When asking different people with successful careers the question, what do you look for in potential employees, every person will have a different answer. Some may say that it is strong leadership qualities; others may say that it comes down to grades. There is no uniform answer. In Berenbaum and Resnick’s essay, “The Seeds of Career Choices: Prenatal Sex Hormone Effects on Psychological Sex Differences”, the two authors assert that though spatial skills and math skills are important for having a career in science, other sex-related characteristics may be more important in career choices and success. This leads to me to ask the question: how does one determine which traits and characteristics are more important than others?

The influence peers and family members play on someone from an early age may be important, but cannot be said to be more important than the ability to perform well. Berenbaum and Resnick argue that peers have a greater influence on one’s choice in career field. While I believe that the people we are around play an influence on what path we choose to go into, I am unsure of whether or not it plays a greater influence than how skilled we are in that respective field. Using Berenbaum and Resnick’s line of argument, if society fosters a better environment for girls and make them more interested in STEM subjects in school. This in turn may create a greater chance for more women to go into that career field, but will these women be hired if their grades don’t match up to that of men? There are still many other factors one considers other than interest, one of them being good spatial and math skills that play a large role in determining the success in the STEM field. Employers look at potential employees holistically and many times, grades and ability to perform well is what gets the potential employees in the door. Once their grades and scores meet the minimum requirement, employers will then look at interest levels and other characteristics. While having a great interest in a career field is important, it is not the most important trait that employers look at.

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Though biological disadvantages in spatial abilities seen in women does not mean that women aren’t able to succeed, but this problem should be taken into account rather than just dismissed. Berenbaum and Resnick continues their argument that sparking an interest is the beginning to having more women in the STEM field. This interest leads parents to be more inclined to foster an environment that will help them learn more and be better at spatial and math skills, thus closing the gender gap in spatial and math ability. However, men are shown to have greater spatial ability than women biologically. Even though there are ways of improving spatial ability in women, this improvement still has not been able to match men’s spatial ability. I agree with Berenbaum and Resnick that biological disadvantages in women does not mean that women are unable to be successful in the related career field. However, this does not mean it should not be taken into account and be deemed to be of lower importance.

Helping more young girls be interested in STEM subjects by fostering an environment where subject fields are not stereotyped by gender is important. However, should this be more important than improving spatial skills or other factors employers will look at? I would argue that it is not and all factors should be held of equal importance because every employer looks at such factors differently.

Why is there such a great gender disparity in the STEM field? Many different researchers and authors list sex differences in spatial skills and cognitive abilities as the reason to why there are more men than women in the STEM field. In Melissa Hines’ essay, “Do Sex Differences in Cognition Cause the Shortage of Women in Science,” it is proved sex differences in cognition are not the cause of the lack of women in the science field nor is it linked with hormones or genetics. Hines states that expectations and behaviors of society’s reaction to the lack of women in the STEM field are better reasons to explain the lack of women in the STEM field. After reading several articles on this topic, I have started to question whether my original views regarding sex differences and their role in workforce gender disparity are correct or valid. If cognitive sex differences do not seem to be linked to hormones or genetics, are we taking correlated data to assume causation? Hines’ essay makes me realize there is not enough proof regarding more men being in the STEM field due to cognitive sex differences. This is due to the inability for researchers to look at the larger picture in relation to possibly contradicting data presented. Instead of taking in all the data that is presented, they only look at specific pieces of data. This leads to many assumptions that should not be made as the reasoning behind sex differences in cognitive abilities.

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Researchers wrongly assume that cognitive sex abilities are genetic by looking at small pieces of data in detail instead of looking at the larger picture. An example of such is how researchers make the assumption that gender differences automatically conclude a link to genetics. However, this assumption should not be made because if so, we should see the same results across all races, economic background, and age. But this cannot be found, as this problem is usually seen in people in higher socioeconomic families. Hines shows how sex differences in height have a standard deviation of 2.0 while cognitive sex differences have a standard deviation of 0.9 units. This proves that there isn’t that great of a difference between male cognitive abilities to that of female in comparison to other traits. However, researchers tend to take the standard deviation in cognitive sex differences as large because a standard deviation of 0.8 units or above is seen as large. They tend to take this “large” standard deviation and link it to higher test scores in men and lower test scores in women. However, when we look back and compare that value to the sex differences in other traits such as height, we can see that the differences are actually very small. Why is it that we take such a comparatively small difference in cognitive abilities and conclude that it can have such a great reaction in the work force? This is because researchers only looked at the small pieces in the puzzle, not the bigger picture. They have cherry-picked research to show causation where it does not exist.

