Power Privilege and the Purse (Humanities)
In this project, the entire 11th grade looked at inequities in America, and, after a lot of reading, writing, and research, we put on a symposium at the Vista Community Clinic, titled "Mind the Gap: Bringing Mindfulness to the Equity Divide in America". My role for the symposium was being an Event Organizer, so I was one of the behind the scenes workers, making sure the event went smoothly (both before the night of, and during). My role was also in charge of contacting guest panelists, coordinating between all of the students, and other things.
After doing this project, I now know more about personal finance, and how important personal finance is to a good future. I also know a lot more about the economy, and some of the political issues surrounding it (as well as some other political issues surrounding the economy). This all led up to our discussion of widespread inequality in the USA. I never knew that, first of all, we as a country were so much less equal than everyone else. and also, that our 1% was SO much wealthier than out middle class, and even our upper-middle class. I also learned about a lot of the social issues in the USA today. Mostly, we covered gender and race prejudices/privileges, which was interesting, especially hearing from those with different racial/gender backgrounds than me.
The most memorable moment from the symposium for me was seeing the audience's reaction after all of the incredible spoken pieces (including the opening and closing keynote speeches, and all of the performance artists). I introduced both keynote speakers, and some of the performing artists, so I got a front row seat to all of those performances. I absolutely loved seeing the audience react in real time to these amazing pieces. It gave me the feeling that our symposium, while not over yet, had already made people stop and think, which, I think, was one of the main goals of the event.
Apart from the symposium, everyone also wrote position papers about the accessibility of the American Dream. Here's mine!
Unfair Discrimination Towards Women in STEM
Kirsten Zornado
Kirsten Zornado
If I were to get a job in mechanical engineering today, I would be a part of the 7.2% of women in that field (Women in the Labor Force...). There has long been an unequal distribution of men to women in STEM fields, though not all of them as stark as this. The really important question in all of this, though, is why? The innate sexism in our country is a barrier to women who are entering STEM fields hoping to achieve the American Dream. This is shown through implicit bias in society against women in science, the fact that women are still not paid as much as men, and positive and negative reinforcement affecting women’s performance.
There is a societal bias against women in STEM fields that prevents them from succeeding in those fields. In a study performed at Yale, participants were given one of two near-identical resumes, one with a man’s name (John), and one with a woman’s (Jennifer), who were applying for a job in STEM, a laboratory assistant. Participants were asked to rate the applicants in multiple categories, including competence, hireability, and likability, and were also asked to give the potential employees a salary. Both applicants were qualified for the job, though they had small drawbacks as well. The results were unanimous. No matter the age, background, or sex of the participant, they rated John an average of a half-point higher than Jennifer in every category except likability. The salary also reflected this, with Jennifer getting an average of $26,508, compared with John’s $30,238. (Pollack)
This study shows that everyone, even women, have an implicit bias towards men in science, with no difference in actual ability of the candidate. This is shown because of the separate, unequal treatment of Jennifer and John in both the way they were rated, and their hypothetical salaries. This discrimination in participant’s views of the applicant’s abilities means that women are less likely to get jobs in STEM than men, and less likely to be paid as much as a man, who is doing the same work. This implicit sexism limits women’s access to the American Dream, and perpetuates the lack of women in STEM.
Harvard, the University of Florida, the University of Washington, and many other schools worked together to create an implicit bias test on the internet. An implicit bias is an automatic attitude about something that is under the surface of your outward beliefs, something that you may not even be aware of believing, or even support outwardly. Implicit bias is often caused by not seeing something very often, or being used to seeing something else. The test on Gender and Science’s results are below
There is a societal bias against women in STEM fields that prevents them from succeeding in those fields. In a study performed at Yale, participants were given one of two near-identical resumes, one with a man’s name (John), and one with a woman’s (Jennifer), who were applying for a job in STEM, a laboratory assistant. Participants were asked to rate the applicants in multiple categories, including competence, hireability, and likability, and were also asked to give the potential employees a salary. Both applicants were qualified for the job, though they had small drawbacks as well. The results were unanimous. No matter the age, background, or sex of the participant, they rated John an average of a half-point higher than Jennifer in every category except likability. The salary also reflected this, with Jennifer getting an average of $26,508, compared with John’s $30,238. (Pollack)
This study shows that everyone, even women, have an implicit bias towards men in science, with no difference in actual ability of the candidate. This is shown because of the separate, unequal treatment of Jennifer and John in both the way they were rated, and their hypothetical salaries. This discrimination in participant’s views of the applicant’s abilities means that women are less likely to get jobs in STEM than men, and less likely to be paid as much as a man, who is doing the same work. This implicit sexism limits women’s access to the American Dream, and perpetuates the lack of women in STEM.
