Overemphasizing Sex Differences as a Problem

Overemphasizing sex differences can lead to error.  This may happen:
 

1. When sex differences are asserted without sufficient evidence or documentation.

Statistically sound, peer-reviewed data are needed to support scientific claims of sex differences. Researchers may assert or suggest sex differences even in the absence of sufficient data, or sufficient data analysis. The bias against reporting negative or null results means that findings of sex difference are reported more often than findings of no sex difference (IOM, 2012).

• ●Example (Disease Genetics): Many diseases show differences in prevalence according to both sex and other genetic traits. For example, systemic lupus is an autoimmune disease with higher prevalence in women than men (i.e., sex is a risk factor) and higher prevalence in people with specific forms of human leukocyte antigen genes (i.e., genetic makeup is a risk factor) (Martens et al., 2009). As a result, researchers are interested in determining how sex and other genetic traits interact in determining risk—if a particular genetic trait is a risk factor only for women or only for men, this information would be useful in disease screening. A review of peer-reviewed papers reporting "sex-related differences in genetic associations" found that "most claims were insufficiently documented or spurious." Problems included lack of control groups, comparing dissimilar cohorts of women and men (such as cohorts of different ages), and many others (Patsopoulos et al., 2007).

2. When differences between women and men are improperly attributed to sex.

Researchers may assume that differences between women and men are due to sex when in fact other factors—such as gender roles or socioeconomic status—come into play. Overemphasizing sex differences can lead, and historically has led, to stereotyping women and men. The U.S. National Institute of Medicine has noted that "Historically, studies on race, ethnicity, age, nationality, religion, and sex have sometimes led to discriminatory practices." The committee recommended that these practices be understood so that they are not repeated (Pardue et al., 2001).

• ●Example (Software Design): Video game firms have produced "pink" and "blue" games according to beliefs about fundamental differences in women's and men's interests and skills—interests that are sometimes seen as innate. Blue games typically focus on combat, and pink games focus on fashion. Recent research shows that gender norms about the appropriateness of gaming influence women's and men's gaming patterns. These norms are changing, and some of the most popular modern games have similar proportions of women and men players. Designing for a broad audience is often a more successful strategy than creating games for players of one sex (Faulkner et al., 2007) (see Case Study: Video Games).

3. When sex is emphasized to the exclusion of other important variables.

• ●Example (Bioengineering and Medicine): Is a female-specific knee prosthesis necessary? Overall, there is a lack of evidence that female-specific prostheses improve women's total knee arthroplasty outcomes. Sex influences both height and knee morphology, but evidence suggests that the choice of a knee prosthesis is better based on the continuous variable of height than the binary variable of sex. Overemphasizing sex differences in knee prostheses may harm both men and women—the "female" knee may be a good physiological fit for some men and a poor fit for some women (see Case Study: De-Gendering the Knee).