you didn’t mention was that men’s performance went down when the task became an exercise rather than a test.

DR. SCHMADER: Members of advantaged groups can get some benefit from positive stereotypes. In any given individual study it often appears that men, when told the task is a lab exercise, suffer some performance decrement, or at least their performance is higher when they think it’s an intellectual test. There is a meta-analysis that suggests that overall that effect is reliable, but the effect size isn’t nearly as large as the threat effect that we see for women.

DR. GROSZ: Barbara Grosz, Harvard University, and also on the committee. I have a question of clarification for Yu Xie. You said that the greatest drop in participation was between high school and the bachelor’s degree. But that conflicts with what other data I know that at the in the life sciences, women are more than 50% of the undergraduate students at many schools.

DR. XIE: The results that I presented were based on old data of all sciences. So, it is true that especially in recent years women’s representation in biological sciences has been pretty high. In this particular analysis, it was a combined definition of science and engineering.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL 3
ORGANIZATIONAL STRUCTURES

   

 Panel Summary

 

 

   

  Moving Beyond the “Chilly Climate” to a New Model for Spurring Organizational Change
Joan Williams, Center for WorkLife Law, University of California, Hastings College of the Law

 

 

   

  Economics of Gendered Distribution of Resources in Academe
Donna Ginther, Department of Economics, University of Kansas

 

 

   

  Bias Avoidance in the Academy: Challenges, Opportunities, and the Value of Policies
Robert Drago, Departments of Labor and Women’s Studies, Pennsylvania State University

 

 

   

  Gendered Organizations: Scientists and Engineers in Universities and Corporations
Joanne Martin, Graduate School of Business, Stanford University

 

 

   

  Selections from the Question and Answer Session
Moderated by committee member Lotte Bailyn

 

 

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL SUMMARY

The panel examined how the features of organizations, their rules, and their policies interact with gender to impose unequal demands or requirements on women.

Joan Williams discussed a new model for examining gender bias against women in academe that moves beyond the traditional concept of a “chilly climate.” This model aims to describe in concrete terms the unrecognized patterns of stereotyping that negatively affect women in academe, to train people to recognize this bias for what it is, and to highlight an important new trend in federal employment lawsuits of which employers must be mindful.

Williams explained that we must use new metaphors and specific descriptions when naming bias, because how an issue is framed affects how it can be dealt with. Calling bias “subtle,” “unconscious,” or “implicit” makes it difficult to hold people responsible for the bias. Calling bias “unexamined,” on the other hand, places the responsibility on the person who holds the stereotype.

Williams discussed the well-known concept of the glass ceiling and then introduced an important new trend in employment discrimination law: the concept of the “maternal wall.” Also known as “family responsibilities discrimination,” the maternal wall penalizes mothers, potential mothers, and fathers who seek an active role in family care. Mothers who face the maternal wall experience gender stereotyping in the way jobs are defined, in the standards to which they are held, and in assumptions that are made about them and their work—for example, a man who is absent is assumed to be presenting a paper, whereas a woman who is absent is assumed to be taking care of her children. They also face negative competence assumptions—assumptions that they are less competent or committed than other workers. In light of such bias, the maternal wall often pits women against women—for example, when women without children fear that making way for mothers may reinforce negative stereotypes about all women. Fathers, too, Williams explained, suffer from family responsibilities discrimination: As compared to mothers, fathers who take a parental leave or even a short leave to deal with family matters often receive fewer rewards, lower performance ratings, and are viewed as less committed.

Williams concluded by discussing the federal employment laws under which employees can sue—and employers can be sued—for maternal wall discrimination, including Title VII of the Civil Rights Act of 1964, the Pregnancy Discrimination Act, and the Family and Medical Leave Act. In sum, Williams argued, it is time to move beyond talking about what is actually gender bias as merely a “chilly climate” for women in academe. She argued for the need to create a new model for spurring institutional change that specifically names and identifies unexamined bias and considers the risk of family responsibilities discrimination lawsuits.

Donna Ginther examined the economic aspects of female academic careers, noting that a salary gap exists between male and female senior science professors

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

and that marital status and parental status are major factors in determining career outcomes for women scientists. Ginther emphasized the importance of disaggregating the data by field and rank and of placing gender differences in a broader context. Women’s representation in science varies by field: significant numbers of women are in the life sciences, much smaller numbers are in the physical sciences and engineering, and over half of the doctorates in the social sciences, except for economics, now go to women.

The percentage of tenured faculty who are female has lagged behind the percentage of women who earn doctorates in all fields. This gap may result from gender differences in hiring, in obtaining tenure, or both. In the social and life sciences, being female significantly and negatively influences women’s chances of being in tenure-track jobs within 5 years of earning the PhD. Like Xie, Ginther found family status a highly significant factor in determining career progression: single women scientists were 16% more likely than single men to be in tenure track jobs 5 years after the PhD, and married women with children 45% less likely than married men with children. Marriage has a positive and significant impact of 22% on men getting a tenure track job whereas the effect of marriage for women is much smaller. Children, especially young children, significantly decrease the likelihood of women obtaining a tenure track job between 8% to 10% in all science fields, while having no significant impact on men. Ginther attributes these differences to the coincident timing of the tenure and biological clocks and women’s role as the primary caregiver for children.

Ten years past the PhD, women faculty in engineering and the life sciences are marginally more likely than men to be promoted to tenure, but in other fields, female promotion is less likely. A significant salary gap exists between men and women at the full professor level but not at other ranks. Neither differences in family status nor productivity explain that discrepancy, nor does the imperfect competition in the academic labor market. The general pattern is consistent with the model that suggests that male advantage accumulates in the scientific world, with men consistently receiving greater rewards than women for accomplishments. Further research—with better data on discrimination and on scientists’ research, resources, job prestige and other factors—is needed, Ginther said.

Echoing themes from Williams’ talk, Robert Drago discussed the pervasive bias against caregiving that exists in many academic institutions and the strategies that academics use to try to prevent it from damaging their careers. “Productive bias avoidance” involves finding ways to minimize family commitments. The most obvious method is to have no children, and female academics indeed do have fewer children than members of other professions, such as female doctors or lawyers. Some 17% of women at research universities stay single, as opposed to 10% of men. In addition, 30% of women but only 13% of men have limited the number of their children to avoid career damage; 18% of women but 8% of men have delayed their second child for the same reason. Given the long periods of training in many sciences, that often pushes the second child into the mother’s forties.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

“Unproductive bias avoidance” involves efforts to deflect attention from one’s family responsibilities and is “a new source of gender inequity.” At research universities, more women than men decline to reduce their workload or to take needed parental leave to care for family, they miss children’s events, and they return to work earlier than they desire after the birth of a child.

Joanne Martin examined how ostensibly gender-neutral organizational practices can disadvantage academic women. The 7- to 10-year tenure clock often imposes a severe conflict with the biological clock that is limiting women’s reproductive years. Requirements to travel, to relocate, and to work long days are often more difficult for women, particularly those with family responsibilities. Performance evaluations based on subjective criteria often yield biased assessments. Exercising significant leadership is often more problematic for women because traditional feminine behavior is judged as “not tough enough,” but assertive behavior inspires dislike.

The traditional approach that universities have used to open careers to women has been to merely hire women, Martin said. That has been presumed to give woman an “equal opportunity” to succeed. Because of gendered requirements and cultures of supposedly gender-neutral organizations, however, it produces high female attrition at every level, leaving only a handful of pioneers who manage to reach the top. Those pioneering women suffer problems including isolation, extreme visibility, unreliable feedback that is either too positive or too negative, and feelings of inauthenticity, which are especially severe for women in minority groups. The classic approach to these problems is to “fix the woman,” but a more effective approach is to tailor responses to the characteristic issues produced at tipping points. Institutional interlocks among numerous organizations, such as families, schools and employers, require a coordinated effort and intra-organizational interventions to remove gender burdens.

MOVING BEYOND THE “CHILLY CLIMATE” TO A NEW MODEL FOR SPURRING ORGANIZATIONAL CHANGE48

Joan Williams

Center for Work-Life Law, University of California, Hastings College of the Law


Joan Williams discussed a new model for spurring organizational change that moves beyond the concept of a “chilly climate” for women in academe to identify unexamined bias and consider a new trend in federal employment discrimination lawsuits.

48

For more detail, figures, and references, see the paper by Joan Williams in Section 2.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

The challenge in science, as expressed by earlier speakers, is that gender bias “[does] not look like what we thought discrimination looked like.”49 The traditional language for talking about the position of women in science calls for eliminating the chilly climate by creating a culture of faculty support.50

In fact, the chilly climate often stems from documented patterns of gender stereotyping, some of which is outright illegal. The Center for WorkLife Law51 (which Williams founded and directs) proposes a new model for creating institutional change. This model aims: first, to describe in readily understandable terms the patterns of stereotyping that create the chilly climate; second, to teach people to spot bias as it is happening; and third, to highlight the importance of a new trend in federal employment law of which institutions should be mindful.

In addition to glass ceiling discrimination and sexual harassment, is a trend called the “maternal wall” or “family responsibilities discrimination” (FRD), which penalizes mothers, potential mothers, and fathers who seek an active role in family care. The Center for WorkLife law has documented over 600 of these cases. One of the things emerging in these maternal wall cases is an alternative to the traditional way of proving discrimination. Traditionally, you would prove discrimination through use of a comparator, comparing the woman to a similarly situated man. But two recent maternal wall cases have had extraordinarily important holdings: one held that discrimination cases may also be proved through stereotyping evidence, even if you don’t have a comparator;52 another case said that cognitive bias—in that case attribution bias—was recognized as a form of stereotyping.53

Given the new importance of stereotyping evidence in discrimination law, we have thought a lot about issues of framing. We have heard some of the traditional language this morning—“subtle,” “unconscious,” “implicit” bias. Some of that language is not particularly helpful in the legal context. First of all, if this bias is so subtle, is it fair to hold people responsible legally? Secondly, if it’s unconscious, how can it meet the standard for intentional discrimination? “Implicit” doesn’t have those problems, but it’s not sufficiently transparent really for use either in public education or certainly in the courtroom.

49

Massachusetts Institute of Technology (1999). A study on the status of women faculty in science at MIT. The MIT Faculty Newsletter 11(4):14-26, http://web.mit.edu/fnl/women/women.html.

40

Stanford University (1993). Report on the provost’s committee on the recruitment and retention of women faculty. M. Strober, Chair.

51

The Center for WorkLife Law is housed at UC Hastings College of the Law; http://www.worklifelaw.org.

52

Back v. Hastings-on-Hudson, 365 F.3d. 107 (2d Cir. 2004).

53

Lust v. Sealy Inc., 383 F.3d 580 (7th Cir. 2004).

