In a research article published in 2018, “The Gender-Equality Paradox in Science, Technology, Engineering, and Mathematics Education,” psychologists Gijsbert Stoet and David Geary present us a seemingly paradoxical statistics showing that countries with less gender equality actually have more women engaging in STEM subjects (581). It is considered as a paradox because gender-equal countries are usually the ones who offer women more educational opportunities and empowerment to motivate their engagement in STEM fields. According to their interpretation, this phenomenon can be partially explained by the fact that “women in countries with higher gender inequality are simply seeking the clearest possible path to financial freedom” (Khazan). In other words, as STEM occupations are typically related to higher salaries, women in countries with fewer possibilities and higher economic risks will be more likely to engage in STEM careers for financial considerations; on the other hand, women in more developed and gender-equal countries face fewer limitations and may enjoy the “freedom” to choose career paths that are both high-paying and in line with their personal interests and strengths, which are usually non-STEM fields (Stoet and Geary 582). However, one critical problem remains unsolved: why do female students show a “lack of interest” in STEM careers while they generally perform similarly or even better than male students in science literacy (Stoet and Geary 585; Voyer and Voyer 1)? From my perspective, Stoet and Geary have neglected the power of environmental influences (social & cultural) in shaping the interests of boys and girls in their education and developmental processes. By using a broad measure of gender equality called the Global Gender Gap Index (GGGI), which only accesses factors like earnings, governmental representations, and life expectancy, they have inevitably placed too much emphasis on the role of explicit barriers comparing to the implicit ones, which I consider to be the most powerful and crucial factors in shaping women’s interests. In this article, I would like to solve this Gender-Equality Paradox (GEP) by focusing on the power of implicit biases in shaping women’s interests, self-efficacy, and career choices in STEM fields. Combining with the concept of “intersectionality” raised by Kimberle Crenshaw (Crenshaw 141), I would also like to touch on the ethnic variations in these gender stereotypes. Through a variety of evidence, I argue that this paradox actually does not exist. And I believe, rather than showing a paradox, Stoet and Geary have actually helpfully illustrated the complexity of the biases and barriers involved in keeping women away from STEM careers.
In Stoet and Geary’s explanation for why women in more gender-equal nations tend to choose non-STEM careers, they have referenced to the expectancy-value theory, by which they suggest that female students tend to choose non-STEM careers because those careers are better in line with their interests and relative academic strengths in reading comprehension, compared to science or mathematics (585). But, to what extent do these interests and strengths really reflect their “genuine” preferences in an unbiased society? In other words, to what extent have the societies and cultures they live in shaped their interests, strengths, and expectancies for different careers? Are they really enjoying more “freedom” when making career decisions comparing to women in less gender-equal countries? To answer these questions, we need to first distinguish between explicit barriers and implicit biases, both commonly faced by women in STEM careers.
Mary K. Feeney has introduced these two kinds of barriers in her article “Why more women don’t win science Nobels.” Explicit barriers, including but not limited to the gender pay gap, the limitations on women’s educational opportunities, and the difficulties in maintaining work-life balance for women due to their family obligations, are the most obvious and direct obstacles that people are commonly aware of and talking about when mentioning these topics. And as we can notice, the GGGI used in Stoet and Geary’s research is measuring exactly the indicators for these explicit gender inequalities, such as labor force participation, income, literacy rate, and so on (584). However, implicit biases – the unconscious stereotypes, assumptions, and preferences that we all possess – are usually overlooked, despite the fact that they might be one of the most dominant forces in shaping the gender inequality existing nowadays. As I will discuss in detail in the following analysis, the real power of implicit biases is not simply in causing women’s disadvantageous state in employment, award winning, or academic success, but in subconsciously constructing and shaping the interests, preferences, expectancies, and stereotypes of everyone from the beginnings of our lives.
