Why are there fewer women scientists? People noticed the phenomenon behind the question and tried to give an answer. Some researchers related it to cognitive difference between men and women. True, they found some evidences for such difference. Yet none of the evidences is strong enough that can be accepted by entire scientific circle. In the first part, I will show that none of research results showing cognitive difference is stable, so cognitive difference cannot explain women’s underrepresentation in scientific fields. In the second part, I will try to give some reasonable explanations for the phenomenon.

The mainstream theories to support the existence of cognitive difference between male and female are relevant to brain and hormone. Most of the research results are not convincing, because they are either inconsistent, controversial, or without practical significance.

Studies about hormones are inconsistent. Many experiment results cannot be successfully replicated.  For example, the hormone testosterone is believed to have positive correlation with spatial ability. Because the disease congenital adrenal hyperplasia (CAH) causes testosterone to be overproduced, researchers suppose that women with this disease should have higher score in spatial ability test. The results of the experiment are inconsistence. Former experiment with small sample got a significant result that women with the disease have higher spatial ability, but later research with larger sample size failed to find the same result.

The research about brain size is controversial. Some argue that men have bigger brain size than women, so men are more intelligent. The argument is unstable because brain occupies larger proportion in women’s body. Moreover, female’s neurons are packed more densely in some brain regions, so one can use the same data to establish an opposite argument: women are more intelligent that men because their neurons are denser in brain.

The research using intelligence test got many statistical significant results to show that men have high spatial ability and mental rotation ability. Though the data are statistical significant, the results have little practical value. Statistical significance does not mean practical value. Even tiny difference can be verified to be statistical significant. Today, doctors refuse to use new treatment only with statistical significance in experiment; they require the treatment effect are different enough from former one. Even meta-analysis of the spatial ability and mental rotation, the most acknowledged fields that favor men, shows effect size of only 0.13 and 0.56. The data are significant, but they do not have big practical value. The differences are fairly negligible compared to the same general intelligence of men and women.

Gender study is an independent subject today and belongs to scientific fields, so it is shocking that no consensus about cognitive difference exists. Gender study is interdisciplinary subject that combines biology, psychology, and social science. All other scientific subjects has some consensus as foundation, but for gender study, the existence of cognitive difference, is still controversial today. We have reason to believe that cognitive difference is too vague to have strong support.

Let’s get back to the original phenomenon that started the debate about cognitive difference: women’s underrepresentation in scientific fields. If the noun “cognitive difference” cannot give an explanation to this phenomenon, what is the answer? Well, we cannot partially give some environmental explanations without strong support. There are some broad acknowledged theories.

First, studies show that people tend to rate women lower than men when they have the same resumes, so women will have disadvantages in hiring process and promotion. Second, today’s academic system requires candidates to finish six years of Ph. D. stage right followed by six years of assistant professor stage to get a tenure position. The process gives big disadvantage to women because most women plan to give birth to children during this time period. But I have to acknowledge that these environmental based theories are just inference, either. Though some experiments have showed expected results to support these two theories, a large database is still unavailable. So we still cannot give a confident answer to the original question: why are there fewer women scientists.

Based on all the above, the existence of cognitive difference does not have strong support and cognitive difference cannot explain women’s underrepresentation in scientific fields. Some environmental based theories give us some reference. Scientists still need to do further research.

Reference:

Halpern, D. F. (2007). Science, Sex, and Good Sense: Why Women Are Underrepresented in Some Areas of Science and Math. American Psychological Association.

Hines, M. (2007). Do sex differences in cognition cause the shortage of women in science?.

Lubinski and Benbow believe that women have innate low interest to work, which gives them disadvantage in career. They make an assumption that work time is positively related with success. Because women have less passion for long time work than men, they are underrepresented in the work place. The theory makes me think. Do women have less enthusiasm in long time work? Is longer work time related to larger success possibility? My answers to both questions are No.

How do we define women’s work interest? In the article, two authors simplify it as how many hours people plan to spend on work. It makes sense at the first time. Yet is it a suitable measurement? If we only compare one variable, we need to make sure that other variables have been controlled. But in this experiment many variables exist. Women’s extra labor in family life explains their lower passion for long time work (Mattingly & Blanchi, 2003). Women’s family role inhibits their free time, as they spend more time than men taking care of children. According to research, women’s free time is less than men. So it is convincing that women need less work time to balance their extra work load. The difference is influenced by environment; it is not innate. Moreover, I notice that the mean age of the sample in the article is 33, which makes the result biased. Because their children are at preschool age, women have larger family burden.