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

The new terminology that we have suggested is the terminology of “unexamined” stereotyping. Note how “unexamined” shifts the burden of proof. If it’s unconscious, “oh my gosh, I didn’t know.” But if it’s unexamined and you are clueless, whose fault is that? This new terminology also highlights that although stereotype activation is automatic, as Mahzarin Banaji pointed out this morning, stereotype application can be controlled.

—Joan Williams

WorkLife Law uses the law proactively to spur institutional change and organizational change by influencing intermediaries. In this case, human resource professionals are extremely important. This process is already underway with respect to the maternal wall. For example, one management side firm advised employers not only to avoid stereotyping, which is what the cases required, but also to consider offering telecommuting, flex time, and proportional pay and benefits for part-time work.54 Once the potential for legal liability is established, often intermediaries institute the norms in a quite sweeping way.55 But to use this new legal trend to spark organizational change, these stereotyping patterns must be easy to spot.

We all know about the glass ceiling. The glass ceiling penalizes women simply because they are women, and it does so in two distinct ways. Some of the patterns make it harder for women to be perceived as competent, which, of course, makes it harder to succeed. For example, when women are judged on accomplishments, but men are judged on potential; performance evaluations are gender-biased; double standards are applied to men and women; women must be superstars to survive while men can be average; women are kept out of the loop; jobs are defined in terms of masculine patters; or women must play certain roles in order to accepted. The other patterns penalize women for being too competent, which again makes it harder to succeed. For example, when women are considered aggressive, while men are considered assertive, but women are also penalized for not being aggressive enough; women are considered shameless self-promoters, while men are considered to know their worth; successful women are sexually harassed.

In addition to the glass ceiling is the maternal wall, which penalizes mothers, women perceived to be potential mothers (which is often most women), and also

54

TP Krukowski, SC Costello (2002). Discrimination: A glass ceiling for parents? Washington, DC Employment Law Letter 3(6):1, http://www.hrhero.com/dcemp.shtml.

55

EE Kelly and F Dobbin (1999). Civil rights law at work: Sex discrimination and the rise of maternity law policies. American Journal of Sociology 105:455-492; LB Edelman (1997). Legal ambiguity and symbolic structures: Organizational mediation of civil rights law. American Journal of Sociology 97(6):1531-1576; R Stryker (2003). Mind the gap: Law, institutional analysis, and socio-economics. Socio-Economic Review 1:335-367.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

fathers who seek an active role in family care. That’s why the more technical name for the maternal wall is family responsibilities discrimination. It is linked to being the primary caregiver or providing care to family members.

Here is an extremely important demographic fact: 95% of mothers aged 25-44 work less than 50 hours a week year round. So, basically all you have to do is define full-time as 50 or more hours a week to come close to wiping mothers, and therefore three-quarters of women, out of your labor pool.

—Joan Williams

Maternal wall patterns of discrimination include: jobs defined around masculine patterns (for example, selecting workers who are “single-minded”); role incongruity (for example, she cannot be both a mother and a full-time academic); prescriptive stereotyping, whether benevolent or hostile (for example, she shouldn’t worry about her work, but should just focus on her family); attribution bias (for example, an absent man is assumed to be presenting a paper, but an absent woman is assumed to be taking care of her kids); and leniency bias (for example, women are held to higher standards than men).

Another key component of maternal wall patterns of discrimination is negative competence assumptions about mothers. A 2005 study found that “relative to other kinds of applicants, mothers were rated as less competent, less committed, less suitable for hire, promotion and management training, and deserving of lower salaries.”56

Another dynamic that is not very well understood is what Williams terms gender wars—tensions among women themselves. This is an extremely acute problem in academics, because 50% of women academics in science have no children. Many of these women are “child-free”—meaning that they do not want children. These women may feel anxiety about making way for mothers out of fear that having to accommodate mothers reinforces negative stereotypes about all women. On the other hand, many of these women are “child-less”—meaning that they want or wanted, but do not have, children. These women may think, “Why should she have it all, when I had to sacrifice so much?” Thus, the maternal wall very often pits women against women. It is important to recognize that this phenomenon is actually a result of gender discrimination, not proof that discrimination against mothers “is not a gender problem.”

There is also family responsibilities discrimination against fathers. In one study, when compared to mothers, fathers who took parental leave were recommended for fewer rewards and viewed as less committed, and fathers with even a

56

SJ Correll and S Benard (2005). Getting a job: Is there a motherhood penalty? Presentation at American Sociological Association Annual Meeting, August 15, 2005, Philadelphia, PA. http://sociology.princeton.edu/programs/workshops/Correll_Benard_manuscript.pdf.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

short work absence due to a family conflict were recommended for fewer rewards and had lower performance ratings.57 In academics this translates into what Robert Drago calls “unproductive bias avoidance”—for example, in the case of an untenured professor who told his mentor that he did not dare even to ask about parental leave, much less take it, for fear his career would be over.

People need to understand their rights as employees, and institutions need to understand the consequences of committing family responsibilities discrimination: potential lawsuits. Maternal wall cases have been brought under a number of legal theories in federal employment law, including the following:

  • Disparate treatment under Title VII of the Civil Rights Act of 1964—for example, a female professor who was treated worse and subject to greater scrutiny by colleagues after she had a baby

  • Retaliation under Title VII of the Civil Rights Act of 1964—for example, when a woman faces negative career consequences for protesting a denial of maternity leave or asking to stop the tenure clock while she is on maternity leave

  • Interference with rights under the Family Medical Leave Act (FMLA)— for example, a female professor who was pressured to reduce the amount of time she took on maternity leave (In certain circumstances, the FMLA provides 12 weeks of unpaid leave and guaranteed reinstatement; one study showed that 40% of academic women surveyed returned to work from leaves earlier than they wanted to.58)

  • Violation of the Pregnancy Discrimination Act (PDA)—which protects employees from discrimination based on pregnancy, childbirth, and related medical conditions and requires that pregnancy be treated the same as other temporary disabilities.

According to a recent study,59 over one-third of academic institutions had family or child rearing policies that probably violate the Pregnancy Discrimination Act (PDA). This, of course, places mothers in extremely awkward positions. They have to impose on their colleagues for leave that they should be entitled to, and they have to fight political battles to get that leave.

—Joan Williams

57

CE Dickson (2003). The impact of family supportive policies and practices on perceived family discrimination, (dissertation).

58

MA Mason (2003). UC Berkeley faculty work and family survey: Preliminary findings, http:// universitywomen.stanford.edu/reports/UCBfacultyworknfamilysurvey.pdf.

59

S Thornton (2003). Maternity and childrearing leave policies for faculty: The legal and practical challenges of complying with Title VII. University of Southern California Review of Law and Women’s Studies 12(2):161-190.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

In conclusion, Williams called for moving beyond talking about gender bias as merely a “chilly climate” for women in academe. She argued for the need to create a new model for spurring institutional change that specifically names and identifies unexamined bias and considers the risk of family responsibilities discrimination lawsuits against employers.

ECONOMICS OF GENDERED DISTRIBUTION OF RESOURCES IN ACADEME

Donna Ginther

Department of Economics, University of Kansas


Donna Ginther focused her comments on the economics of gender differences in employment outcomes in academia. She observes gender and race differences in employment outcomes. From the economics perspective, gender differences in employment outcomes result from a variety of factors besides discrimination.

  • Differences in productivity. Are men more productive than women?

  • Differences in choices. Women’s choice of occupations and jobs affect their employment outcomes.

  • Imperfectly competitive markets. Becker’s theory of discrimination was predicated on perfect competition; however, universities are not perfectly competitive. In fact, they have monopsony power where universities act as single purchasers of academic labor and have more market power than employees.

  • Job matching. This theory suggests that differential employment outcomes result from one group performing better on the job than another.

If none of those theories explains the employment-outcome difference, then what is left over could be attributed to discrimination. That said, economists, on average, do not believe that discrimination explains observed gender differences in employment outcomes.

There is no single scientific labor market. As a result, we need to disaggregate the data. We need to look at the different scientific labor markets because they have different outcomes for women. We need to make comparisons across fields to understand the status of women relative to one another. Hiring, salary, and promotion outcomes are interrelated. You cannot look at one without considering the others.

—Donna Ginther

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

BOX 1-3

The Economist’s Perspectivea

  • Economists view the world as being organized by markets, and assume that markets matter. Thus, supply and demand determine employment outcomes.

  • Economists assume that equally productive workers will be paid the same. Thus, we should not observe gender differences provided that men and women are equally productive.

  • Discrimination exists, but market competition will remove it. In other words, if you have a perfectly competitive market, some employer can exploit the fact that it is not paying women enough, hire only women, and then become more profitable.

  

aGary Becker won the Nobel prize in economics in part for his theories of discrimination. GS Becker (1971). The Economics of Discrimination. Chicago: University of Chicago Press.

What explains the differential employment outcomes in science and engineering fields? To examine hiring, promotion, and salary, Ginther used the 1973-2001 waves of the Survey of Doctorate Recipients (SDR).60 Because the SDR is longitudinal, respondents can be tracked over time. She split the data into fields: life sciences (agriculture, food science, and biology), physical sciences (chemistry, earth sciences, physics, and mathematics), engineering, and social science (economics, psychology, sociology, anthropology, and political science). Control variables include the demographic variables of gender, race, and age; academic field and degree; rank and tenure status; and institutional characteristics (Carnegie rankings, public or private). She included control variables for primary work activities which indicate whether the respondent primarily teaches, does research, manages, or engages in another activity. She also included an indicator for whether a respondent receives government support and some measures of publications.

Ginther’s research shows again that women’s representation depends on field (Figure 1-7). Since the 1970s there has been tremendous growth in the number of doctorates awarded to women. In the physical sciences, there is still anemic representation of women, but in the life sciences and the social sciences (except in economics) half or more of doctorates are awarded to women.

60

From 1987 to 1995 the SDR also followed people in the humanities; for these years, Ginther includes humanities in her analysis.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-7 Percentage of doctorates granted to females.

SOURCE: National Science Foundation (1974-2004) Survey of Earned Doctorates. Arlington, VA: National Science Foundation.

However, even in life science and social sciences, the percentages of women tenured is low. For example, in social science, over 50% of the doctorates have been women since 1990, but in 2001 only 28% of tenured faculty were women (Figure 1-8).

Does that discrepancy result from differences in hiring or from differences in promotion? Ginther examined gender differences in tenure-track jobs within 5 years of earning a PhD and measured the effect of being female on getting a tenure-track job. She found that single women are significantly more likely than single men—by 11 to 21%—to have tenure-track jobs. Marital status and presence of children drive this result and explain the leaky pipeline.

