Backlash: Using Flawed Science to Justify Sexism

And what Lady Gaga and Mark Zuckerberg have in common

Women protesting Harvard President Larry Summers in 2006. Summers made derogatory comments about women’s aptitude for STEM.

One of the most frustrating phenomena in the 20^th and 21^st centuries is “backlash” against feminist gains. This includes scientific “studies” that extrapolate minor cognitive differences between the sexes (though often derived from limited or poorly designed studies) to explain the major gaps we see in equity in the STEM work force. Even more disturbing, is that women scientists are sometimes touting and supporting these flawed studies. To these anti-feminists, discussing sexism is merely “Crying Wolf”. They tout the easy narrative that science is completely “objective” and “merit-based” and that women do not succeed because they either don’t want to pursue it, or they are not smart enough.

When there are feminist gains, a conservative “backlash” typically emerges. As Faludi describes in her amazing book Backlash: The Undeclared War Against American Women, anti-feminist attitudes tend to gain public attention in decades following substantial progress for women. For example, the 1950s was inhospitable to women scientists after women’s contributions to the war effort in the 1940s. The 1980s was no exception, after the feminist gains of the 1970s. For example, Faludi points out that the 1987 American Educational Research Associations annual conference had twenty-five sessions on sex differences in an attempt to link biological differences to masculine/feminine dichotomies. These studies often emphasized the differences between men and women as “biologically predetermined and intractable” (Faludi 1991) (pp. 335-336). Faludi points out that some of these studies were not drawn from representative demographic pools or used control groups. Furthermore, “human capital” models in the 1980s attributed differential male/female earnings to occupational status, shorter hours, less investment, interrupted work histories and individual choice. These studies failed to explain differences between men and women with similar career histories, the legacy of sex segregation, cultural conditioning about the female role, increased domestic workload for women, unconscious gender bias, lack of institutional support, and a counterpart examination of males with families. These “studies” were often used to justify workplace discrimination.

Gifted and Talented Programs

One of the most influential studies about sex-differences in intelligence was conducted by Camilla P. Benbow** and Julian Stanley in 1980. This infamous study collected data from a program called the “Study for Mathematically Precocious Youth” (SMPY) which re-enforced the “meritocracy myth”, i.e., that individuals’ success in STEM is entirely based on merit. The SMPY study began in 1971 at Johns Hopkins University and was a planned fifty-year longitudinal study to identify and develop strategies for nurturing exceptionally talented youth in STEM (Study of Mathematically Precocious Youth 2021). The SMPY initially examined a self-selected group of “gifted” 7^th and 8^th grade students in the top 3% in quantitative or verbal reasoning ability as measured by the SAT verbal (SAT-V) and math sections (SAT-M) tests, which are above age-level assessments. They found a significant gap between male and female SAT-M scores, with that gap widening over high school years. No other metrics for sex differences were tested and no information about the subjects’ demographics or academic background were given. But they argue that “Putting one’s faith in boy-versus-girl socialization processes as the only permissible explanation of the sex difference in mathematics is premature.” (Benbow and Stanley 1980) (p 1264). In a follow-up article, Benbow-Stanley state that “Mathematical reasoning ability is a scarce and probably dwindling national resource […] All the professions and vocations that need great quantitative ability must compete for this limited pool of talent.” (Stanley and Benbow 1982) (p. 4). They then provide recommendations for nurturing gifted youth rather than ways to expand this “pool”. More disturbingly, SMPY implies that early cognitive ability is the most important factor for academic achievement. That other skills like creativity, empathy, communication, emotional intelligence, are useless.

Aaron M. Pallas and Karl L. Alexander directly challenged the Benbow-Stanley study by examining the relationship between high school SAT-M scores and coursework. Pallas and Alexander selected a broad cohort of students across the U.S. and considered the effect of parental education level, race, and 9^th grade quantitative test performance on SAT-M scores. They found that quantitative differences between men and women were about the same in 9^th grade and that the gender gap increased by graduation. When controlling for coursework, the SAT-M scores between men and women shrank considerably. They show that women who took advanced mathematics and quantitative science courses in high school were able to improve their SAT-M score, concluding that sex differences in SAT-M scores are probably due to sex-differences in socialization (Pallas and Alexander 1983).

Gifted and Talented first graders at Decatur Elementary School, meeting the then mayor of Seattle in 1978 (Greg Gilbert / The Seattle Times). The students in this photo are predominately white males. By 2019, only just 1.7% of students in the same program were black.