Harvard, the University of Florida, the University of Washington, and many other schools worked together to create an implicit bias test on the internet. An implicit bias is an automatic attitude about something that is under the surface of your outward beliefs, something that you may not even be aware of believing, or even support outwardly. Implicit bias is often caused by not seeing something very often, or being used to seeing something else. The test on Gender and Science’s results are below
This graph shows that 72% of people who took the test had some automatic association with males and science, and females with liberal arts (Project Implicit). This association has been created in our minds because of repeated insistence by society (and our own experiences) that the association is correct. In this case, that means that associations with women in science are viewed by society as “wrong” (or, at least, less common).
As said by the Project Implicit FAQ, “One solution [to having unwanted biases] is to seek experiences that could undo or reverse the patterns of experience that could have created the unwanted preference... That could mean interacting with people that provide experiences that can counter your preference.” This is saying that one of the ways to counter unwanted biases is to directly contradict them, which suggests that the cause of the bias is not being exposed to the thing you are biased against. This means that, though we are seeing more women in STEM fields, they are still not common enough to have implicit biases level out.
Financial bias against women is another barrier to their access to the American Dream. In 2011, there was a jump in the amount of male nurses in the United States, up to 10%. In tandem with this, male nurses got a jump in pay. “In 2011, the average female nurse earned $51,100, 16 percent less than the $60,700 earned by the average man in the same job.” (Cummings). This means that, in a traditionally female dominated field, men that are doing the same job as women, are getting paid 16% more than women. As above, this means that there is some kind of implicit bias against women in STEM, that allows men to earn more money in the same jobs. This pattern is thought to be caused by men simply being more confident in their work, and their deserved pay, than women.
Many studies have shown that men are more aggressive and confident in their abilities than women. All of the studies vary in content, but they almost all show the same thing - women being less cutthroat, and more generous, than men with their money. There were other studies that showed that women were more likely to be aggressive in negotiation if they were negotiating for someone other than themselves. In other world, they negotiated harder when talking about other people, which shows a reluctance to put their interests above others’. (Cummings) This can be applied to the above case because of differences in men versus women negotiating for salaries. Men are more likely to ask for things like a bonus, raise, or even promotion, than women. This simple psychological difference leads to less women earning these benefits than men.
The above mentioned study performed by Yale, with the resumes labeled either John or Jennifer, shows this financial bias as well. With absolutely no difference in the resumes other than name, John got a salary that was $4,000 higher than that of Jennifer. This smaller salary (and smaller chance of getting the job) will deter Jennifer from going into this career, and potentially from continuing in this subject at all.
The negative reinforcement towards women in STEM has a detrimental effect on their performance in those fields, and, eventually, their willingness to stay in the field. 41% of early career STEM workers are women, but 52% of them drop out before their mid to late 30’s (Hewlett). This means that, although there has been an increase in women in STEM (Women, Minorities...), they are not staying in STEM, because of negative stereotypes.
This is sometimes because of women becoming isolated. This can be being the only woman in a room, being left out of decisions because of your gender, even having your ideas shot down because no one in the room supported your being there. Isolation can have a harmful effect on women’s job performance. “Women who are isolated are 13% more likely to report being unsatisfied with their job. Moreover, women who are not satisfied with their job are 22 times more likely to leave.” (Hewlett). This means that women who are isolated in their field, as most women in STEM are (Women in the Labor Force...), have a much larger chance of leaving their jobs than women who aren’t isolated. This is because women who are isolated are generally unhappy with their jobs, and when someone is unhappy with their job, they try to leave.
There was also a study done in 1999, in which two groups of equally strong University of Michigan students were given the same math test, but one group was told that men perform better on math tests, and one was told that, contrary to popular belief, women and men perform the same on math tests. In the first group, the men did an average of 20 points better on the test than the women in the same room. In the second group, the men scored only 2 point higher than the women. (Pollack)
This study shows that positive or negative reinforcement by society can (and does) change women’s behavior and ability. If a change in the beliefs expressed to someone is limited to this study environment, it can’t go on for much longer than a few hours, and it only happens one time. Women who are exposed to these small, individual experiences of prejudice for all of their lives are much more likely to perform worse than their male counterparts, and eventually get discouraged and stop working. On the contrary, if women are exposed to positive (or even neutral) beliefs, their performance steps up to that level. This is the power of positive reinforcement in society, if only we decide to use it.