Marriage has a positive and significant impact of 22% on men getting a tenure-track job whereas the effect of marriage on women ranges between 0 and 8% for all science, life science, and social science fields. Children, especially young children, significantly decrease the likelihood of women obtaining a tenure-track job between 8 to 10% in all science fields, life science, and social science while having no significant impact on men.61

61

MA Mason and M Goulden (2002). Do babies matter? The effect of family formation on the lifelong careers of academic men and women. Academe 88(6):21-27, http://www.aaup.org/publications/Academe/2002/02nd/02ndmas.htm.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-8 Percentage of tenured faculty who are women.

SOURCE: National Science Foundation (1973-2001). Survey of Doctoral Recipients. Arlington, VA: National Science Foundation.

The differential impact of marriage and children may be explained by a number of factors. Women may choose to have children instead of pursuing an academic career because of the coincident timing of the tenure and biological clocks. The dual career problem may also play a role. Career hierarchies in marriage often result in the husband’s career taking precedence over the wife’s career. If it is difficult to obtain two tenure-track jobs, she may choose to have children instead of investing in her career.

In particular, with respect to hiring policies, the dual career problem should be taken seriously. There is an economic advantage for a university to hire couples, because couples are less mobile. The university can probably keep them longer.

—Donna Ginther

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Ginther also examined gender differences in promotion 10 years past the PhD. Overall, she found a 1.4% gender difference in promotion to tenure 10 years past PhD. The gender promotion gap varies significantly by field. In the social sciences, excluding economics, women are 8% less likely to have obtained tenure; in the life sciences, 2% more likely; in the physical sciences 3% less likely; in engineering, 4% more likely; in humanities, 8% less likely. Economics is the outlier, in which there is a 21% promotion gap in favor of men.

After examining hiring and promotion, Ginther considered the gender salary gap. In the economy as a whole, women earn 75 cents for every dollar a man earns. In engineering, women earn 80 cents for every dollar. Previous research has shown that if academic rank is factored in, the gender differences in salary go away, except for full professors. What is an 18% difference favoring men in science as a whole falls to just over 5% in science for assistant professors, even less for associate professors. For full professors there is a 13.2% salary gap. One-third of the 13.2% salary gap is attributable to valuing the observable qualifications of women differently than men. Across the campus in the humanities, there is essentially no salary difference at any level. Something is going on in the humanities and the social sciences relative to science. For some reason, there are huge salary discrepancies at the full-professor rank in the sciences but not in the social sciences or humanities.

What are the economic explanations for the salary gap? It is not the result of marriage and children, except in the life sciences. Women are more productive on the average than men at Research I institutions; productivity is not explaining the gap. The salary gap is probably not the result of monopsony in the academic labor market. We also can dismiss the explanation that women are not good scientists, because they would not be full professors if that were the case.

What I find is that the salary gap is explained largely by gender differences in work experience and that men are rewarded more than women. That is consistent with the cumulative advantage model.

—Donna Ginther

To address outstanding questions, Ginther recommended improving the quality of data. She suggested building on existing datasets, including the SDR and the National Institutes of Health Consolidated Grant File. The postdoctoral process should be examined because it seems to be a key point at which women are dropping out. In particular, the SDR should add questions on publications and citations, grant awards, laboratory space, number of graduate students supervised, and a special module on postdoctorates. She called for additional questions on spouses—their education, their employment, their earnings, and how much child care time is allocated. She also urged universities to undertake a systematic review of academic salaries.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
BIAS AVOIDANCE IN THE ACADEMY: CHALLENGES, OPPORTUNITIES, AND THE VALUE OF POLICIES

Robert Drago

Labor Studies and Women’s Studies, Pennsylvania State University


Robert Drago discussed caregiving bias avoidance62 in the academy. That motherhood is a serious problem for professional advancement in academe is shown in Figure 1-9. The data show the percentages of women faculty, doctors, or lawyers with a baby (0-1 yrs old) in the household. The women academics are having fewer babies than the doctors or lawyers. Academe is obviously a tough sector to work in.

Another study63 suggests that there is a bias against caregiving in the professional workplace. It affects women more than men, partly because of stereotyping, but anybody who exhibits symptoms of caring for family will be penalized or experience bias in the workplace, and that leads to the new glass ceiling, the maternal wall.

Drago and colleagues performed a series of focus groups with faculty parents at Pennsylvania State University and found evidence of caregiving bias. But there was more evidence of what they came to call bias avoidance. That is, faculty are smart enough to figure out that they are going to run up against biases, so they find strategies to avoid them.

They categorized two types of strategies: productive and unproductive. In productive bias avoidance you find ways to minimize family commitments to create more time for career—having fewer children than you wanted, delaying having children, buying wife-replacement services, and so on. These strategies are productive, because they free up time. Productive bias avoidance may be efficient, but it is inequitable. That is, it is not distributed equally across genders, so it is not fair. In unproductive bias avoidance, you ignore your family commitments, which is both inefficient and inequitable. Unproductive bias avoidance has no general rationale and is a game that has unknown rules. That is, you can not ask, Will I experience bias against caregiving if I have a child? To do so, you have to admit that you care about children, and this might potentially write off your career.

With those initial results, Drago and colleague Carol Colbeck did a national study of faculty in chemistry and English at 507 schools, including all the

62

Kathleen Christianson at the Sloan Foundation coined the term bias avoidance, and it comes out of research by Joan Williams.

63

JC Williams (2001). Unbending Gender. Why Family and Work Conflict and What to Do About It. New York: Oxford University Press.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-9 Women fast-track professionals with babies in the household, by age of professional.

SOURCE: US Census, 2000 Public Use Microdata 5% Sample, prepared by M Goulden.

BOX 1-4

Bias Avoidance Behaviorsa

Productive Bias Avoidance

Men

Women

Stayed single to achieve academic success.

10 %

17 %

Limited the number of children—that is had fewer children than desired—to achieve academic success.

13 %

30 %

Delayed having a second child until after tenure.b

8 %

18 %

Unproductive Bias Avoidance

Men

Women

Did not take a reduced load when needed for family commitments.

19 %

30%

Did not take parental leave even though it was needed.

27 %

31 %

Missed some of the young children’s important events, because wanted to be taken seriously.

34 %

40 %

Came back too soon after a new child.

12 %

46 %

  

aSurvey results presented are restricted to Research I institutions.

  

bGiven that on average, if US women are 34 when they receive their PhD, that puts the second childbirth in a woman’s forties. Less than 1% of all live births are to women over the age of 40 even today. So this strategy does not always work.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Research I universities.64 They did 10 case studies and shadowed 13 faculty for about 650 hours. They asked subjects whether they engaged in avoidance behaviors and if so, whether for career success or to appear committed or to be taken seriously (Box 1-4).

Avoidance behaviors are distributed unevenly. They appear to be a new source of gender inequity not seen in salary or promotion figures. Women are having to engage in these largely hidden behaviors. They can not ask anyone whether they need to engage in the behaviors, because of how the “game” is structured. Bias avoidance more often affects women and is reduced by supervisor support.65 After introducing a control for positive affect, Drago found that upbeat, happy people engage in bias avoidance behaviors less often.

What are the returns to avoidance behaviors? Are people getting tenured earlier, or were they reducing the time between PhD and the point of tenure? For women who engaged in bias avoidance behaviors, time to tenure was reduced by productive bias avoidance behavior; the age at tenure was also significantly reduced.

There are payoffs for avoidance behaviors. With productive bias avoidance, that is no surprise. You are making more time by not having children or delaying having them. You should get tenure earlier and move through more quickly. The real surprise is that unproductive bias avoidance behaviors—which do not free up any time and may even be increasing the burden of trying to handle work and family— for men reduced the time to tenure by over a year and for women reduced the age at tenure by over a year. Playing the game has a payoff.

—Robert Drago

To address the question of whether institutional policies reduce the incidence of bias avoidance, Drago matched the Mapping Project data to a survey of 250 schools’ work-life policies performed by Carol Hollenshead and Beth Sullivan. The policies included paid maternity leave, reduced hours, child and elder care, flexible hours, and some connection between policies for faculty, staff, and students. Drago created a scale out of the eight bias avoidance behaviors and correlated

64

R Drago, C Colbeck, KD Stauffer, A Pirretti, K Burkum, J Fazioli, G Lazarro, and T Habasevich (2005). Bias against caregiving. Academe. Sept/Oct. http://www.aaup.org/publications/Academe/2005/05so/05sodrag.htm. Research I university was a category formerly used by the Carnegie Classification of Institutions of Higher Education to indicate those universities in the United States which received the highest amounts of Federal science research funding. The category is, since 2000, obsolete, but the term is often still used.

65

R Drago, C Colbeck, KD Stauffer, A Pirretti, K Burkum, J Fazioli, G Lazarro, and T Habasevich (2005). Bias against caregiving. Academe, http://www.aaup.org/publications/Academe/2005/05so/05sodrag.htm.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

them with work-life policies. Negative correlations would indicate that with more work-life policies there is less bias avoidance. However, instead of negative correlations they found positive correlations between policies and bias avoidance for not taking parental leave, indicating that the more policies that existed, the less they were used.

I got to thinking, well, which universities have gotten on the Working Mother Top-100 list? Harvard, Stanford, and MIT. Those are the only three schools. They have great policies, but they are extremely tough places to work for parents. If we reexamined the data and focused on the subsample of women faculty at research universities, all fairly tough schools to work at, all of a sudden we start seeing the negative correlations that we expected.

—Robert Drago

GENDERED ORGANIZATIONS: SCIENTISTS AND ENGINEERS IN UNIVERSITIES AND CORPORATIONS

Joanne Martin

Graduate School of Business, Stanford University


Joanne Martin shifted the focus from documentation of discrimination to institutional change efforts.

The old-fashioned approach to changing gender inequality was to hire more women, who would supposedly have equal opportunities to succeed. The problem was that this strategy was based on a false assumption: that organizational structures and cultures are gender-neutral. We know they are not. Many things that look gender-neutral, like the requirement that you have to travel and present your research or geographically relocate,66 are tougher for women on the average than for men, particularly for those women with caregiving responsibilities.

—Joanne Martin

66

AR Hochschild (1997). When work becomes home and home becomes work. California Management Review 39(4):79-97. Other practices include tenure-biological clock conflicts, subjective criteria in performance appraisals (C Wenneras, and A Wold (1997). Nepotism and sexism in peer-review. Nature 387:341-343; M Heilman, AS Wallen, D Fuchs, and MM Tamkins (2004). Penalties for success: Reactions to women who succeed at male gender-specific tasks. Journal of Applied Psychology 89:416-427, long hours, and acceptance of women in leadership roles (KH Jamieson (1995) Beyond the Double Bind. New York: Oxford University Press).