Besides women’s heavier family burden, their free time has lower quality. Research shows that women is under more pressure than men during free time (Mattingly & Blanchi, 2003). Because women’s activities are usually around their family, the family role still binds them. We can easily find examples in daily life. In activities such as hiking and family movie night, women still need to take care of the family. Some people call the self-report data into question, arguing that the measurement is biased by different ways individuals report their feelings. But the sample size is big enough (more than 500 people) to eliminate influential bias. So women’s low interest in work is related to low quality of free time.

An economic model explains how child-care program decreases women’s work effort (Heckman, 1974). The assumption is that wage has a positive relation with work passion. Because of child-care program, women’s labor supply is divided. And this task has no money feedback. So child-care task decreases women’s wage ratio relative to the same supply. The financial cut back will decrease women’s work passion. As another evidence, the research also shows that women with low productivity in family tend to be more active in work field. We can conclude that nurturing children hinders women’s interest in work. Again, women’s lower passion in long time work is not innate; it is impacted by external world.

As for our second question, the authors give a simplified assumption without proof: long time work is related to success. Long work time never equals to success. In contrary, it brings low effectiveness (Golden, 2012). The longer you work, the more productivity you have. But be careful, the productivity growth-rate diminishes. The longer one works, the lower effectiveness he or she has. Long-term overwork also increases risk of health problem and depression. Though in certain situations, the hard work method is beneficial to someone, we adopt the opposite theory because it has universality. We should not simply link work time with success potential. So the logic behind the article is not stable.

In short, women’s lower interest for long time work fails to reflect women’s innate lower interest in career. Women’s vigor is dispersed by family life and the link between work time and success is vague. However, my statement has limitation itself. A perfect experiment about women’s interest may never be done, because extraneous variable always exists. So I am on a safe position to point out unstable statement of the article. A more practical action is to change women’s situation in family. Today, men’s participation rate in house working increases, but equality in nurturing children and house working is still idealistic. New research should focus on how to equally distribute family burden to both genders.

Reference

Lubinski, D. S., & Benbow, C. P. (2007). Sex Differences in Personal Attributes for the    Development of        Scientific Expertise. American Psychological Association.

Mattingly, M. J., & Blanchi, S. M. (2003). Gender differences in the quantity and quality of free time: The     US experience. Social Forces, 81(3), 999-1030.

Golden, L. (2012). The Effects of Working Time on Productivity and Firm Performance, Research        Synthesis Paper. International Labor Organization (ILO) Conditions of Work and Employment Series, (33).

Heckman, J. J. (1974). Effects of child-care programs on women’s work effort. In Marriage, Family, Human Capital, and Fertility (pp. 136-169). Journal of Political Economy 82 (2), Part II.

Newcombe’s article has an unusually neutral position. Newcombe talks about Lawrence Summer’s argument and the negative influence of itsmisinterpretation. She mainly evaluates the interpretation that sex difference of intelligence is biological based and unchangeable. She points out that there is little evidence of extant biological explanations and she argues that though sex difference can be eliminated through training, intelligence ability is one of many elements that contribute to science success so we should more focus on education. Many parts of her analysis convinces me. However, the effort to contain opposite viewpoints makes her article confusing and her rejection lack linkage. Although I believe in the authenticity of evolution psychology theory and think that it can explain differences between men and women, it should not be the only factor focused on today. The veracity of biological evidence should never be obstacle for women in their career lives. Newcombe’s rejection approach is good but she arrives at it for the wrong reasons.

Newcombe over looks the differences in division of men and women’s social labors. Evolution theory says that primitive men target at prey to hunt and women search for fruit without targeting at certain objects, so such different duties has improved men’s spatial ability. Newcombe believes that men do not usually use spatial ability to hunt and women need spatial ability too to search for food. Yet her assumption is more farfetched. First, opposite to the author’s inference that men use traps rather than follow the prey to hunt, in many primitive tribes today, men follow prey for three to four days and use spears to kill it. Second, focusing on a fruit and quickly switch to another is very different from aiming at one target for a long time. Women and men may have different types of searching ability. Research shows that women are better at finding objects in brand visual field while men are better at focusing on one target, which fit in the evolutionary theory. I believe the evolution theory because it exists. In nature, many species have distinct difference among male and female. Female insects usually have much bigger volume and are more aggressive for breeding offspring. Male mammals usually have stronger body to protect their occupation of mate partner and their children. Among the same species, we should not overlook the difference between male and female.

