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Note: This blog post is one in a series of briefs examining the problems and solutions of the STEM gender gap. These briefs use data quantified from scholarship applications of NMOST's Advancing Young Women in STEM Scholarship in order to connect the youth voice of New Mexico to a national problem.  Eventually, this post will be available as a polished brief for educational dissemination. This post was created by Ethan Greene. 

 

 

 

What is the Gender Gap in STEM? 

Women and people of color are consistently underrepresented in computer science and engineering, two of the largest and highest paying sectors in the Science, Technology, Engineering and Mathematics (STEM) fields. This lack of diversity hurts the industry by suppressing innovation, and hiring bias creates an untapped pool of talented workers. In addition, there is a significant gender pay gap across the highest paying STEM jobs. In order to understand how to address inequality in the STEM fields, we must first understand what is meant by the STEM gender gap.

If one takes a broad view of what a STEM field is then, on the surface level, there isn’t a STEM gender gap at all. When a Pew Research Center study by Cary Funk and Kim Parker (2018) included healthcare workers as STEM workers they found that women made up 50% of all US workers in STEM fields.  

A clearer image of the disparities emerge when we look within the different STEM fields. In health-related jobs, women make up 75% percent of the workforce, which accounts for 9.0 million of the 17.3 million STEM jobs in the U.S. While women may be overrepresented in the health related workforce they are actually underrepresented in the highest paying jobs in the health-care industry. Women working as healthcare practitioners and in technical occupations make $1,153 a week compared to $1,506 a week made by men (Labor Force Statistics, 2021). The disparity is both a pay gap and a job category gap. In other words, a female surgeon makes less than a male surgeon on average and women are more heavily represented among nurses than surgeons. Of the 4.4 million computer science workers, women make up only 25% of the workforce, and of the 2.7 million engineers and architects, women make up only 14% of the workforce. While women make up 47% of life sciences workers, 46% of Math workers, and 39% of physical science workers, these occupations only consist of 1.1 million jobs (Funk and Parker, 2018). 

In their report, “Solving the Equation: Variables for Women’s Success In Engineering and Computing,” authors Christianne Corbett and Catherine Hill (2015) argue that having a less diverse workforce in engineering and computer science leads to less innovation in these fields (p. 10). Less talented men are often picked over more talented women because of biases and the engineering and computer science industries miss out on a large pool of highly skilled workers, making them less competitive. There are also numerous studies showing evidence that a more diverse group of people leads to greater “innovation and productivity” (p. 12). 

The industry suffers when there is a lack of diversity in the field, but women also miss out on the economic advantages of working in higher paying STEM jobs. According to the US Bureau of Labor Statistics (2021), architects and engineers make a median $1,575 a week and computer scientists make a median $1,633 a week, while biological scientists and physical scientists make only $1,141 and $1,438 a week respectively (Labor Force Statistics). What’s more, the computer science workforce has increased by 338% since 1990, while women’s representation has decreased from 32% in 1990 to 25% in 2016 (Funk and Parker, 2018). The data also shows how, even when women do work in the fields of computer science and engineering a stark gender pay gap remains. For example, the median weekly salaries of software developers is $1,920, but men make a median weekly earning of $2,004 and women make $1,728 (Labor Force Statistics, 2021).

 

In addition to a gender gap it is also true that Black, Hispanic, and Native American workers are underrepresented in most STEM fields. While Black workers represent 11% of the U.S. workforce, they make up only 7% of the computer science workforce and 5% of the engineering workforce. Hispanic workers account for 16% of the workforce, but only 7% of the computer science workforce and 8% of the engineering workforce (Funk and Parker, 2018). Native Americans represent 1 percent of the labor force (Labor force characteristics, 2019), but make up less than half a percentage point of the engineering workforce (Change, 2015), and receive less than half a percentage point of computer science bachelors degrees (Computer Science, 2020). Thus, in addition to women being underrepresented in these fields, women of color face both gender and racial barriers. 

The gender gap in STEM means that women, and especially women of color, are underrepresented in the highest paying positions in these fields. It also means that women working in STEM get payed less than men who work the same job. 


References

Chang, J. (2015). Bridging the racial gap in STEM education. NACME. https://www.nacme.org/nacme-career-center/89-news/articles/170-bridging-the-racial-gap-in-stem-education

Computer Science. (2020). Data USA. https://datausa.io/profile/cip/computer-science-110701

Corbett, C., & Hill, C. (2015). Solving the Equation: The Variables for Women’s Success in Engineering & Computing (pp. 1–141). AAUW.

Funk, C., & Parker, K. (2018, January 9). Women and Men in STEM Often at Odds Over Workplace Equity: 1. Diversity in the STEM Workforce Varies Widely Across Jobs. Pew Reserach Center. https://www.pewresearch.org/social-trends/2018/01/09/diversity-in-the-stem-workforce-varies-widely-across-jobs/

Labor force characteristics by race and ethnicity, 2018: BLS Reports: U.S. Bureau of Labor Statistics. (2019). U.S. Bureau of Labor Statistics. https://www.bls.gov/opub/reports/race-and-ethnicity/2018/home.htm

Labor Force Statistics from the Current Population Survey (No. 39; Household Data: Median Weekly Earnings of Full-Time Wage and Salary Workers by Detailed Occupation and Sex). (2021). U.S. Bureau of Labor Statistics. https://www.bls.gov/cps/cpsaat39.htm

 

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