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

BOX 1-5

Pioneers Have Predictable Problemsa

  • Exclusion and isolation.

  • Extreme visibility, particularly for woman of color. Every failure and every mistake is public. The good news is, if you succeed, that also is highly visible.

  • Unreliable performance feedback. Like flying an airplane without a gyroscope, you cannot rely on the feedback you are getting, and so you rely on your own sense of where you are doing well and where you are doing poorly.

  • Very strong probability of being unfairly promoted and unfairly paid.

  

aRM Kanter (1977). Men and Women of the Corporation. New York: Basic Books; J Crocker and KM McGraw (1984). What’s good for the goose is not good for the gander: Solo status as an obstacle to occupational achievement for males and females. American Behavioral Scientist 27(3):357-369.

The first-stage remedy of add women and stir is often unsuccessful in part because organizational structures and policies are gendered, and women leave more than men at each level of the promotion hierarchy.67 At the highest levels, only women pioneers remain. This will be the situation for years and years for women scientists and engineers.

In addition to the problems faced by pioneers, another problem, which has received less attention in the literature, is women’s discomfort in male-dominated cultures.68 Inauthenticity problems are heightened when one is a woman of color.69 The result is that women, particularly women of color, quit.

The classic remedy is to fix the women. Training women to be better leaders, to be more assertive, and to have the same kinds of tough

67

J Acker (1990). Hierarchies, jobs, bodies: A theory of gendered organizations. Gender and Society 4(2):139-58; AJ Mills and P Tancred (1992). Gendering Organizational Analysis. London: Sage Publications.

68

J Martin and D Meyerson (1998). Women and Power: Conformity, Resistance, and Disorganized Coaction. In Power and Influence in Organizations, Eds. RM Kramer and MA Neale. San Francisco: Sage Publications.

69

AM Morrison (1992). New solutions to the same old glass ceiling. Women in Management Review 7(4):15-19; E Bell and SM Nkomo (2001). Our Separate Ways: Black and White Women and the Struggle for Professional Identity. Boston: Harvard Business School Press.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

negotiating skills that men have encourages women to act like men and leaves intact the inauthenticity problem. Such training programs may be needed in the short term, but if inauthencity feelings are a real reason why women are dropping out, fixing the women won’t fix the problem.

—Joanne Martin

A better approach is to study the kinds of problems that occur as the percentage of women in an occupation changes. Those kinds of problems are actually pretty well understood by organizational researchers.70 There are three tipping points where the nature of the problems experienced by women changes drastically. The first, and the one that is most relevant in our lifetimes for women who are scientists and engineers, is the point at which the glass ceiling starts to break, and women start to enter into higher level positions, for example, department chair, dean, or college president. At 18-22% female, there is a critical mass. Women start to get leadership positions, and sometimes they get together, discuss their common interests, and organize collectively, for example for better work-family policies. So far, so good; but there is also a problem with this first tipping point: it is the first point at which white male backlash starts to appear. Women are starting to be a threat; as a result, they get resistance, sometimes overt resistance, from men.

The second tipping point is a temporary nirvana. When you have 40-60% women in an occupation, gender issues tend to disappear. People simply don’t worry about gender issues, and evidence of discrimination and unfair pay and promotion policies are gone. It is a temporary nirvana; it doesn’t last long. It quickly—amazingly quickly—switches to the third tipping point: occupational sex segregation.71 That occurs when an occupation is either 90% female or 90% male.

The vast majority of occupations in the United States are sex segregated. In medicine, neurosurgery is still very close to being an all-male occupation, whereas pediatrics is beginning to be dominated by women. When Stanford did its big study in 1993, it found that almost all the hard sciences and engineering specialties were virtually all male, with one exception—biology. Occupational sex segrega-

70

TF Pettigrew and J Martin (1987). Shaping the organizational context for Black American inclusion. Journal of Social Issues 43(1):41-78; M Gladwell (2000). The Tipping Point: How Little Things Can Make a Big Difference. Boston: Little, Brown.

71

MH Strober and C Arnold (1987). The Dynamics of Occupational Segregation Among Bank Tellers. In Eds. C Brown and J Pechman, Gender in the Workplace. Washington, DC: Brookings Institution; F Conley (1998). Walking Out on the Boys. San Francisco: Farrar, Straus and Giroux; Stanford University Committee on Recruitment and Retention of Women, 1993; JC Touhey (1974). Effects of additional women professionals on ratings of occupational prestige and desirability. Journal of Personality and Social Psychology 29:86-89.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

tion is a crucial issue because, in the United States at least, female jobs have lower pay and lower prestige.

We need to tailor and plan organizational change programs to fit the tipping-point stage. What you do for a biology department is going to be very different from what you do in a medical school which in turn will depend on whether you are working on the neurosurgeons.

—Joanne Martin

There are standard things that you do in an organization when you are just starting to try to get the ball rolling: You start counting things—not just personnel and pay, but also the number of square feet of a laboratory space.72 Networking and mentoring are also classic strategies at this stage. Access to effective mentors is very important, particularly for minority-group women.73

Next, we need to de-gender organizations. The change strategies here are a little more ambitious. First is the 7-10 year tenure clock. Scientists and engineers in academe and corporations are under similar time demands. We know that the tenure clock and the fast-track schemes are harmful to women because they conflict with the biological clock, that is, the number of years that women have to have children before the danger of birth defects gets large.

Young women are telling us that they do not want to be like the pioneer generation, the super women who have gotten very tired trying to balance work and family. For example, at the Harvard and Stanford business schools, 70% of the female MBAs who graduate stop out of the workforce; of the female business school graduates from the Harvard classes of 1981, 1986 and 1991, only 38% are still working full time today.74 Most who stop out would like to re-enter the workforce, but they are handicapped by having that hole in their CVs. They say that they want us to change organizations and change university curriculum so they can brush up their skills and re-enter the workforce after they stop out. That suggests that we think about instituting, for example, postdoctoral fellowships to facilitate re-entry. We need to revamp career tracks in academe, as well as in business.75 That is going to be a long, hard struggle.

72

Massachusetts Institute of Technology (1999). A study on the status of women faculty in science at MIT. The MIT Faculty Newsletter 11(4):14-26, http://web.mit.edu/fnl/women/women.html.

73

SD Blake-Beard (2001). Taking a hard look at formal mentoring programs: a consideration of potential challenges facing women. Journal of Management Development 20(4):331-345; AJ Murrell, F Crosby, and R Ely (1999). Mentoring Dilemmas: Developmental Relationships Within Multicultural Organizations. Mahwah, NJ: Erlbaum; KE Kram (1985) Mentoring at Work: Developmental Relationships in Organizational Life. Glenview, IL: Scott Foresman.

74

See M Conlin, J Merritt, and L Himelstein (2002). Mommy is really home from work. Business Week (November 25), http://www.businessweek.com/magazine/content/02_47/b3809108.htm

75

SA Hewlett and CB Luce (2005) Off-ramps and on-ramps: Keeping talented women on the road to success. Harvard Business Review 83(3):43-46, 48, 50-54 passim.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Next, we have individual tempered radicals,76 people who have worked from within an organization for change that benefits women. What we need to do is figure out what tempered radicals have done that has worked, share those strategies, and use them to train the next generation of tempered radicals. There are wonderful strategies out there, but there are few opportunities for us to share that knowledge and pass it on.

Finally, and most exciting, is the research on small-win experiments. Small wins are not small at all. The idea is that you go into an organization and implement a very small-scale experiment that, if it worked, would shatter gender stereotypes and open doors to equality as they had never been open before. Meyerson and Fletcher went to the Body Shop, the cosmetics company in England. The lipstick factory employed people on the assembly line in feminine uniforms, and every assembly line had a male supervisor in a white lab coat. The experiment abolished the male supervisor with the lab coat on two of the assembly lines, and had the assembly line workers, who were all women, rotate in and out of the leadership position. Productivity skyrocketed, and at the end of the experiment every woman on that assembly line had had leadership experience, and two or three of them actually got promoted. That’s a small win that matters. Lotte Bailyn did the same thing at Xerox and changed the norms about working impossibly long hours.77

Because of interlocking institutions, which were mentioned previously by Yu Xie, in academe more than in any other domain, we can not just change universities. We have to change all kinds of other institutions simultaneously. And in designing change programs, you can not duck the need to look at families and the need to look at employing organizations more broadly.

As to future research, we should go beyond counting bodies and providing statistics, beyond documenting unfairness. That does not change behavior. What is needed are organization-level change programs tailored to the tipping points, because outcomes will not change until the process changes. For example, the first tipping point is probably the most germane for science and engineering. Once an organization or department is 18% women, what helps women to see their common interests, to network, and to organize collectively? What kinds of programs work best for minority women? How can male backlash be minimized? And when should policies benefit both sexes, and when should they not?78

76

DE Myerson and MA Scully (1995).Tempered radicalism and the politics of radicalism and change. Organization Science 6(5):585-600.

77

R Rapoport, L Bailyn, JK Fletcher, BH Pruitt (2002). Beyond Work-Family Balance: Advancing Gender Equity and Workplace Performance. San Fransisco: Jossey-Bass; D Meyerson (2003). Tempered Radicals: How People Use Difference to Inspire Change at Work. Boston: Harvard Business School Press.

78

H Ibarra (1992). Homophily and differential returns: Sex differences in network structure and access in an advertising firm. Administrative Science Quarterly 37(3):422-447; DA Thomas and JJ

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

At the institutional level of analysis, Williams called for large scale, cross-institutional change programs that go beyond the boundaries of a single organization or even a single institution; where a single institution would be a member of class of organizations like “high schools” or “universities” or “families.” How can the institutional interlock of families, schools, and religious organizations be broken so that gender progress is not blocked?79 Finally, Williams said a lot could be learned by studying other countries. An example was the Australian equal opportunity agency (EOWA), which has given financial awards to organizations, including universities, for exemplary practices. It also has software on line that can be used to calculate whether men and women are being paid fairly.

SELECTIONS FROM THE QUESTION AND ANSWER SESSION

DR. CHUCK: Emil Chuck, Duke University. Certainly, many of these ideas are great, but how much money is it going to take? That has been the question that has confronted our parents group over at Duke University and our advocates for the last three years when it comes to human resources, finding less expensive child care, and so forth.

DR. MARTIN: You need to count the lost cost in faculty time, and in all other kinds of time, when you hire women who then quit.

DR. WILLIAMS: And in the sciences, the business case can be really robust when a university pays $200,000 for example, to hire a single person who will then leave because of work-family issues. With respect to graduate students, what graduate students very often need is part-time inexpensive childcare. Childcare, like everything else, tends to be conceptualized in an on/off model. If you had part-time child care slots through a co-op system, that might actually be far better for graduate students than an extremely expensive subsidy per child care slot, which is the classic model.