Raised and educated by our parents, we are constantly influenced by their thoughts, behaviors, and choices. Viewing them as authorities in our childhood, their values and beliefs – including but not limited to those beliefs of gender roles, social expectations, and cultural norms – usually have significant impacts on our interests and perspectives. Moreover, they may influence our perception toward ourselves and our expectations for career outcomes. This is a problem worth noticing as people’s career choices are actually more related to their self-perception of their abilities, instead of their real abilities (Bleeker and Jacobs 98). And according to the social cognitive career theory (SCCT), the “outcome expectations” in relation to career opportunities people possess are also essential for their career decisions (Tellhed, Una, et al. 87). Therefore, as female students tend to choose non-STEM careers, researchers hypothesized that their self-beliefs of their STEM abilities and their outcome expectations for STEM careers might be lower than the ones of male students, and this is exactly what they have found. After measuring high school students’ interests, self-efficacy, outcome expectations, and social belongingness expectations in relations to the STEM majors, they found that female students have significantly lower scores in all of these dimensions (Tellhed, Una, et al. 90).
This relationship between parental beliefs and children’s later self-efficacy and academic performances has been supported by various evidence. Using a follow-up design, researchers Bleeker and Jacobs have confirmed the essential role of parents’ beliefs and stereotypes in negatively shaping and constructing girls’ self-perception of their abilities and their ultimate choices in math-science careers (98). On the other hand, focusing on boys, Muntoni and Retelsdorf have recently published a study that demonstrates the same negative effects of parental stereotypes on boys’ reading-related performances (95).
In addition to parental beliefs, early school life has been suggested to be another major contributor to this differentiation process. Teachers’ gender stereotypes have been indicated to be directly biasing their perceptions of boys’ and girls’ mathematical abilities and influencing the academic resources, attention, and feedbacks they give to them accordingly (Tiedemann 49). Furthermore, other studies have demonstrated the contribution of both teachers and peers in perpetuating these gender stereotypes (Beilock et al. 1860; Tiedemann 49; Liben and Bigler 9).
Hence, either consciously or unconsciously, under the influences of parents, teachers, and peers with gender stereotypes and biased perception of their abilities, children are more likely to accommodate to these conventional gender roles and develop their relative interests and strengths in line with these sociocultural expectations. With the existing gender gaps in STEM careers, women’s expectations for the potential barriers and the feeling of emotional isolation are probably even exacerbating the differences in career choices. Combining the results of all these studies with the argument raised in Stoet and Geary’s article, it is not hard to discover that their explanation based on the relative strengths of boys in math-sciences and girls in reading comprehension is relatively superficial, as they have neglected all the impacts of the environmental influences in shaping these strengths and interests.
The significance of implicit biases can also be supported by data from several macroscale studies. For example, after measuring the implicit biases of citizens across 34 countries by using the Implicit Association Test (IAT), scientists have found a positive correlation between “nation-level implicit stereotypes” and “nation-level sex differences in 8th-grade science and mathematics achievement” (Nosek et al. 10593). Furthermore, collecting the IAT data from about 350,000 participants in 66 nations, researchers have concluded that “higher female enrollment in tertiary science education (community college or above) is related to weaker explicit and implicit national gender-science stereotypes” (Miller et al. 631). Therefore, I would like to argue that the paradox actually does not exist after we take into account the influences of all the implicit biases mentioned above. As interpreted by Miller et al., even nations with high overall gender equality scores can have strong gender-science stereotypes, as they can be gender-equal in other aspects but still biased in terms of STEM careers specifically (631).
After discussing all the evidence supporting the sociocultural construction theory of sexual differences, some people may naturally raise this question: is it possible that men and women are simply biologically different in terms of their intrinsic aptitudes for mathematics and sciences? This has been a very popular response to all kinds of gender gaps we are seeing in the current society. Nevertheless, according to a recent review by Elizabeth Spelke, “[r]esearch on the cognitive development in human infants, preschool children, and students at all levels fails to support” this claim that men have greater intrinsic aptitudes for STEM majors (950). To briefly summarize her point, after reviewing a great variety of research on this topic, she has concluded with finding no significant differences between male and female infants in terms of their cognitive abilities that are foundational for studying sciences or mathematics (956). Although she acknowledges the fact that there does exist a certain degree of sexual differences between older boys and girls, the differences are, in her words, “complex and subtle” (956), in a way that it is too subtle to be held responsible for the relatively large gender gaps existing in STEM fields. Therefore, it is more likely that environmental influences and implicit biases are playing a more significant role in forming the gender gaps in STEM fields.