Author’s claim that men don’t need spatial ability to find women for reproduction and gain reproductive advantage ignores opposite evidence either, for men need to trek between different tribes to find female spouse. The author disputes the generalization to human from an experiment that shows male vole, who needs to search for female to mate, has better spatial ability than female. Female human, unlike vole, live in a tribe rather live separately. Yet though human females live in tribe, marriage usually won’t happen in the same tribe, so male still need spatial ability to find female in other tribes. Also, research reveals that women tend to find stronger, more athletic men; such tendency has imprinted on female’s unconscious mind. Such physical advantages include ability to hunt, which engaged with spatial ability. A simple question, if spatial ability fails to give men productive advantage, how could it maintains in gene, and spread all tribes across the world?I think men actually gain some productive advantages.

Although the correlation between spatial ability and biological basis is unclear now, it is hasty to link it just to accident. True, some gene mutation happens, but the actual accidents will be weed out and the ones conserve have pass through nature selection. Moreover, to analogize spatial and acne is improper. Acne is a skin disease but spatial ability is an inner element that can affect our behavior in many dimensions. Moreover, acne may not be an accidental as it linked to male’s high metabolism in adolescence. Thus, like acne, spatial ability is likely linked to certain function that important to male. In a word, distinctive spatial ability is not accident.

Other than her rejection to evolutional theory, her objection to other biological theories conflicts with each other, as she implies sex difference appears at older age as maturational without intention to focus on that. Arguing whether sex difference emerges at early ages is caused by biological basis, Newcombe refutes the biological theory by saying that early-emerging effect is more likely produced by environment, and late-emerging effect is more maturational. However, such argument mixes with following statement: more obvious sex difference emerges in middle and high school. Such statements convey the information Newcombe doesn’t mean to highlight: sex difference in older age period is maturational.

Though Newcombe’s arguments lack linkage, her main point that we should not focus on unchangeable sex difference and that it doesn’t link to scientific success reminds me of the nature of serendipity in science, thus highlighting that sex difference is meaningless, even harmful. She compromises that the sex difference can be hard to eliminate even by such training, yet it never has had a dominant effect to academic success. We fail to state a linkage between intelligence and scientific success. First of all, does science retain the most intelligent brains? Fifty percent students in Princeton University choose careers in financial field.(Rampell) Science has become unpopular among smart students due to its low salary and arduous laboratory work. We will find it hard to prove that people in science field are intelligent. Moreover, can we imply a correlation between intelligence and success? Probably not. Proof by fact, success is more related with chance rather intelligence, just like success of science. Most scientific success is rather serendipity than result of wisdom, such serendipity more reflecting diligence of scientists rather than intelligence. For example, the discovery of nylon. However, I have to compromise that the science successes is circumscribed at science field, as success of mathematics is more related to intelligence.We can infer from the truth that focusing on women’s weakness is only meaningless and will truly become an obstacle for women scientists.

In “Taking Science Seriously”, Newcombe fails to refute the evolutional theory by strong evidence. But her opinion about limited correlation between spatial ability and science success is right. She fails to use the right reasons to approach her purpose as decrease the influence of biological sex difference theory. Based on fact, there are many factors influence a scientist’s career success, and intelligence may just play part role. And the research about biological explanation for sex difference in spatial ability is endless. We are hard to find a perfect answer. In contrary, we shall focus on how to retain intelligent group in science and how to train both men and women to improve their ability as part of them will become next generation of scientists.

Citation:

Newcombe, Sex differences in spatial ability and spatial activities in Why there are few women in science? Ceci and William

Catherine Rampell, http://economix.blogs.nytimes.com/2011/12/21/out-of-harvard-and-into-finance/?_r=0

What if I asked about your attitude toward Lawrence Summer’s address that women’s innate reasons cause their absence in science? Well, the issue has been debated again and again that even for the same argument, there are lots of different explanations. Sex, math, and science, an academic response of Lawrence Summer’s assertion, points out Spelke’s belief that it is not cognitive difference but social discrimination causes women’s absence in science. Her statements that gender schema and discrimination are reasons for the phenomenon are very convincing, but part of her statements lack logic and can be questioned.