DR. DRAGO: Many universities, including Penn State, have networks of undergraduate child care and babysitting at some level. So, you can connect, and you can usually find somebody. The second is there is federal money through CCAMPIS grants,80 which many universities have used to fund student child care. Third, you have to be organized. We have been fighting to get a third childcare center at Penn State for a while. It is just going to take time, and you have to keep

Gabarro (1999). Breaking Through: The Making of Minority Executives in Corporate America. Boston: Harvard Business School Press.

79

J Martin (2006). Gender Equity Interventions: What Works, What Doesn’t, and Why. Manuscript in preparation. Stanford University, Stanford, CA; L Wacquant (1997). For an analytic of racial domination. Political Power and Social Theory 11:221-234.

80

The Child Care Access Means Parents in School (CCAMPIS) grants are administered through the Department of Education. See http://www.ed.gov/programs/campisp/index.html.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

publicizing it. Fourth, I would say without federal money we’re never going to solve the childcare problem. It’s too big.

DR. GINTHER: A study of private sector employers found that only 2% provide paid parental leave. Coherent parental leave policies are really hard to come by even in academia. Joan Williams mentioned Saranna Thornton’s work where one-third of universities had illegal family leave policies.81 I think the first thing is to get universities to be law abiding institutions.

DR. SIMPSON: Carol Simpson, Worcester Polytechnic Institute. I’m at an institution where we are fortunate in having reached the first tipping point, and it’s predominately an engineering institution, so we are very pleased with that. But, what that means is now we have two female faculty members in one department, three in another, one in another. And there is a sense of real isolation among those women. One strategy that I have used as provost that seems to be bearing some fruit is to bring faculty together at my invitation—in informal receptions, two or three times a year. Still, while this has had a very positive impact, it has not solved the problem. We lost two women this year by attrition. There is still a lot of work to be done.

DR. CARNEY: Arlene Carney, University of Minnesota. I was wondering if anyone on the panel could address the existence of data about stopping the tenure clock? I find it very difficult to convince our young untenured faculty members to take advantage of our policies. Are there data that show that women who have stopped the tenure clock have suffered, or that tenure committees actively have misjudged people because of stopping the tenure clock?

DR. BAILYN: As many of you know, Princeton and MIT have made it stopping the clock automatic, so that people do not have to ask for it. We did have some data in the period before it was automatic, and that’s where the evidence comes that people who took leave didn’t get tenure. I don’t think we have enough time yet to know whether the automatic extension is going to help. At MIT it’s only been in place for five years. There does have to be some rethinking about “time since PhD.” Time is a complicated issue that needs to be dealt with.

DR. WILLIAMS: The rethinking of time very specifically has to be reflected in the letter that goes out to reviewers. There is an increasing legal dimension to this. In the Lisa Arkin case for example, the $500,000 settlement, one of the statements was that stopping the tenure clock was “a red flag” in a tenure file. This is just not anywhere a university wants to go legally. If you have a stop the tenure clock policy, there should be a strong, concerted effort to make it real, or you are placing yourself at potential risk.

81

S Thornton (2003). Maternity and Childrearing Leave Policies for Faculty: The Legal and Practical Challenges of Complying with Title VII. University of Southern California Review of Law and Women’s Studies 12(2):161-190.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

DR. DRAGO: When Joan and I published the part-time tenure track piece,82 one of the responses we got from a man was, I don’t know what half a tenure case is. The time from PhD measure is particularly of concern with more scientists doing postdocs. It is exacerbating the conflict between the biological and tenure clocks. One thing that I keep coming back to is maybe we should be thinking about shortening the tenure clock at some level. Law schools are three years I think.

DR. MARTIN: Law schools are tenure in a flash. I did want to mention one issue that hasn’t come up, which is the structure of grants in the sciences. If you tie eligibility for certain grants for three or five or ten years from PhD, that means that if you take time out to have a baby, or if you take time out to care for an elderly person, you are basically placed at a systematic disadvantage. I understand that this is not an easy system to solve, but it is a system that clearly has a disproportionate negative impact on women.

DR. CHAN: Emily Chan, Colorado College. A lot of the data in the points represented so far is about young researchers in R-1 universities, maybe R-2 universities. Given that liberal arts colleges are more and more emphasizing research in the sciences, I wonder how a lot of these things that you talk about may be similar or different in the liberal arts context.

DR. DRAGO: From our study, the main differences were women in liberal arts colleges reported missing more of their children’s important events when they were young, because of a heavier teaching load. There is no surprise there. They were more likely to parent. The women and men in chemistry were more likely to parent than the women and men in English. Presumably, that has to do with family. There is about an $8,000 pay difference.

DR. WILLIAMS: There are also different design issues with regard to a part-time tenure track in a liberal arts college.83

DR. GINTHER: My research combined all people in four-year institutions. Women tend to be more represented at teaching institutions than at Research 1 institutions.84

82

R Drago and JC Williams (2000). A half-time tenure track proposal. Change 32(6):46-51.

83

JC Williams (2004). Part-timers on the tenure track. The Chronicle of Higher Education, http://chronicle.com/jobs/2004/10/2004101401c.htm.

84

DA Nelson and DC Rogers (2005) A National Analysis of Diversity in Science and Engineering Faculties at Research Universities, http://www.cwru.edu/admin/aces/search/diversityreport.pdf.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL 4
IMPLEMENTING POLICIES

   

 Panel Summary

 

 

   

  Recruitment Practices
Angelica Stacy, Department of Chemistry, University of California, Berkeley

 

 

   

  Reaching into Minority Populations
Joan Reede, Harvard Medical School

 

 

   

  Creating an Inclusive Work Environment
Sue Rosser, Ivan Allen College, Georgia Institute of Technology

 

 

   

  Successful Practices in Industry
Kellee Noonan, Technical Career Path, Hewlett Packard

 

 

   

  Selections from the Question and Answer Session
Moderated by committee member Nan Keohane

 

 

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

PANEL SUMMARY

This panel discussed specific practices and policies that foster or discourage the employment and advancement of women in academic science. Angelica Stacy began by questioning whether the entryway to science positions in research universities is inviting to women. Some science departments have noted an “applicant-pool problem” in which the proportion of female applications is lower than that within the total pool of doctorate holders. Departments that have excellent records in hiring women have taken such special steps as selecting diverse search committees and including input from graduate students in the search process.

Like Xie and Drago, Stacy noted that conflict between work and family is a barrier to women, citing statistics that married men with young children are 50% more likely to enter tenure-track jobs than comparable women. Three-fourths of female assistant professors at the University of California, Berkeley have no children, as opposed to 58% of men; and only 9% of female assistant professors have two children, as opposed to 13% of males. Narrow position specifications also disadvantage women, who are 50% more likely than men to do interdisciplinary work and have joint appointments. Berkeley’s new department of bioengineering, for example, is 50% female. Building an entry that is inviting and accessible to women requires proactive recruitment, family-friendly policies, and full-time allocations for multidisciplinary posts.

Joan Reede discussed the special problems of women biomedical scientists who are members of minority groups. Their underrepresentation results from a variety of pipeline issues and barriers, despite the fact that interest in studying science is higher among African American and Asian girls than among white girls. Of African Americans who receive science degrees, 64% are women.

Minority women who do enter academic science careers suffer a double jeopardy, however, because of isolation, lack of mentoring, and the expectation that they will serve as advisors and committee members, Reede added. They have only limited networks for their own guidance. She then described examples of several Harvard University programs (aimed at encouraging and supporting minority science and medical students) that have contributed to the more than doubling of underrepresented minority representation on the Harvard Medical School faculty as well as providing increased opportunities to more than 4800 students.

Sue Rosser examined various approaches to creating inclusive work environments. She used questionnaires and interviews to identify the issues of greatest importance to female science faculty. The top issue, cited by 65 to 88% of respondents, was balancing work with family responsibilities. Next were time management, especially the balance among teaching, research, and committee responsibilities; the low number of women and resulting lack of mentoring and camaraderie; the difficulty of gaining respect and credibility among male peers;

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

and dual career problems, especially pertinent to women scientists since more than 60% are married to men scientists. Reports of harassment, overt discrimination, stereotyping, lack of respect for one’s work, and mere “lip service” to diversity were numerous.

The National Science Foundation’s ADVANCE program is focused on institutional transformation to facilitate the advancement of women scientists into senior faculty and leadership positions in universities. The 19 universities that have received ADVANCE grants are developing an array of models for transformation. Helpful models for making workplaces more inclusive include family-friendly policies and practices and training search committees, chairs, deans, and tenure and promotion committees.

Kellee Noonan, the only convocation speaker from industry, described her company’s Technical Career Program, which is used throughout the company’s worldwide operations. The program aims to recruit and advance the careers of a diverse workforce of highly trained technical professionals. It is designed to break the glass ceiling by making processes fair and transparent, eliminating cumulative bias in selection and promotion, and applying to career advancement the First Law of Diversity: “when bad things happen, they happen worst to people in the minority.”

The career ladder for each position is clearly open and defined, and promotion is based on criteria that are readily accessible on company Web sites and linked to open and broadly available learning resources. This allows employees to know what they need to do to meet each criterion and then to gain the skills required for advancement. A core team works continuously to educate employees about the criteria, using regular forums and other means. A diversity team focuses on goals and metrics, developing mentoring and other programs to help underrepresented ethnic, gender and geographic groups to succeed and advance. Those policies have helped break the glass ceiling for women technologists in some areas of the company, and current efforts continue to “raise the roof.”

RECRUITMENT PRACTICES

Angelica Stacy

Department of Chemistry, University of California, Berkeley


Angelica Stacy focused on recruitment practices, specifically, the structures that are in place in academic institutions and the degree to which they are inviting and accessible to women. As associate vice provost for faculty equity at the University of California, Berkeley, and professor of chemistry, she has been monitoring for a number of years the searches for and the career advancement of faculty and also has been doing general studies of diversity and inclusion on the faculty.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

She provided evidence from the Berkeley database on the faculty applicant pool that the entryway to faculty positions is neither inviting nor accessible. Of people who have applied to Berkeley for a faculty position, 75% have filled out a survey indicating their gender and ethnicity. No faculty search had a pool of women that was equal to, let alone above, the pool of women that are in even the most conservative estimate of the PhD pool. Figure 1-10 shows the U.S. PhD pool weighted average across physical science, mathematics, and engineering (n = 12,214). It includes about 15% white women, and 4-6% female members of underrepresented minority groups. Above that is shown the 2001-2004 Berkeley applicant pool (n = 3,952), which is about one-third of the PhD pool. Women are hired as assistant professors in a proportion similar to their representation in the applicant pool.