However, we should always bear in mind the complexity of this issue, as the discussion should not be limited to the level of explicit and implicit biases that are preventing women from thriving in the STEM fields. When we are talking about women in STEM, it seems to be a kind of natural tendency for people to view this as a binary conflict (men vs. women). Nevertheless, the reality is always more complicated than a simple binary division, as there will always be interactions and intersections between all these divided social identities. Kimberle Crenshaw is known for her introduction of the concept of “intersectionality,” which she used originally to illustrate the special social identity of “black women” in our society, as they have always been “multiply-burdened” (140) by both gender and racial discriminations against them. According to her, as they are sitting at the intersection of these oppressions, they are facing a unique kind of barrier and inevitably having a unique, multidimensional experience in their lives. What we can take away from her idea is the complexity of the issues related to race, gender, ethnicity, and so on. Relating to our discussion of women in STEM, we also need to consider the unique barriers experienced by only certain groups of people, who are sitting, similarly, at the intersection of two different kinds of social identities. For example, will women with different ethnicities have different participation rates in STEM careers? Although not many studies have been done to specifically answer this question, there are some insightful findings that may provide us with some foundations for our future discussion of related topics.
In Charleston et al.’s study, they have specifically addressed this problem by investigating African American women’s representation in STEM fields in the United States (17). What they have found is that African American women, or women of color in general, are generally facing a greater amount of challenges throughout the educational pipeline (19). Comparing to whites, black girls are less likely to get exposure to computers and technologies in their childhood; girls of color are less likely to succeed in areas of math-sciences at all levels of their education processes; and black women are more likely to develop lower levels of self-efficacy in STEM-related subjects (20). There are a lot more studies which have suggested the unique difficulties faced by colored women in the current US education system, but I think these findings listed above are sufficient in showing that women of color are, as previously mentioned, “multiply-burdened” (Crenshaw 140) comparing to white women in pursuing their STEM careers.
In another study, researchers have compared the participation rate in STEM between African American women and European American women (O’Brien et al. 169). Interestingly, the data they collected have shown that African American college women actually participate in STEM majors at higher rates than European American college women (169). One explanation for this is, again, the different levels of sociocultural construction of gender-STEM implicit stereotypes between different cultures. Using the IAT, these researchers have confirmed this hypothesis, as African Americans (both men and women) have weaker implicit gender-STEM stereotypes than European Americans (177). One way to understand this difference might be that, as STEM is typically associated with financial independence and agency and these concepts are viewed as more masculine in European American culture African American culture (170), African American women will be more comfortable with pursuing STEM careers for becoming more financially independent, referencing to Stoet and Geary’s explanation for the GEP previously. Therefore, indirectly, these findings are, again, indicating the extremely crucial role that social and cultural influences have played in creating the gender gaps in STEM careers. And as we can notice, when we are mentioning the domains of gender and ethnicity, factors including income, social ranking, and culture are simultaneously mixing into the discussion, which has really represented the complexity of these issues.
To conclude, based on multiple scientific evidence, I have responded to the paradox raised by Stoet and Geary by arguing that this paradox will not continue to exist after they take into account the substantial influences of implicit gender-STEM biases existing in different societies and cultures. And what we need to take away from these studies is the fact that men’s and women’s interests, strengths, and eventually career choices, can be either consciously or unconsciously shaped, constructed by various kinds of environmental factors, including but not limited to parental biases, gender role constructions, social expectations, etc. Also, learning Crenshaw’s concept of “intersectionality” (139), we need to acknowledge the complexity and importance of this issue, as “women in STEM” is not simply a binary war between men and women. In order to increase women’s representation in STEM careers, we need to realize and understand how these gender stereotypes are implicitly embedded in every facet of our social system. Overcoming them will be difficult, but it is only through stopping to perpetuate these beliefs that we can eventually allow children to develop their interests and strengths regardless of their gender, creating a society where STEM is no longer considered to be associated with men to a greater extent, where STEM can thrive with both men and women cooperating and utilizing their strengths.