Spelke’s points about gender discrimination and social elements are very convincing. I believe that women’s underrepresentation due to discrimination decrease science’s attractiveness to young female. And I believe that Spelke’s statement about women’s plausible low interest in science: it is not women’s lack of interest but more the invisible cost women need to pay to pursue a scientific occupation that stops women’s pavement to science career. She points out that children will be treated differently because of their gender, as parents always see boys as stronger, more intelligent, and aggressive. People’s assessment about candidates’ competence is different towards male and female, in which people tend to believe males have more ability and tend to doubt females that show extreme competence in their resume. Spelke’s data convinces me. It reminds me about social schema theory and several similar experiments. First is about judgment of ability of different genders. When men and women have similar resume, people tend to see male candidates as more competent. And when female candidate are especially competent, people admit her ability but describe her as more hostile (Heilman, Wallen, Fuchs, Tamkins, 2004). The second experiment shows people’s standard shift: there are two candidates that either have more education history or more work experience. When the former is male and latter is female, people tend to choose the former. But when their gender switched, people change their standard to support the male (Norton, Wandello, 2004). Furthermore, even females tend to underestimate female themselves. Both experiments convince me about the existence of the influence of social stereotype to women. In many situations, becoming a scientist means that females have to tolerate extra pressure and bias, discrimination of workplace and extra difficulty to advance. In China, there is pressure of marriage and advancement difficulties for female scientists, stemming from people’s biased attitude and negative description on media. In three top universities ( Beijing University, Tsinghua University, GUCAS), eighty percent of women doctoral students doesn’t have relationship (Tingru Li, 2008).

Though I agree with Skelke’s viewpoint, her rejection towards sex difference in cognitive ability has many logic loopholes. She rejects Summer’s three factors that women focus more on people, women are less talented and women are less motivated. I think her logic isn’t convincing. The first factor is that men are more focused on objects, and girls on people. Without a definition of “focus on object” and “focus on people”, Spelke compares the time male and female infants need to study discerning the distance an object moves and study how to build stacks. Depends on equal time period infants need, she infers that infants of different genders have same abilities to learn about objects, thus there are no different focuses for males and females. However, Spelke’s assumption is that similar time to learn something means equal focuses and interest on such thing. I don’t think so, as interest does not equal ability. One may has ability to do one thing but doesn’t have interest in it; one can also lack the ability to do a thing but has enthusiasm about it.

The second factor is the different mathematic and spatial ability of men and women. Spelke compromises that adult of different genders have different favored types of mathematics abilities, which may be a key variable in high-level mathematics. She makes a great point that the SAT test doesn’t have equal items that favors men and women, so the SAT data cannot reflect aptitude of women and men. Spelke’s assumption is that mathematical abilities that favor male and female are equally important in high level math. However, what if the distribution of mathematic ability doesn’t equal the abilities needed in the high level? What if some kinds of abilities are especially important in the high level math that favors certain gender? Other study implies that the ability of spatial and rotation, which favors male, may be the key ability to achieve high-level success in mathematics.

Moreover, the following experiment about effectiveness of studying mathematical materials of male and female students has lots of uncontrolled variables. Spelke’s first assumption is that amount of males and females taking math course and their grades can reflect math aptitude of different genders. But I doubt it. People will find it farfetched to link a student’s class choice with his or her aptitude. If a student’s attendance of mathematic class proves his or her high aptitude, the student doesn’t need to study hard to prove it anymore. We can just choose four most difficult mathematical courses and then we can convince that we are geniuses. As for grades, there are more than one variable. What if one student studies very hard to get certain grade and another one just feels easy to get the same grade? Do they have the same aptitude? I don’t think so. As there are many extraneous variables, the validity of such study can be questioned. The study may not show a suitable causal variable of aptitude but may just reveal a correlation. In addition, there are other research suggests that men have higher aptitude. In such research, men and women are asked to solve questions that were not already rehearsed in a classroom, and males get better scores (Felson & Trudeau, 1991; Wainer & Steinberg, 1992).

In her rejection to the third factor that there are more male geniuses, she equates some objects that have different definitions. She uses the male-female ratio of mathematics major to measure the geniuses in each field, which reveals equal numbers of male and female in this major. So she concludes that there are not more male geniuses. However, her assumption, again, shows simplification that composition of genders reveals the composition of geniuses of different genders. For example, there may be ten percent of male students have high talent but only five percent of female students have such talent. The geniuses are people have high mathematics abilities, and they don’t have causal relationship with major choices. There is also opposite research shows that there are especially large difference in tail of intelligence distribution in one percent, five percent and ten percent of different genders. And males excel over females ( Hedges& Nowell, 1995).