In the biological and health sciences, there are many more women in the PhD pool (Figure 1-11). The applicant pool is about 17% of the PhD pool. Berkeley has been hiring about 50% women into assistant professor positions and now has close to 50% women at the associate professor level. That bulge has not reached the full-professor or leadership ranks at Berkeley.

What can we do to improve recruitment and hiring of women? Figure 1-12 plots the percentage of women hired against the percentage of women in a conservative estimate of the pool,85 which the departments estimated themselves. The diamonds represent individual departments at Berkeley. The dashed line is a theoretical indicator for hiring equaling the pool. As shown by the bold line, over the entire institution, and even within the sciences, hiring vs. the pool is on the average about even.

Those data can be used to determine which recruitment and hiring practices correlate with hiring above, at, or below the applicant pool. Table 1-1 shows a ranked list of practices used by departments to enhance the faculty pool; 96% of departments reported listing faculty positions in multiple venues and 84% said that they made it clear that women and members of underrepresented minority groups were encouraged to apply. Dividing the list by those departments that hired at or above the level of the pool of women (Exc.), and those that hired below the level of the pool (Not Ex.) yielded statistically significant differences. The most significant ones—designating an affirmative action officer to serve on the search and saying women and minorities please apply—were highly correlated with those departments that didn’t hire at the level of the pool. Those who are doing excellently are using other kinds of strategies: they are including graduate student input, selecting diverse search committees, and going out to professional meetings and establishing relationships and inviting women to apply

85

The pool was calculated on the basis of on PhDs granted to US residents, 1997-2001 (Survey of Earned Doctorates, National Science Foundation) at the 35 top-quartile rated doctoral programs (National Research Council reputation ratings) producing the most PhDs.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-10 Physical science, mathematics, and engineering applicant pool and faculty positions at the University of California, Berkeley.

SOURCE: UC Berkeley Faculty Applicant Pool Database, 2001-2004; UC Berkeley Faculty Personnel Records, 2003.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-11 Biological and health sciences applicant pool and faculty positions at the University of California, Berkeley.

SOURCE: UC Berkeley Faculty Applicant Pool Database, 2001-2004; UC Berkeley Faculty Personnel Records, 2003.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-12 Departmental hiring vs the applicant pool, University of California, Berkeley.

Notes: Figures are since 2000; only departments that hired over five faculty during that period are included.

rather than assuming that women feel confident enough or included enough to send in an application.

Work-family conflict also affects the applicant pool. Mary Ann Mason and Marc Goulden have found that married women who have children pay a 50% penalty in terms of entering faculty positions, as compared with single women or married men who have children.86 At Berkeley, of female assistant professors, 16% have one child and 75% have no children; 27% of male assistant professors have one child, and only 58% have no children (Figure 1-13).

86

M Mason and M Goulden (2004). Marriage and baby blue: Redefining gender equity in the academy. The Annals of the American Academy of Political Social Science 596:86-103.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

TABLE 1-1 Methods Used by University of California, Berkeley Departments to Enhance Faculty Hiring Pool

Rank Order

Methods Used

# Women Hired

Total(n=59)

Exc. (n=25)

Not Ex . (n=29)

1

Listed faculty positions in multiple venues

96%

97%

96%

2

Job description made clear women/URM encouraged to apply

76%

90%

84%

3

Made personal calls to encourage potential candidates to apply

84%

86%

84%

4

Selected diverse search committees

92%

79%

84%

5

Included graduate student input in search process

92%

72%

82%

6

Made calls to colleagues asking them to encourage women/URM to apply

80%

83%

80%

7

Circulated job description among networks women/URM educators

88%

72%

79%

8

Designated an affirmative action officer to serve on search

64%

90%

77%

9

Approached or interviewed applicants at professional meetings

72%

72%

73%

10

Established relationships with local/national women/URM organizations

68%

52%

59%

11

Educated search committee members on diversity/equity/affirmative action

52%

55%

54%

12

Discounted caregiving related resume gaps

32%

41%

36%

13

Prioritized subdisciplines with high diversity

36%

31%

32%

14

Encouraged UC President's Postdoctoral Fellows to apply

36%

31%

32%

15

Interviewed candidates at a variety of conferences

36%

21%

27%

Notes: Hatched shading denotes p < .05 significant difference based on chi-square. Dotted shading denotes p < .10 significant difference based on chi-square.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-13 Children in households among assistant professors at the University of California, Berkeley.

SOURCE: MA Mason, A Stacy, and M Goulden. 2003. “The UC Faculty Work and Family Survey.” See http://ucfamilyedge.berkeley.edu.

Note: Numbers of children were self-reported.

We now have better policies around the country. Let me assure you that if you get out there and start to say, “This is what we want, this is the way we do things, and this is an entitlement,” which is where a number of our institutions are moving, I think we’re going to see things change.

—Angelica Stacy

Narrow position specifications also affect the applicant pool and numbers of women hired. There is mounting evidence that women are choosing to work at the boundaries of the disciplines. Among the STEM87 faculty at Berkeley, 26% of the women and 15% of the men have joint appointments. Women tend to hold joint appointments in business, biology, law, city and regional planning, economics, and environmental science. In one of the newer departments, bioengineering, 50% of the faculty are women. The biological sciences were restructured. They now include broad, multidisciplinary approaches, and no longer have the old embedded departmental structures of the beginning of the last century. Fifty percent of the faculty are women.

87

At Berkeley, biology and health sciences are not included in the category “STEM”, science, technology, engineering, and mathematics.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

I can’t tell you how many times I have reviewed searches in which the people—predominantly women and minority-group members—were not hired, because they didn’t “fit.”

—Angelica Stacy

As part of its diversity initiative, Berkeley has started to hold full-time equivalent (FTE) faculty positions centrally for groups of faculty and departments that get together proposing new multidisciplinary research areas. This is done to counteract the tendency in departments to hire people who they have always hired, who look just like them, who fill the mainstream slots, rather than moving the institutions forward into new areas. For this, institutional leadership is important. Stacy concluded with four main ideas: proactive recruitment, family-friendly policies, FTE allocations, and leadership. Her motto: build it, so the best will come.

REACHING INTO MINORITY POPULATIONS

Joan Reede

Harvard Medical School


Joan Reede focused her remarks on reaching into and across minority populations, particularly in the biomedical sciences.

There is a well-known persistent and continuing underrepresentation of African American, Hispanic, American Indian, Alaskan Native, and Native Hawaiian males and females in academic science. The underrepresentation is fueled by limitations in the pipeline and by what Reede termed the “academic black hole” into which many graduates fall, a hole associated with attrition and lack of advancement. Pipeline deficiencies are found in access, achievement, and attitude. Oftentimes, minority-group students are faced with inadequate preparation and awareness of opportunities, underdeveloped relationships with adults and an associated unrecognized potential, and lack of mentoring and career counseling. Minority-group students often have insufficient social supports and resources, particularly financial resources that are necessary to pursue advanced education. As described by Toni Schmader earlier, data show that African American, Hispanic and American Indian students fare less well on high school, college and professional school standardized tests.

In an analysis of the National Educational Longitudinal Survey, Hanson found that there was variability in attitudes toward science for women across racial and ethnic groups.88 For example, African American female students

88

SL Hanson (2004). African American women in science: Experiences from high school through the post-secondary years and beyond. NWSA Journal 16(1):96-115.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

expressed a greater interest in science than did white female students in the 8th and 10th grades.

An important question is what factors sustain, increase, or decrease student’s interests as they move along the educational ladder. Once minority-group members and women enter the academy, they are confronted with barriers and diversity taxes—such barriers as assumptions and stereotypes, including all the “isms”—racism, classism, sexism— and discrimination. They often face cultural, social, and intellectual isolation, and do not have access to formal and informal mentoring.

—Joan Reede

Minority-group women face a double jeopardy associated with their limited numbers and are expected to take on extra service responsibilities associated with counseling of students, residents and fellows and to assume committee assignments. Those activities are not adequately acknowledged within the academic reward system or in the promotion review process.

Minority groups and women often have few research sponsors and opportunities for collaborative research. Their informational networks that can provide input, critique, validation of experiences, and an understanding of organizational rules and bureaucracy are limited. Those issues are cumulative and persist from junior to senior faculty levels.

Adequate numbers of minority-group members, particularly female faculty, cannot be achieved unless pipeline issues are dealt with. Deficiencies in the educational process leading to graduate and professional school disproportionately affect minority-group and poor students. An analysis by the Education Trust89 found that of every 100 white kindergartners, 93% would graduate from high school, 65% would complete some college, and 33% would obtain bachelor’s degrees. The corresponding numbers for black kindergartners were 87%, 50%, and 18% respectively. For Latino and American Indian kindergartners, only 11% and 7% of youth, respectively, would earn bachelor’s degrees. There is also an association between poverty and graduation: the vast majority of students who graduated from college by the age of 26 years come from high-income families.

Of those students who enter college, the National Science Foundation reports that the percentage of Asian, African American, and Latino freshmen who intended to pursue a science or engineering major is higher than that of white freshmen. And for all racial and ethnic groups, the percentage of freshmen females planning to major in science or engineering was higher than the percentage of males. That was true for all science and engineering majors (Table 1-2).

89

Education Trust, Inc. (2002). US Department of Commerce, Bureau of the Census, March Current Population Surveys, 1971-2001. In The Condition of Education. US Department of Education.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

TABLE 1-2 Intentions of Freshman to Major in Science and Engineering Fields, by Race, Ethnicity, and Sex, 2002

Race/Ethnicity

All S&E Majors (%)

Biological/ Agricultural Sciences (%)

White

 

 

 

Male

23.8

6.2

 

Female

37.9

7.6

Asian/Pacific Islander

 

 

 

Male

33.1

10.2

 

Female

53.0

13.5

African-American/Black

 

 

 

Male

31.9

5.8

 

Female

38.0

10.0

Chicano/Puerto Rican

 

 

 

Male

30.6

6.8

 

Female

39.4

9.2

Other Hispanic

 

 

 

Male

30.9

6.9

 

Female

40.8

8.3

American Indian/Alaska Native

 

 

 

Male

27.2

6.1

 

Female

37.6

8.8

SOURCE: Women, Minorities, and Persons with Disabilities in Science and Engineering, 2004, National Science Foundation.

From 1994 to 2001, there was an increase of 27 to 38% in the numbers of science and engineering bachelor’s degrees awarded to all minorities (Figure 1-14). During that period, however, there was a 10% decline in science and engineering bachelor’s degrees awarded to whites. Much of the increase among minorities was fueled by an increase in science and engineering degrees awarded to women. For example, in 2001, 64% or roughly 21,000 of science and engineering bachelor’s degrees earned by African Americans, and 55% or 15,000 of the science and engineering bachelor’s degrees earned by Hispanics were awarded to women.