Annotated Bibliography
Beilock, S. L., et al. “Female Teachers’ Math Anxiety Affects Girls’ Math Achievement.” Proceedings of the National Academy of Sciences, vol. 107, no. 5, Feb. 2010, pp. 1860–63.
Bigler, Rebecca. “The Role of Classification Skill in Moderating Environmental Influences on Children’s Gender Stereotyping: A Study of the Functional Use of Gender in the Classroom.” Child Development, vol. 66, no. 4, 1995, pp. 1072–87.
Bleeker, Martha M., and Janis E. Jacobs. “Achievement in Math and Science: Do Mothers’ Beliefs Matter 12 Years Later?” Journal of Educational Psychology, vol. 96, no. 1, 2004, pp. 97–109.
Charleston, LaVar J., et al. “Intersectionality and STEM: The Role of Race and Gender in the Academic Pursuits of African American Women in STEM.” Journal of Progressive Policy & Practice, vol. 2, no. 3, 2014, pp. 7–37.
Crenshaw, Kimberle. “Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory and Antiracist Politics.” The University of Chicago Legal Forum, vol. 140, 1989, pp. 139–167.
Feeney, Mary K. “Why More Women Don't Win Science Nobels.” The Conversation, 21 Dec. 2018, theconversation.com/why-more-women-dont-win-science-nobels-104370.
In Feeney’s article, she makes a clear distinction between explicit and implicit biases and analyzes their different roles in composing the barriers that prevent women from entering STEM careers in the current society. For my essay, this article serves as a very good demonstration for the differences between these two kinds of biases, which is a central critique against the scientists’ interpretation of the Gender-Equality Paradox. I believe the reason for why Gender-Equality Paradox seems to exist is that the researchers have used an index that largely neglects the role of implicit biases in leading to women’s lack of interests in STEM. Furthermore, Feeney has mentioned the emotional isolation, the lack of support, and the lack of belongingness that women in STEM typically feel. This will be in line with my emphasis on the role of implicit social stereotypes in forming women’s lower self-efficacy for STEM careers and lower social belongingness expectations with students in STEM majors.
Jacobs, Janis E. “Influence of Gender Stereotypes on Parent and Child Mathematics Attitudes.” Journal of Educational Psychology, vol. 83, no. 4, 1991, pp. 518–27.
Khazan, Olga. The More Gender Equality, the Fewer Women in STEM - The Atlantic. https://www.theatlantic.com/science/archive/2018/02/the-more-gender-equality-the-fewer-women-in-stem/553592/. Accessed 16 Feb. 2019.
Liben, Lynn, and Rebecca Bigler. “The Developmental Course of Gender Differentiation: Conceptualizing, Measuring, and Evaluating Constructs and Pathways.” Monographs of the Society for Research in Child Development, vol. 67, no. 2, 2002, pp. i-viii+1-183.
Miller, David I., et al. “Women’s Representation in Science Predicts National Gender-Science Stereotypes: Evidence from 66 Nations.” Journal of Educational Psychology, vol. 107, no. 3, 2015, pp. 631–44.
Muntoni, Francesca, and Jan Retelsdorf. “At Their Children’s Expense: How Parents’ Gender Stereotypes Affect Their Children’s Reading Outcomes.” Learning and Instruction, vol. 60, Apr. 2019, pp. 95–103.
Nosek, Brian A., et al. “National Differences in Gender–Science Stereotypes Predict National Sex Differences in Science and Math Achievement.” Proceedings of the National Academy of Sciences, vol. 106, no. 26, pp. 10593–97.
O’Brien, Laurie T., et al. “Ethnic Variation in Gender-STEM Stereotypes and STEM Participation: An Intersectional Approach.” Cultural Diversity and Ethnic Minority Psychology, vol. 21, no. 2, 2015, pp. 169–80.