As conclusion, though Spelke’s inference about sex difference of cognitive ability has some loopholes, her points about gender bias and discriminations convince me. Again, back to Summer’s assertion, the debate of cognitive difference of males and females still need further evidence. I hope new research will reveal deeper reality.

Citation:

Hedges, Nowell, Sex differences in mental test scores, variability, and numbers of high-scoring individuals.

Doreen Kimura, Underrepresentation or misrepresentation?

Tingru Li, Walking along in the edge between male and female—female doctorate “ third gender” phenomenon analysis.

Virginia Valian, Women at the top in science——and elsewhere.

Synopsis

Is Math a Gift, an academic paper of Dweck, states a brand new angle that it is not the lack of ability, but the combination of entity belief and stereotype makes girls venerable when face academic obstacle. At the same time, girls who believe talent can be gained through effort aren’t not shown grade trap when meet set back. So it is not the difference of ability but different venerabilities to set back that makes women have lower grades in science classes, as boys are less venerable than girls. So the effort to make girls believe in incremental theory may eliminate the gap between male and female in science class, because people’s ability decreases when they believe they have lower ability. Dweck ends up by arguing we should teach students incremental belief in school, implicating we should ignore the influence of the innate element.

Dweck’s assumptions

There are some uncertainties within the author’s assumptions. First, the author points out a phenomenon: the higher IQ a girl has, the worse a girl does when facing difficulty. Then she points out that only intelligent girl who believes that talent is a gift is venerable to setback. The rest of intelligent girls who believe that talent can be nurtured are not that venerable. Then how did she come up with the first theory that girls with high IQ are venerable, since part of them has been defined as “not venerable” later? Second, Dweck focus on top grade girls’ phenomenon at the beginning, saying that girls with high IQ are more venerable than girls with low IQ. But the following parts are focusing on two types of girls who are defined by different beliefs of talent. The author does not mention the girls have top grades anymore at the rest of her article. She highlights the way to classify girls by their grades at first then follows by a different method as to classify girls by their beliefs to talent. I don’t think the two methods are compatible. Third, she doesn’t point out the reason of phenomenon that girls with high IQ are venerable than girls with low IQ. Forth, Dweck also confuses two variables that have small difference: venerability and lack of confidence. The former part of essay is talking about girls’ venerability while the latter part silently switches the point “venerability” to lack of confidence and implicates that they have the same meanings. These two terms are not same.

Don’t tell the truth can be a correct choice

Well, there are some uncertainties in her article, but also, she puts forward an interesting solution for girls’ venerability which may involve complex social paradox: to conceal the scientific truth may be helpful to promote girls’ performance in math and science. And I generally agree with that. In a modern society, equality and humanity is the main thesis. There is even research showing biological difference between gender, race or even different persons, the equality is always the most important thing. We can indeed see the positive effect of the talent-growing belief to women. We have the reason to believe, when the incremental theory collide with education in school, women’s academic performance will improve rapidly. In my high school in china, teachers told us that hard work can bring good grade. There are more and more girls decided to choose engineering or science as major; they think the major could prove their ability in logic and systematic thinking.

Other than gender’s issue, there are many examples shows that keep the research truth may be a better way to improve people’s equality. The judgment of certain group’s ability is not moral. There is some research showing that black people’s intelligence is lower than that of other races. The social effect of these research make public and black people themselves see black people with a low grade as normal thing. However, black people show by their effort that they can succeed in academic fields, Derrick Bell, the first black professor at Harvard University, is a good example. So we can clearly say that speaking out some research studies do harm people. A better way is to encourage them and make them believe there is way to promote their ability.

Conclusion

As a conclusion, Dweck states that girls’ belief of entity theory makes them venerable to setbacks. And she argues to apply incremental theory to education to decrease the gap between grades of men and women. Though there are some shortcomings about Dweck’s assumptions, her solution to decrease the gap of ability of women and men is worth thinking.

Reference:

Dweck, C. S. (2007). Is Math a Gift? Beliefs That Put Females at Risk. Why Aren’t More Women in Science? Top Researchers Debate the Evidence.