There is a similar increase in science and engineering doctorates awarded to minority women in the same period, except for Asian Americans (Figure 1-15). Although there was an increase in absolute numbers, the representation of minority-group women as a percentage of all science and engineering doctorates in 2001 was less than 9%, and half of those degrees were to Asian American women. The decrease in Asian American women receiving science and engineering doctoral degrees was not seen in the biological sciences, where the numbers were the same in 1994 and 2001: 268 degrees.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-14 Number of science and engineering bachelor’s degrees awarded to minority females, by race and ethnicity, 1994-2001.

Note: American Indian/Alaskan Native includes Native Hawaiians and other Pacific Islanders; Other/Unknown includes those with unknown race/ethnicity and respondents choosing multiple races (excluding those selecting Hispanic ethnicity).

SOURCE: National Science Foundation, Division of Science Resources Statistics, special tabulations of US Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System, Completions Survey, 2001.

For academic medicine and the pipeline of medical students, there was an overall decline in medical-school applications from all racial and ethnic groups from 1997 to 2002. That was followed by a rise in the past two years, with underrepresented-minority applicants finally achieving their 1992 levels in 2004. Associated with the overall increase in applications was an increase in applications from women. However, there was variability in applications across racial and ethnic groups; African American women were nearly 70% of all African American applicants to medical schools.

In looking at applications, matriculants, and graduates, it is important to disaggregate racial and ethnic groups. For example, there was variation in applications among Hispanic subgroups, with a 10% increase in Mexican American applicants from 2002 to 2004, and a 20% decline in Puerto Rican applicants in the same period. That variability was also seen in the percentage of women among the various racial and ethnic applicant pools.

Among medical school faculty, three striking patterns are noted: men and women of color are underrepresented; African American, Hispanic, American Indian, and Alaskan Native women represent a very small percentage of all

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-15 Number of science and engineering doctorates awarded to minority-group women, by race and ethnicity, 1994-2001.

Note: American Indian/Alaskan Native includes Native Hawaiians and other Pacific Islanders; Other/Unknown includes those with unknown race/ethnicity and respondents choosing multiple races (excluding those selecting Hispanic ethnicity).

SOURCE: National Science Foundation, Division of Science Resources Statistics, Survey of Earned Doctorates, 1994-2001.

medical school faculty; and the proportion of women faculty in all racial and ethnic categories declines in advancing up the academic ladder from instructor to full professor (Figure 1-16).

Among science and engineering doctorate holders employed in colleges and universities, similar patters of underrepresentation of racial and ethnic minorities, low numbers of women faculty, and aggregation of women among lower academic ranks are also seen (Figure 1-17).

Part of Harvard Medical School’s response to the need for diversity was the establishment of the Minority Faculty Development Program in 1990 and its incorporation into the Office of Diversity and Community Partnership (DCP) that was established in 2002. DCP sponsors almost 20 programs that cross multiple academic levels from kindergarten through college and medical student fellowship and junior faculty programs that provide multiple points of entry, exit, and re-entry. Themes included in the development and implementation of DCP programs include continuity, collaboration and partnership, the building of networks and support systems, formal and informal mentoring, skill building, increasing awareness of career paths and opportunities, and evaluation and tracking.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-16 Medical school faculty by rank, gender, race, and ethnicity.

SOURCE: AAMC Faculty Roles Survey, 2004.

Using elements of those themes, Reede described three Harvard Medical School programs that are related to organizational structures and policies that deal with collaboration and that address issues that cross multiple levels of the academic and career ladder.


Biomedical Science Careers Program (BSCP). Of the students in this program 60% are women, 47% are African American, and 19% are Hispanic. Founded in 1991 with a group of people from Reede’s office at Harvard Medical School, the Massachusetts Medical Society, and the New England Board of Higher Education, the BSCP quickly grew to a community of individuals and organizations that shared a desire to address diversity. It is now led by a board of directors that includes presidents and CEOs in biotechnology, medical device research, legal, and finance industries; leaders in academe, professional associations, and community colleges; educators; practitioners; and employers. Supported by the community, and without public funding, the BSCP has now reached more than 4,800 high school, college, medical school and professional school graduates, and postdoctoral students and fellows. The more than 500 volunteers who have made the BSCP initiatives work point to the fact that many in the biomedical community are deeply concerned about education, diversity, and the

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

FIGURE 1-17 Number of science and engineering doctorate holders employed in science and engineering occupations in universities and 4-year colleges, by race, ethnicity, and faculty rank, 2001.

SOURCE: Women, Minorities, and Persons with Disabilities in Science and Engineering (2004). Arlington, VA: National Science Foundation.

Note: American Indian/Alaskan Native (AI/AN) data for “Other faculty” are suppressed because there are fewer than 50 weighted cases.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

future science workforce. BSCP students have said that experiential opportunities such as internships and job shadowing, contact with minority-group role models, and encouragement from teachers have a large influence on their educational and career goals. BSCP has influenced students to obtain more information, strengthen their interests, and to make them aware of career opportunities and connections with people. Students have been able to identify jobs and apply for jobs, participate in new programs and internships, identify mentors at their schools, and obtain funding.

Visiting Clerkship Program (VCP). More than 700 third- and fourth-year medical students from schools across the country have participated in this 1-month externship program, established in 1990. The program offers travel, housing, faculty advisers, and access to networks and resources. Some 15% of VCP students have returned to Harvard as residents, fellows, and faculty. The students have said the things that are important to them in selecting a residency program are academic training programs, the pre-eminence of those programs, their recommendations and interactions with advisers and mentors, their potential for research participation, and family considerations.

Center of Excellence in Minority Health and Health Disparities. This fellowship program for junior faculty was established in 2002; the first cohort began in 2003. To date, nine faculty fellows have participated. Four have been promoted, one to a division chief. Two are up for promotion now. Eight have obtained external grant funding. An essential component of the program is selected mentors. All fellows have to have letters of support and involvement of department chairs, and the presidents of the participating Harvard Medical School hospitals are involved in the selection. Built into this program are accountability and recognition of and support for excellence.

What issues need to be addressed if we are to achieve racial and ethnic diversity? Responsibility at multiple levels. There needs to be top-down and bottom-up activity that provides vehicles to ensure the success of minority and women students, trainees, and faculty. And this activity must extend beyond verbal acknowledgment of the need for diversity. Recognition of the need should be incorporated into the institutional missions, reiterated in the setting of policies, and integrated in the design of programs. Data should be disaggregated to ensure that issues that disproportionately impact certain racial and ethnic groups are appropriately addressed and outcomes of interventions are adequately tracked. Diversity is not just about minorities and women. Diversity is about how we can improve and advance science for all.

—Joan Reede

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
CREATING AN INCLUSIVE WORK ENVIRONMENT90

Sue Rosser

Ivan Allen College, Georgia Institute of Technology


Sue Rosser began with an emphasis on the need for practical institutional approaches, as suggested by the MIT report.91 Almost simultaneous with the release of the MIT report, the National Science Foundation launched its ADVANCE Institutional Transformation Initiative. For many years, there had been successor programs such as visiting professorships for women, career advancement awards, and professional opportunities for women in research and education (POWRE). Although some of them had a component for institutional transformation, they largely gave money to individual women researchers. In contrast, ADVANCE focuses on institutional changes, especially for women on the academic tenure track to senior and leadership positions. The first round of ADVANCE awardees occurred in 2001 and the second in 2003, and the third round will be announced in early 2006.92 From these grants will come several models of what has worked and what has not worked for different institutions.

Rosser studied the NSF POWRE awardees and the Clare Booth Luce professors to understand the most significant issues, challenges, and opportunities facing women scientists today as they plan their careers.93 She received about 450 responses to e-mail questionnaires and conducted 40 in-depth interviews. Respondents were distributed among all the disciplines, and each of the different years the awards were made are represented.

The first question—an open-ended question—was, What are the most significant issues, challenges, and opportunities facing women scientists today as they plan their careers? People could have said anything. What amazed me was that balancing career with family was the overwhelming response—65 to 88% for all 4 years.

—Sue Rosser

After balancing career with family, a second major issue was time management: balancing work with research, teaching, and service. The third issue was isolation: low numbers, and lack of camaraderie and mentoring. The fourth issue

90

For more details, figures, and references, see the paper by Rosser in Section 2.

91

Massachusetts Institute of Technology (1999). A study on the status of women faculty in science at MIT. The MIT Faculty Newsletter 11(4):14-26, http://web.mit.edu/fnl/women/women.html.

92

Several of the meeting posters presented research from ADVANCE grantees; see the poster abstracts later in this volume (p. 175).

93

SV Rosser and J Daniels (2004). Widening paths to success, improving the environment, and moving toward lessons learned from experiences of POWRE and CBL awardees. Journal of Women and Minorities in Science and Engineering 10(2):131-148.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

was gaining credibility and respectability. And then the fifth major issue was the dual career problem. All those issues have come up previously in this meeting.

Many of these issues are centered around the fact that the life cycle is based on what I call the white male model. There is nothing wrong with that, unless you’re not white and male; if you are not then it does not work very well for you, particularly the competition between the biological clock and the tenure clock.

—Sue Rosser

Another way of presenting the data is by dividing the responses into four groups:

  1. Pressures women face in balancing career and family (~30%).

  2. Problems faced by women because of low numbers and stereotypes held by others regarding gender (~10%).

  3. Issues that are faced by both men and women scientists and engineers which, because of the current environment of tight resources, may pose particular difficulties for women (~7%).

  4. Overt discrimination and harassment (~5%).

Included in the first category are issues related to the dual career family, which is a particular problem because most women scientists and engineers are married to men scientists and engineers.

The second category has to do with being taken seriously and having increased visibility. The latter is particularly important for women of color, who are very visible because of their low numbers in faculties. If things go well, that’s remembered and can put you on a quick career trajectory. If things go badly, it is not forgotten.

The third category contains issues that are faced by everyone but that have particular angles for women, such as the assumption of being available.

Finally there are overt discrimination and harassment, including slow promotions, lack of women in senior positions, and placement of women into difficult situations because they must buffer the bad behavior of their male colleagues.

Effective models for countering some of those issues have been developed and tested at some of the ADVANCE institutions, including

  • Family-friendly policies and practices, including family-work initiatives, tenure-clock extension, childbearing and family leave, active service modified duty, and daycare facilities.

  • Training of search committees.

  • Training of chairs and deans to manage search committee results and to foster a welcoming departmental environment.