It is often claimed that women don’t go into STEM fields because they “just don’t like science”. Reasons for this include women having naturally lower IQs than men, or more interest/a genetic predisposition for the humanities, which lead to less interest in STEM from a young age. This is not true, because of these claims’ factual inaccuracy and flawed logic. A study performed in 2009 shows that newborn boys (and newborn monkeys of the same gender) prefer to play with mechanical toys, like mobiles, and that newborn girls (and female monkeys) have an equal interest in mechanical toys, and “girl toys” (like dolls). (Hassett) This shows that men and women have an equal preference for STEM-related fields at birth, before any socialization can alter their preferences, because of the girl’s propensity to play with all types of toys, even mechanical ones, associated with STEM.
The implicit sexixim towards women in STEM fileds is a barrier to women who are entering those fields, hoping to achieve the American Dream. Knowing what I know, I can join the 7.2% of women in mechanical engineering, but I don’t have to perpetuate the negative barriers that others before me have unknowingly perpetuated.
As said by the Project Implicit FAQ, “One solution [to having unwanted biases] is to seek experiences that could undo or reverse the patterns of experience that could have created the unwanted preference... That could mean interacting with people that provide experiences that can counter your preference.” This is saying that one of the ways to counter unwanted biases is to directly contradict them, which suggests that the cause of the bias is not being exposed to the thing you are biased against. This means that, though we are seeing more women in STEM fields, they are still not common enough to have implicit biases level out.
Financial bias against women is another barrier to their access to the American Dream. In 2011, there was a jump in the amount of male nurses in the United States, up to 10%. In tandem with this, male nurses got a jump in pay. “In 2011, the average female nurse earned $51,100, 16 percent less than the $60,700 earned by the average man in the same job.” (Cummings). This means that, in a traditionally female dominated field, men that are doing the same job as women, are getting paid 16% more than women. As above, this means that there is some kind of implicit bias against women in STEM, that allows men to earn more money in the same jobs. This pattern is thought to be caused by men simply being more confident in their work, and their deserved pay, than women.
Many studies have shown that men are more aggressive and confident in their abilities than women. All of the studies vary in content, but they almost all show the same thing - women being less cutthroat, and more generous, than men with their money. There were other studies that showed that women were more likely to be aggressive in negotiation if they were negotiating for someone other than themselves. In other world, they negotiated harder when talking about other people, which shows a reluctance to put their interests above others’. (Cummings) This can be applied to the above case because of differences in men versus women negotiating for salaries. Men are more likely to ask for things like a bonus, raise, or even promotion, than women. This simple psychological difference leads to less women earning these benefits than men.
The above mentioned study performed by Yale, with the resumes labeled either John or Jennifer, shows this financial bias as well. With absolutely no difference in the resumes other than name, John got a salary that was $4,000 higher than that of Jennifer. This smaller salary (and smaller chance of getting the job) will deter Jennifer from going into this career, and potentially from continuing in this subject at all.
The negative reinforcement towards women in STEM has a detrimental effect on their performance in those fields, and, eventually, their willingness to stay in the field. 41% of early career STEM workers are women, but 52% of them drop out before their mid to late 30’s (Hewlett). This means that, although there has been an increase in women in STEM (Women, Minorities...), they are not staying in STEM, because of negative stereotypes.
This is sometimes because of women becoming isolated. This can be being the only woman in a room, being left out of decisions because of your gender, even having your ideas shot down because no one in the room supported your being there. Isolation can have a harmful effect on women’s job performance. “Women who are isolated are 13% more likely to report being unsatisfied with their job. Moreover, women who are not satisfied with their job are 22 times more likely to leave.” (Hewlett). This means that women who are isolated in their field, as most women in STEM are (Women in the Labor Force...), have a much larger chance of leaving their jobs than women who aren’t isolated. This is because women who are isolated are generally unhappy with their jobs, and when someone is unhappy with their job, they try to leave.
There was also a study done in 1999, in which two groups of equally strong University of Michigan students were given the same math test, but one group was told that men perform better on math tests, and one was told that, contrary to popular belief, women and men perform the same on math tests. In the first group, the men did an average of 20 points better on the test than the women in the same room. In the second group, the men scored only 2 point higher than the women. (Pollack)
This study shows that positive or negative reinforcement by society can (and does) change women’s behavior and ability. If a change in the beliefs expressed to someone is limited to this study environment, it can’t go on for much longer than a few hours, and it only happens one time. Women who are exposed to these small, individual experiences of prejudice for all of their lives are much more likely to perform worse than their male counterparts, and eventually get discouraged and stop working. On the contrary, if women are exposed to positive (or even neutral) beliefs, their performance steps up to that level. This is the power of positive reinforcement in society, if only we decide to use it.