In addition, Hines also asserts that biases are often present in these research projects. From the selected group of people used for research on whether cognitive abilities linked to hormones, Hines shows how the results prove that the data correlates. However, it cannot be proved that sex differences are hormonal and that men have greater cognitive abilities because there is a selection bias in who gets chosen for these research projects. Oftentimes, the pool of candidates used for these research projects are people of higher intelligence. By using a limited variety of people, the data received will seem to correlate; however, if we take people with median intelligence levels, the intelligence test scores vary and tend to show different trends. In David Lubinski and Camilla Persson Benbow’s essay “Sex Differences In Personal Attributes For the Development of Scientific Expertise”, they show a graph (Ceci and Williams, 81) showing girls in the median IQ score band are scoring higher on tests than that of boys. The data taken if a greater variety of people were included in the research would probably show something different. The data many researchers use correlates due to the selection bias, but with insufficient diversity in research participants, it is hard to conclude that the data proves causation.

In conclusion, it is improper of researchers to conclude that cognitive sex differences are the cause of the lack of females in the STEM field because their research is cherry-picked and includes biases. Researchers must look at the larger picture to eliminate assumptions wrongly made and come to stronger conclusions that can be made from using all data found.

Sources:

Ceci, Stephen J., and Wendy M. Williams. Why Aren’t More Women in Science?: Top Researchers Debate the Evidence. Washington, DC: American Psychological Association, 2007. Print.

With many authors taking a firm stance of either being an incremental theorist or an entity theorist, Nora S. Newcombe takes a stance that incorporates both theories in the conclusions found in her essay “Taking Science Seriously: Straight Thinking About Spatial Sex Differences”. Newcombe concludes that while men may have an upper hand than women from having greater spatial abilities genetically, spatial abilities can be improved over time, therefore lessening the intellectual gap between men and women. She reaches this conclusion by discussing the evolution of the cause of sex-related differences, the misinterpretation between correlation and causation made by many, and the ability to improve spatial ability. While Newcombe has not yet found evidence that shows women improving in spatial ability so greatly to be equal to that of men, she argues that employers should also look at other measures to define potential success in a company on top of spatial skills, and that the importance in educating spatial skills to improve the overall skill as a whole society. The limitation in scope of Newcombe’s argument overemphasizes the necessity of high spatial skills. While her points about looking at other measurements are true, at times it is unrealistic with the inability to look at such measures of success objectively through quantitative measures.

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Just as schools look at a variety of factors to decide on whether or not a student is the right fit for a school, employers should do the same thing in their hiring process rather than solely focusing on spatial skills even after realizing that such skills can be improved over time. When high school students apply for college, while schools put heavy emphasis on standardized test scores and GPAs, there is a holistic look at a student that includes extracurricular activities, letters of recommendations of a student’s attitude and behavior in a classroom setting. The same can be said about the hiring process for potential employees. Newcombe provides research that shows how for children and adults, spatial ability can be improved over time with practice through activities such as academic work, musical training and, computer games. However, she is unable to show a point of convergence between men’s spatial abilities and women’s spatial abilities. Therefore, there is still a lack in a woman’s spatial ability compared to that of a man. Newcombe argues that even if it is so, the success of a person in the STEM field is derived of more than just spatial ability, such as creative thinking and leadership capabilities. I agree with Newcombe’s statement because oftentimes employers look at the whole package, not just the quantitative data. For example, how well a person works in a team dynamic, or whether they can contribute a lot in a conversation are all qualities employers look for in their employees that is not seen through test scores. Therefore, the determinant of a successful employee in the STEM field should be more broadly defined than spatial ability. The problem with this is that it is hard to quantitatively show this. Creative thinking and leadership skills cannot be measured and is solely based on the judgment of the employee making the decision on who to hire. These traits are purely subjective which makes it hard for an employee to argue for why they hired such an employee based on these standards. Therefore, we are unable to tell how much this plays a role in the decision to hire a man over a woman. It is hard to research such factor. For example, it is hard to determine how one person may be able to think more creatively than others. Such qualities are very subjective and are hard to look at objectively and put a number to it.