  • Speed mentoring.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

Rosser explained that the Georgia Institute of Technology, an ADVANCE institution, has focused on training of tenure and promotion committees. It developed an ADEPT model, an interactive CD-ROM with which people can participate in a tenure and promotion meeting. It developed nine case studies and nine virtual CVs to go with them. The player of the game can participate with three virtual people in the tenure meeting; and depending on what the player says, ADEPT sends the conversation in a particular direction. In addition to research expertise, ADEPT includes such issues as gender, disability, race, ethnicity, and sexuality. The deans were the first to use ADEPT, and then it moved to the department level, the chairs, and all the promotion and tenure committees. All faculty are now using ADEPT.

Rosser and her colleagues are now developing a “navigate your career” section for junior faculty, with frequently asked questions, such as, Should I serve on that NSF review panel, or should I be writing my own proposal? How do I decline gracefully to serve on that committee that my senior colleague has asked me to serve on?

“Speed mentoring” is another popular program at the Georgia Institute of Technology. Junior faculty take their CVs to a meeting with senior faculty who have served on tenure and promotion committees, but who are not currently on tenure and promotion committees. The junior faculty meet with four or five senior faculty in an hour to get a quick take on their CVs and what they might need to do to get ready for promotion to the next level. The senior faculty may suggest another publication or two in a refereed journal, beefing up their teaching, more service on national committees, and so on. Junior faculty like this very much, and say that they get an impression of the different perspectives that different people have. These are the people who have served on tenure and promotion committees, so it is quite realistic.

Rosser is doing some research on older women scientists because she has become concerned that many of the policies put into place through ADVANCE are primarily for younger women. It is very important for more junior women to achieve tenure, but there are different problems for senior women that need to be addressed.

SUCCESSFUL PRACTICES IN INDUSTRY

Kellee Noonan

Diversity Program Manager, Technical Career Path, Hewlett Packard


Kellee Noonan explained that about 5 years ago, when Hewlett Packard (HP) merged with Compaq, they found that they had noncompatible technical career ladders. They took the opportunity to step back and say, “Can we take the former HP program and the former Compaq program, do some industry benchmarking,

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×

and put together a framework that gives us a place for technologists to be able to see where they are in terms of their skills and abilities, and what they need to be able to do to move to the next level?”

In creating the Technical Career Program (TCP), the goals were to make the promotion process fair and transparent and to eliminate the cumulative bias in selection and promoting. The TCP appears to be helping in terms of moving women and, in the United States, members of underrepresented groups up the career ladder.

The first law of diversity is that when bad things happen, they happen worse to people who are not in the majority.

—Kellee Noonan, quoting Alan Fisher, iCarnegie, Co-author of “Unlocking the Clubhouse”

In developing a promotion policy, HP is faced with some challenges different from universities. For example, because it is a global company, the framework needs to apply to all its businesses in the whole world. HP has research laboratories in the United States, Israel, the United Kingdom, China, Brazil, and India. And it has researchers in outposts in many other places. The program has to be able to address all those areas.

The TCP has clearly defined steps, and they are criteria-based. An employee can go to the TCP Web site in the company portal, and ask, What are the criteria to get to the next step? What kinds of things do I have to do? The criteria are balanced around three areas: impact on the business, depth and breadth of knowledge, and technical leadership skills. It’s a balance of all of them. You don’t have to be perfect in every one. You might have a technologist who is an inch deep but a mile wide. Or you could have a technologist who is an inch wide and a mile deep. What’s the difference? How do you evaluate that? The difference is in the impact they have on the business. How are they applying what they are doing to move the business forward and to get the best products, the best technology, and the best services out to customers in a way that matters?

In addition to the criteria, which are specific, there are career development road maps, examples at every level of what it means to meet a criterion. An HP team works diligently to go through the company’s workforce-development resources to find the exact resources that match a criterion for each level, and publishes them on the company Web site.

If my manager told me that I need to increase my ability to influence a negotiation when there is technology involved, I can go to the TCP Portal Web site and look it up under “influencing” or “negotiation” for my level. And I can find classes that are geared toward improving that skill. We have review boards in place at the higher levels of our ladder. If you get to what we call our strategists’ level, you are reviewed

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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by a cross-business review board to make sure that we maintain consistency in the application of the levels across the company.

—Kellee Noonan

The TCP program core team has a representative of every chief technology office (CTO) to ensure consistency of policy and interpretation. The core team has an information technology function and a research and development function, called the Office of Strategy and Technology. It organizes quarterly TCP information forums, called “airing the dirty linen time,” for employees, HR, managers, and review boards. People can get to the really hard questions. This year, one major focus is the worldwide diversity team. Now, diversity goals and metrics are presented to the CTO every quarter.

HP has also instituted technical leadership curriculum94 which is for distinguished and master level technologists. Those leadership programs have taken traditional leadership out of the management curriculum. These new programs are focused on leading by influence and engagement, because most of the people on the technical career path don’t have a direct staff that can work with them or for them. They have to convince people that it’s worth working for them, they have to convince their manager, they have to convince their manager’s manager.

We have broken the glass ceiling at some of our levels, but we still need to continue raising the roof.

—Kellee Noonan

SELECTIONS FROM THE QUESTION AND ANSWER SESSION

DR. REED: Alyson Reed with the National Post-Doctoral Association. I was hoping that Sue Rosser could elaborate briefly on the speed mentoring model.

DR. ROSSER: This is a neat program that one of our ADVANCE professors, Jane Ammons, invented. In an hour, junior faculty meet with four or five senior faculty—who have served on tenure and promotion committees, but who are not on tenure and promotion committees at the time of the meeting—and get a quick take on their CV and the senior faculty member’s concept of what they might need to do to get ready for promotion to the next level, from another publication or two in a refereed journal, to teaching, or service on national committees. It’s been very popular. We have done it now three or four times, and we have calls for more. I highly recommend it. The only issue is getting it organized, but we have

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The curriculum is based in part on Robert Kelley’s Star at Work (Three Rivers, MI: Three Rivers Press, 1999) and a program developed in-house called TCP Catalyst.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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not had trouble getting senior faculty to do it, and the junior faculty really, really like it.

DR. FLETCHER: Hi, my name is Mary Ann Fletcher at the University of Miami. I would like to speak just briefly about the problem with recruitment of faculty. In my opinion, this problem frequently lies in the fact that at many universities, including my own, have a very severe shortage of women in higher positions in the administration. We have few women as deans, few women as chairs of departments. And so, this leads to search committees that I think frequently have an inborn bias.

I serve on the faculty senate, and we recently had a provost search. I was able to convince our senate to set up a search committee that had one-half female faculty members, and one-half males. Some of the senators said, well, the faculty is not that way. And I said, but the student body is. There are more women than men in our student body. It takes work all the time, and I think the search committees are really key.

DR. AGOGINO: Alice Agogino from the University of California at Berkeley. Do you have any recommendations on how to improve the climate for women faculty in those departments that haven’t reached this magical 18% number?

DR. STACY: We really do need to start taking action at the department level, especially when we start to hear that they are not being managed well, or the interactions aren’t productive, and that they are not an inclusive environment for all the members of that unit, including students and staff, as well as faculty. I think we just need the wherewithal to say that mismanagement is not acceptable at our institutions.

DR. ROSSER: One of the things that’s been helpful to us at Georgia Tech with the ADVANCE institutional transformation grant is in each college we have an ADVANCE professor. This senior professor gets paid extra money from the grant, on the order of $60,000 a year—it’s like an endowed chair—to do activities and build mentoring networks. That has united women in each college, so that for example in engineering, where there are something like 415 tenure track faculty and where women may be isolated in departments, they now don’t feel as isolated, because they now know each other across the college. I have also encouraged department chairs to encourage their women faculty to join women’s studies, which most science chairs think, huh? Why would they do that? I say that may be what makes women hang in.

DR. REEDE: I just want to speak a little bit related to that question, and the comment before about representation of women on searches, et cetera, because one of the critical issues here is oftentimes what gets left out of these discussions: minority representation.

What ends up happening is that one minority person in that department gets rotated for everything. My challenge to the committee and to all of you, as you go back to your institutions, as you think about issues of women, don’t ignore the issues of women of color. When you think about putting women on committees,

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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also think about who will be attending to issues for women and men of color. If you are waiting until women and men of color reach a critical mass on faculties, then I’ll have to look at my great-grandchildren. Oftentimes with minorities, issues are not going to bubble up to the top. They are so isolated and so alienated you may not hear about it.

DR. HAZELTINE: Florence Hazeltine, National Institutes of Health. You said that that there was a bias that women would get short listed or interviewed, but not get past the next step. This reminded me of some business models where if a woman at a high level lost her job, it took her twice as long to get a job as a man. What I want to know is when women do get interviewed for high-level academic jobs—and I see women presidents and chancellors—how many times have they gone up for it versus how many times the successful men have. If the women knew that in advance, we might be able to get them better coaching, a better feel for the system, when they are just going for practice, and when they are just going for real.

DR. KEOHANE: Having had prior experience either in a coaching setting or having been through another interview is very important. I know that this is true for many men as well as women. Since our particular focus here is for women, I think that the suggestion that was implicit in your question is that you prepare in advance for a job interview in the same way you did as a graduate student when you were going for your first assistant professorship, and you learn from these experiences.

I don’t know that there is any evidence that women in most of the really top positions are more likely to be short listed and not chosen. I think that was often true in the past. I think women are more often getting into top leadership positions when they are on the final choice set. What I worry about is that not enough women in academia are seeing high-level leadership positions as an appropriate ambition for themselves. One of the things I find most encouraging about this congregation today is the number of women of strong faculty backgrounds who have been willing to say I will be an associate dean, I will be an associate provost, I will be a provost or a dean or a president.

Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
Page 90
Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
Page 91
Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
Page 92
Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
Page 93
Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
×
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Suggested Citation:"Section 1--Summaries of Convocation Sessions." National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. 2006. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering: Report of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11766.
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Next: Section 2--Selected Workshop Papers »
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During the last 40 years, the number of women studying science and engineering (S&E) has increased dramatically. Nevertheless, women do not hold academic faculty positions in numbers that commensurate with their increasing share of the S&E talent pool. The discrepancy exists at both the junior and senior faculty levels. In December 2005, the National Research Council held a workshop to explore these issues. Experts in a number of disciplines met to address what sex-differences research tells us about capability, behavior, career decisions, and achievement; the role of organizational structures and institutional policy; cross-cutting issues of race and ethnicity; key research needs and experimental paradigms and tools; and the ramifications of their research for policy, particularly for evaluating current and potential academic faculty. Biological, Social, and Organizational Components of Success for Women in Academic Science and Engineering consists of three elements: an introduction, summaries of panel discussions including public comment sessions, and poster abstracts.

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