In this journal article, the researchers utilize an intersectional approach to investigate the ethnic variation in gender-STEM stereotypes and STEM participation. Through their studies, they have demonstrated that African American college women actually participate more in STEM majors than European American college women, although the participation rates of African American and European American men do not generate a significant difference. Also, using the Implicit Association Test (IAT), they have shown that both African American men and women have weaker implicit association between males and STEM subjects, comparing to European Americans. This study serves as a very great example and evidence for my discussion on the intersectionality problem. As women have generally suffered from the explicit and implicit biases keeping them away from STEM careers, there is still variation cross different ethnics, which better illustrates that gender stereotype is a kind of social & cultural construct. Connecting this scientific evidence with Crenshaw’s analysis, I would like to show the readers about the complexity involved in this problem.
Reuben, E., et al. “How Stereotypes Impair Women’s Careers in Science.” Proceedings of the National Academy of Sciences, vol. 111, no. 12, Mar. 2014, pp. 4403–08.
Spelke, Elizabeth S. “Sex Differences in Intrinsic Aptitude for Mathematics and Science?: A Critical Review.” American Psychologist, vol. 60, no. 9, 2005, pp. 950–58.
Stoet, Gijsbert, and David C. Geary. “The Gender-Equality Paradox in Science, Technology, Engineering, and Mathematics Education.” Psychological Science, vol. 29, no. 4, Apr. 2018, pp. 581–93.
This article is the central article upon which my critiques and arguments are based on. In this scientific journal, psychologists Gijsbert Stoet and David Geary present us a seemingly paradoxical statistics showing that countries with less gender equality actually have more women engaging in STEM subjects, which is contrary to our intuition. When interpreting this result, they suggest that women in countries with higher gender-equality have more “freedom” to choose the careers that fit their strengths and interests, which are usually not STEM ones. However, their explanation for why women have a lack of interest in STEM fields is untenable, as they simply attribute this to men’s and women’s “relative strengths.” Using this article as the introduction, I would like to present my counter-argument against their interpretation and suggest the crucial roles implicit biases and environmental influences have played in subtly forming females’ interests. I believe, rather than showing a paradox, Stoet and Geary have actually helpfully illustrated the complexity of the biases and barriers involved in keeping women away from STEM careers.
Tellhed, Una, et al. “Will I Fit in and Do Well? The Importance of Social Belongingness and Self-Efficacy for Explaining Gender Differences in Interest in STEM and HEED Majors.” Sex Roles, vol. 77, no. 1–2, July 2017, pp. 86–96.
In this research article, the authors analyze the importance of self-efficacy, outcome expectations and social belongingness in shaping women’s career decisions away from STEM fields. Based on the social cognitive career theory (SCCT), which states that the career interests will be affected by both how one can do (self-efficacy) and what one will get (outcome expectations), they have hypothesized that women’s underrepresentation in STEM careers is, overall, the result of their low self-efficacy in succeeding in STEM, their low outcome expectation for STEM careers, and their low social belongingness expectations for entering STEM fields. I think this research has provided a very strong evidence for my argument emphasizing the role of implicit bias (gender-STEM stereotypes) in shaping women’s interests in the society. Following this logic, the choices of women in more gender-equal countries may not reflect their “free” choice of their real interests, but merely reflecting the social stereotypes keeping them away from STEM. This provides a solid foundation for me to crack the Gender-Equality Paradox and illustrate the importance of reducing the implicit biases against women in STEM.
Tiedemann, Joachim. “Teachers’ Gender Stereotypes as Determinants of Teacher Perceptions in Elementary School Mathematics.” Educational Studies in Mathematics, vol. 50, no. 1, 2002, pp. 49–62.
Voyer, Daniel, and Susan D. Voyer. “Gender Differences in Scholastic Achievement: A Meta-Analysis.” Psychological Bulletin, vol. 140, no. 4, 2014, pp. 1174–204.
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