However, the 1980 Benbow-Stanley study was seemingly influential with over 1950 citations reported by Google Scholar as of 2025 (versus 428 for Pallas and Alexander’s paper). Benbow co-authored a follow-up study thirty-five years later which included more information about SMPY participants (i.e., career paths, educational attainment, course interests) and their outcomes. The follow-up study examined the original cohort’s career choices and strongly attributed “preference” as to why fewer women, particularly women of color in the original cohort, pursued STEM careers (Lubinski and Benbow 2006). The SMPY program has spawned over 400 papers and several books on identifying and developing STEM aptitude in youths. The SMPY has been covered in prestigious scientific journals such as Nature and in a documentary and website for the parents of “gifted” children. The program has also spawned several influential alumni including Facebook co-founder Mark Zuckerberg, Google’s co-founder Sergey Brin, and musician Stefani Germanotta (Lady Gaga). Johnathan Wai, a psychologist at the Duke University Talent Identification Program ominously states in a Nature article that “Whether we like it or not, these people really do control our society” (Clynes 2016) (p. 153).

Calling out Sexism is not “Crying Wolf”

Psychologists Stephen Ceci and Wendy Williams** have developed a more palatable version of gender essentials in the 21^st century. Yet, they have also devoted considerable efforts to downplaying or qualifying claims of sexism in STEM aptitude testing and academic hiring. While Ceci and Williams caution from completely discounting sex differences, they do acknowledge that other factors influence sex differences in STEM aptitude (Ceci et al. 2014). Ceci and Williams argue that the sex differences in the top 5% of mathematical ability (the “right tail”) do not translate into the large sex-differences in senior academic jobs in mathematics, computer science, physics, and engineering. Additionally, the so-called male advantage in the right-tail mathematics distribution, typically measured using standardized tests like the SAT-M, is inconsistent among different geographical regions and ethnicities. They note that even very subtle priming about sex-based mathematical ability can lower a female’s math performance. But their article repeatedly emphasizes individual choice, rather than institutional barriers, as the reason for women not excelling in STEM academic careers. And they do not definitively rule out male advantage in STEM aptitude and state that “environmental influences” could not explain the extreme right tail advantage for men.

But their arguments get worse. Ceci and Williams’ notorious 2015 study published in the Psychological Science in the Public Interest (a journal for which Ceci was a co-founding editor (Ceci and Bjorik 2000) stated that there was a 2:1 hiring preference for women applicants at American colleges/universities in most math and science intensive fields based on hypothetical scenarios (W. M. Williams and Ceci 2015). Their study reveals that a higher percentage of female applicants than male applicants were offered academic interviews and job offers in hypothetical scenarios. Their ableist conclusion places the blame squarely on the women as just not being interested in pursuing STEM:

“We hope the discovery of an overall 2:1 preference for hiring women over otherwise identical men will help counter self-handicapping and opting-out by talented women at the point of entry to the STEM professoriate, and suggest that female underrepresentation can be addressed in part by increasing the number of women applying for tenure-track positions”

Ceci and Williams published an op-ed based in the New York Times called “Academia Isn’t Sexist” which received considerable media attention (W. M. Williams and Ceci 2014) and perpetuated the meritocracy myth of academic hiring. Their methods were criticized for making broad, logically faulty claims and dismissing evidence of sexism they encountered in their own research (Cruz 2015; Leuschner and Pinto 2021; Schuman 2014). Their research ran against most published research on sexism in STEM at that time and also did not consider the effect of race or class on women’s academic progress. They also fail to consider the quote “superstar” effect, i.e., certain women are promoted quickly through the ranks due to connection to influential mentors and above-and-beyond credentials which are unobtainable for most. Other candidates fall away because they cannot get a foothold in the academic career ladder after a PhD (Rossiter 2012, J. C. Williams and Smith 2015). Therefore, the reason for these greater offers may be because of their extreme credentials.

Ceci and Williams qualified some of their claims in a 2023 follow-up study by noting that female doctorates were less likely to apply to tenure-track jobs and acknowledged some evidence of bias in teaching, promotion, and salary of tenure-track women and the weakness of using hypothetical hiring scenarios for examining hiring equity (Ceci, Kahn, and Williams 2023). However, their research only included studies from “pre-2000” (ignoring cohorts of women faculty that received Ph.Ds. in the 1990s and 1980s who were still in the workforce) and ignored race and social class “because very limited data exist” (p. 17). They justified their study by condescendingly stating that

as in the story of the boy who cried wolf, if people claim unfair bias every time there is out-come asymmetry—and if the well-intentioned efforts of many academic leaders and administrators, teachers, policymakers, and funders over the past 20 years to equalize treatment of scientists irrespective of gender appear not to have improved the situation—many people may give up in discouragement (which would be particularly regrettable if their efforts actually worked) (Ceci, Kahn, and Williams 2023) (p. 19).