It is important for society to increase their spatial skills as a whole when looking at how to maximize the number of people available for employment that require spatial skills. However, there are other problems that account for the limiting number of people available for employment other than spatial skills such as the difficulties in having a work-life balance. Newcombe states that instead of only focusing on explaining how these sex differences come about, to increase the number of people available to work in jobs that require spatial skill, we must focus on finding out how to teach spatial skill. I agree with Newcombe’s conclusions, as women should improve spatial skill to get to the level of that of men, society as a whole should also continue to work on the improvement of spatial skill. This would increase the quality of work done in employment and level of intelligence in seeking employment will continue on an upward trend as it is a major factor that companies look at. However, I would add that there are other solutions to maximize the number of people available to work. In Dr. Lucie Schmidt’s talk, “The Balancing Act: Work, Family, and What Economics can Tell Us about Women’s Choices”, she talks about the evolution of the female labor force participation. Prior to the 1960s, there was a slow and steady growth in the female labor force participation rate, with a strong increase from the 1970s-1990s. However, we have now reached a plateau. The United States ranking has fallen over time for female labor fore participation rates. While the rate has been constant in the United States, the female labor force participation rate has been increasing in other countries. Dr. Schmidt lists off a few reasons for why the female labor force participation rate has hit a plateau, some which include the leveling off of egalitarian gender role attitudes, depending on the city, the high commuting time and cost, as well as the lack of child care in addition to the new trend shown of how families are now spending more time on childcare. From this data, it can be seen that another solution to increase the number of people available to work is by trying to solve the work-life balance problem that is more heavily faced by women by pressure of societal norms, as well as tackling the problem of the leveling off of female labor force participation rate. The lack of spatial skills is only one of many problems society is facing when looking at the limiting labor force participation rate.

Spatial ability is important. However, while spatial ability is one measure of the ability to succeed in the math and science field, success can be measured in a number of different ways. While this may cause difficulty for companies in the ability to measure these other factors, it is important to take them into account. While society should focus on how to teach spatial skills to increase potential workers, this idea is limiting and is not the sole solution. This argument must be expanded to include solutions for other problems that contribute to the limiting number of potential employees.

The most famous and controversial opinion of why there are more men than women in the STEM field is from Harvard University’s former president, Lawrence Summers. Elizabeth S. Spelke and Ariel D. Grace’s essay “Sex, Math, and Science” explores the three reasons Summers listed for the reason for the gender gap in the STEM field and proves why Summers’ arguments are flawed. They then go on to prove how men and women are stereotyped from a young age, which in turn deters women from entering the science and math field, as well as the distorted perception of how women are treated in the STEM field.

Spelke and Grace focuses on tackling popular claims society has made about men having more skill in math and science than women do, starting off with the claim that men tend to learn more about mechanical relationships while women tend to learn more about human relationships between people, therefore men tend to follow their stronger skill and go into math and science. However, Spelke and Grace proves that this statement does not hold true. At infancy, male and female toddlers learn the mechanics of objects at the same rate, with girls learning earlier than boys the correlation between the forces exerted on an object and the distance of the object. The same research is proven to be true throughout development. I would agree with the research that Spelke and Grace used because girls and boys are taught the same things from a young age and tend to do the same things, therefore neither sex is given an upper hand at a certain skill.