It is often claimed that women don’t go into STEM fields because they “just don’t like science”. Reasons for this include women having naturally lower IQs than men, or more interest/a genetic predisposition for the humanities, which lead to less interest in STEM from a young age. This is not true, because of these claims’ factual inaccuracy and flawed logic. A study performed in 2009 shows that newborn boys (and newborn monkeys of the same gender) prefer to play with mechanical toys, like mobiles, and that newborn girls (and female monkeys) have an equal interest in mechanical toys, and “girl toys” (like dolls). (Hassett) This shows that men and women have an equal preference for STEM-related fields at birth, before any socialization can alter their preferences, because of the girl’s propensity to play with all types of toys, even mechanical ones, associated with STEM.
The implicit sexixim towards women in STEM fileds is a barrier to women who are entering those fields, hoping to achieve the American Dream. Knowing what I know, I can join the 7.2% of women in mechanical engineering, but I don’t have to perpetuate the negative barriers that others before me have unknowingly perpetuated.
Bibliography
Cummins, Denise. “Why the STEM gender gap is overblown.” PBS Newshour. PBS. 17 Apr. 2015. Web. 21 Oct. 2015.
Hassett, Janice M., Siebert, Erin R. and Wallen, Kim. “Sex differences in rhesus monkey toy preferences parallel those of children.” PubMed Central. National Center for Biotechnology Information. 1 Sept. 2009. Web. 27 Oct. 2015.
Hewlett, Sylvia Ann, Luce, Carolyn Buck, Servon, Lisa J., Sherbin, Laura, Shiller, Peggy, Sosnovich, Eytan, and Sumberg, Karen. “The Athena Factor: Reversing the Brain Drain in Science, Engineering, and Technology.” Harvard Business Review Research Report. June 2008. Web. 27 Oct. 2015. [http://documents.library.nsf.gov/edocs/HD6060-.A84-2008-PDF-Athena-factor-Reversing-the-brain-drain-in-science,-engineering,-and-technology.pdf]
Marks, Gene. “The Real Reason Most Women Don’t Go Into Tech.” Forbes Tech. Forbes. 16 Mar. 2015. Web. 21 Oct. 2015.
Pollack, Eileen. “Why Are There Still So Few Women In Science?” New York Times. 3 Oct. 2013. Web. 21 Oct. 2015.
Project Implicit. Harvard.edu. Web.27 Oct. 2015. [https://implicit.harvard.edu/implicit/]
“Women in the Labor Force: A Databook - December 2014” BLS Reports. U.S. Bureau of Labor Statistics. Dec. 2014. Web. 1 Nov. 2015.
“Women, Minorities, and Persons with Disabilities in Science and Engineering.” nsf.gov. National Science Foundation. Web. 19 Oct. 2015.
Hassett, Janice M., Siebert, Erin R. and Wallen, Kim. “Sex differences in rhesus monkey toy preferences parallel those of children.” PubMed Central. National Center for Biotechnology Information. 1 Sept. 2009. Web. 27 Oct. 2015.
Hewlett, Sylvia Ann, Luce, Carolyn Buck, Servon, Lisa J., Sherbin, Laura, Shiller, Peggy, Sosnovich, Eytan, and Sumberg, Karen. “The Athena Factor: Reversing the Brain Drain in Science, Engineering, and Technology.” Harvard Business Review Research Report. June 2008. Web. 27 Oct. 2015. [http://documents.library.nsf.gov/edocs/HD6060-.A84-2008-PDF-Athena-factor-Reversing-the-brain-drain-in-science,-engineering,-and-technology.pdf]
Marks, Gene. “The Real Reason Most Women Don’t Go Into Tech.” Forbes Tech. Forbes. 16 Mar. 2015. Web. 21 Oct. 2015.
Pollack, Eileen. “Why Are There Still So Few Women In Science?” New York Times. 3 Oct. 2013. Web. 21 Oct. 2015.
Project Implicit. Harvard.edu. Web.27 Oct. 2015. [https://implicit.harvard.edu/implicit/]
“Women in the Labor Force: A Databook - December 2014” BLS Reports. U.S. Bureau of Labor Statistics. Dec. 2014. Web. 1 Nov. 2015.
“Women, Minorities, and Persons with Disabilities in Science and Engineering.” nsf.gov. National Science Foundation. Web. 19 Oct. 2015.