Comparing women’s experiences of “sexism” to “crying wolf” dismissed decades of evidence of sexism in STEM. The media once again ran with the article, with an Inside Higher Ed piece gleefully proclaiming “Research Finds No Gender Bias in Academic Science”. A letter to the editor later criticized the “misleading” title in this article. Ultimately, these types of studies treat women as a monolith, and attempt to “gaslight” women about their experiences. Furthermore, they can continue to perpetuate gender stereotypes (Riegle-Crumb et al. 2012) and negatively affect students’ academic motivation (Clynes 2016).

These studies are also used by administrators to justify discriminatory hiring practices.

For example, in a January 2005 meeting, Lawrence Summers, then President of Harvard University, suggested the declining percentage of female tenure appointments under his administration was due to a "different availability of aptitude at the high end" between the sexes (Hirsh and National Journal 2013). Feminist scientists and activist Dr. Nancy Hopkins, who happened to be in the meeting, leaked his comments to the press, resulting in tremendous media attention. Though Summers clarified, apologized, and recanted his statements, he was already unpopular for his belligerent management style (Bradley 2005). Summers resigned a year after the comments, and historian Drew Faust became Harvard’s first female president. Meanwhile, Summers was appointed to a top economics post by President Obama (Kelderman 2008). Summers had some defenders. Psychologist Doreen Kimura who authored a 1992 Scientific American “Sex Differences in the Brain” stated that “I think Summers has more courage than any university administrator I have encountered.” (Fogg 2005). In the article, Kimura attributed inequalities in STEM fields due to individual preference related to these sex differences (Kimura 1992). Notably, Kimura’s article gives little information on the selection of subjects that she tested to draw these conclusions.

2010 MIT’s System Design and Management (SDM) program There are only 4 women in a cohort of over 50 members.

More disturbingly, a February 2005 op-ed from The Atlantic entitled “Why Feminist Careerists Neutered Larry Summers” angrily asserts that the feminists who “stomped” Larry Summers were “pursuing a careerist, self-serving agenda” (Taylor Jr 2005). Such an article, comparing feminist criticism to castration, indicates a backlash rooted in angry insecurity. Kimura’s response demonstrates the incentive a women scientist may have to eschew feminism; it may lead to short-term approval, though they likely benefitted from feminist gains. At best, they may avoid negative attacks but are doing little to help those interested in the field.

Also, Summers was president of Harvard when Mark Zuckerberg launched Facebook and did little to intervene when the Winklevoss twins alleged intellectual property theft. Larry Summers’s behavior was forever immortalized by Douglas Urbanski in The Social Network.

Conclusion

Overall, it is tempting to fall into the myth that the scientific method somehow translates to a similar objectivity and merit-based promotion in the scientific workforce. Considering social or structural barriers is perceived by many in the scientific world as “weak”, or “lowering standards” or “unfair” to people who had to go through them. It is this mindset that keeps the ranks closed.

**And yes, we will further explore why women are authoring scientific papers justifying sex discrimination.

References

Bradley, Richard. 2005. “War.” In Harvard Rules, New York City: HarperCollins, 243–80.

Ceci, Stephen J., Shulamit Kahn, and Wendy M. Williams. 2023. “Exploring Gender Bias in Six Key Domains of Academic Science: An Adversarial Collaboration.” Psychological Science in the Public Interest 24(1): 17, 19.

Faludi, Susan. 1991. Backlash: The Undeclared War Against American Women. 2020 ed. New York: Broadway Books.

Levin, Margarita. 1988. “Caring New World: Feminism and Science.” The American Scholar 57(1): 100,101,106.

Lubinski, David, and Camilla Persson Benbow. 2006. “Special Section : Doing Psychological Science Study of Mathematically Precocious Youth After 35 Years.” Perspectives on Psychological Science 1(4): 316–45.

Pallas, Aaron M, and Karl L Alexander. 1983. “Sex Differences in Quantitative SAT Performance: New Evidence on the Differential Coursework Hypothesis.” American Educational Research Journal 20(2): 165–82.

Riegle-Crumb, Catherine, Barbara King, Eric Grodsky, and Chandra Muller. 2012. “The More Things Change, the More They Stay the Same? Prior Achievement Fails to Explain Gender Inequality in Entry Into STEM College Majors Over Time.” American Educational Research Journal 49(6): 1048–1073.

Rossiter, Margaret W. 2012. Women Scientists in America: Forging a New World since 1972. Baltimore: The Johns Hopkins University Press.

Stanley, Julian C., and Camilla Persson Benbow. 1982. “Educating Mathematically Precocious Youths: Twelve Policy Recommendations.” Educational Researcher 11(5): 4.

———. 2015. “National Hiring Experiments Reveal 2:1 Faculty Preference for Women on STEM Tenure Track.” PNAS 112(17): 5365.