Retrieved from: ibtimes.com

Spelke and Grace also bring in research on how men and women use different strategies to go about the same math problem, which means that they tend to have different speeds for tackling different types of question. They then go on to prove how many standardized tests, like that of the SAT-M test, used as a yardstick to measure men and women’s aptitude in math is inaccurate and gives men an advantage over women. If given the assumption that the SAT-M test was questions taken that were most similar to those found in the mathematics field or most similar to tasks companies would need people to do, then I would disagree with what Spelke and Grace have found. From an economics point of view, a company would hire the person who is most efficient. If the questions from the SAT-M reflect well upon the questions that students would need to know for that line of work, and men tend to test better in it just because their strategies are faster for those types of questions, companies would hire men over women who tested better because time is an important and limited resource. However, if the SAT-M test questions were not an accurate representation to that of questions found in the real world, I would be inclined to agree with Spelke and Grace on the tests being the problem, as then it would benefit men more than women while still having questions that are inacurrate representations of what is expected to be known in the workplace.

When giving their own solution, Spelke and Grace believes that the problem is in parents’ gender bias and how they raise their children with certain stereotypes they believe are true in certain genders. From the research they have concluded, Spelke and Grace make the assumption the parents tend to overestimate their sons while underestimating their daughters. While unsure of whether or not this assumption is true, if it is, I would agree that this causes a hindrance in development in the math and science field because parents who overestimate their children tend to encourage them to do more, while parents who underestimate their children to do discourage them to do more or to do something that seems to be hard, such as working in the STEM field.

Spelke and Grace bring in many new points. While unsure of whether or not I am in complete agreement with the arguments due to the overwhelming amount of research but lack of depth when describing them, I believe that they have brought up good points that society must take a look at.

After looking at the incremental theorist argument and the entity theorist argument, Carol S. Dweck takes a refreshing stance in her essay “Is Math a Gift? Beliefs that Put Females at Risk” that looks at both stances objectively to determine which one is better. After different experiments and research dealing with both beliefs in women, Dweck comes to the conclusion that it all comes down to the mindset of women and their education. She goes on to conclude that women who believe that their capabilities can be strengthened over time with practice and commitment leads to an equal number of men and women in the STEM field. What causes the problem is the mindset and attitude that a person’s skill cannot be harnessed over time; you can only use what you are given.

Retrieved from: blog.chocchildrens.org

Dweck starts off by pointing out an inherent difference between boys and girls. When given a test with hard questions in the beginning, boys tend to use the confusion they feel to fuel their motivation to try harder and do better. However, with girls, their attitude will automatically want to make them give up, therefore leading them to do worse overall on the test. Dweck uses this as the foundation to her research. She reasons that because the data was taken from students of such a young age without the idea of gender stereotypes, that this would not come into the equation, thus making the assumption the stereotyping genders does not play a role when trying to find a solution with this problem. I do not agree with this mindset that gender stereotype does not play a role based on the fact that the research was done on such young children. Just because it may not have existed in that point of their lives doesn’t mean that it won’t in the future.

One of the research Dweck uses to prove how much different this attitude changes scores is by taking one group of girls and instilling the idea that their skills and abilities can be developed and improved, and taking another group of girls and teaching them that their skill is a gift that cannot be changed. Dweck goes on to prove that the girls who were taught with an incremental theory had equal test numbers to that of the boys while the other group scored significantly lower compared to boys. While I do agree that attitude plays a role in how well a person will do on a test, I would not say that it is a well-rounded enough argument to only argue that point. How come this gap is seen so greatly in the STEM field and not other fields? How would Dweck explain the fields of work that are predominantly women, such as the nursing field? Does that show something of men’s attitude? Dweck has also only used test scores to prove the disparity in the STEM field, making the assumption that when companies hire employees, they would only take test scores into consideration. However, I would argue that while test scores is very important, I would argue that they would look at other factors as well, such as experience, skills that one may bring to the table other than testing well. Just like the university admissions process, the firm will look holistically at a person, some subjective, such as the interview portion, some objective, such as the test scores received.

While I do agree with Dweck’s points made, I believe that she does not go far enough to fully answer the question. Attitudes of women do create change. However, the flaws made in her argument causes me to question whether there are other variables that come into play that may help answer the question.