Just Like a Circus: The Public Consumption of Sex Differences

  • Donna L. Maney
Part of the Current Topics in Behavioral Neurosciences book series (CTBN, volume 19)


The study of sex differences is a rich, productive area of neuroscience, yielding findings that inform our understanding of basic biology and hold promise for clinical applications. There is a tremendous, problematic mismatch, however, between the actual implications of this research and what has generally been communicated to the public. The message communicated by the media, popular press, and in some cases researchers is often inaccurate with respect to what can and cannot be concluded from the data. This misrepresentation of findings has led to a crisis in public education and threatens to do the same in public health. Here, I suggest a number of ways that neuroscientists might address this growing problem. First, we should acknowledge that the term ‘sex difference’ is usually interpreted by the media and the public as evidence for dichotomous categories that do not actually exist. Because data rarely sort so cleanly into sex-specific categories, clearer presentation of the nature and size of sex differences is warranted. The term ‘sex effect’ may be preferable to ‘sex difference’ when the effect is not large. Second, factors that covary with sex, particularly experience, should be considered as causes of sex differences before the idea of “hardwiring” is invoked. Finally, we should be more vigilant about how our own findings are conveyed to policymakers and the public and speak out when they are misrepresented.


Brain-based learning Neuromyth Neurosexism Pseudoscience Reverse inference Sex differences Single-sex education 

1 Brain-Based Learning and the Power of the Crockus

In December 2006, the elementary school where my mother was teaching held a staff development workshop called Boys and How They Learn. In the material distributed for the workshop, the principal noted, ‘We decided to concentrate on boys and how they learn because our boys are not performing as well as our girls.’ Several pages of pseudoscientific claims were supplied from the popular press, for example, from Gurian and Stevens (2005): Boys need more room on a table than girls do, boys see better in bright light, and boys tend to hear less well than girls. The majority of the material advocated distinct educational methods for boys and girls, implemented in separate classrooms, citing profound dichotomies in learning styles, neuroanatomy, and physiology. The school had already begun offering an all-girls kindergarten class, and one purpose of the workshop was to explore whether single-sex education should be expanded to other grades.

My mother’s school was not alone in this endeavor. Earlier that year, the US Department of Education announced a reinterpretation of Title IX, which had previously prohibited segregation of boys and girls in public schools. Federally funded, single-sex classrooms would now be allowed, if necessary to achieve identified, specific educational goals (US Department of Education 2006). Almost immediately, several hundred public schools in the US implemented single-sex classrooms under the pretense that boys and girls are “hardwired” to process information differently and thus require separate learning environments (American Civil Liberties Union 2012). This surge in ‘brain-based’ single-sex education programs was fueled in large part by misinformation and pseudoscience from the popular press and media, repackaged under the guise of professional development for teachers. Materials for teacher workshops described profound sex differences for which there is no scientific basis—for example, that boys’ brains develop from back to front, whereas girls’ develop from front to back; that boys use the ‘primitive’ parts of their brains, whereas girls used the ‘advanced’ parts; and that boys cannot remember anything that is told to them (Table 1). In a particularly infamous example, an educational consultant addressing a large urban school district asserted that the “detailed area of the brain”, a nonexistent structure he called the ‘crockus’, is four times larger in girls (Hodgins n.d., as cited in Liberman 2007)—allowing girls to see more details in each experience. Proponents of brain-based single-sex programs typically claimed that effective coeducational classrooms are impossible, not only because of profound sex differences in brain development and information processing, but also because optimal temperature, sound, and light levels differ dramatically between boys and girls (American Civil Liberties Union 2012). References to scholarly research supporting these claims were rarely offered.
Table 1

Examples of claims commonly presented to elementary school staff in professional development workshops in the USA



Boys’ brains develop from the back of the head to the front, from the ‘doing’ part of the brain to the ‘thinking’ part, whereas girls’ brains develop from the front of the brain to the rear. This means that boys are able to act before they are able to think

Hodgins (2011)

The resting female brain is more active than the male brain, which often goes into a pause state after tasks. To break the pause, boys must use loud voices, run, or jump

Gurian and Stevens (2004), Hodgins (2011), McBride (2008)

Boys don’t remember what you have told them. Each time an incident happens, it’s as if it has never happened before

Hodgins (2007)

Girls’ brains experience 15 % more blood flow than boys’

Gurian and Stevens (2004), McBride (2008)

Girls tend to use the more advanced parts of their brains, whereas boys use the more primitive parts

McBride (2008)

Girls develop language 6 years earlier than do boys

McBride (2008)

The corpus callosum is 20 % larger in girls than boys. This means that boys have trouble talking about their emotions, since emotion and language are located on opposite sides of the brain

Gurian and Stevens (2004), Hodgins (2007, 2011), McBride (2008)

Boys have half as much neural tissue devoted to verbal-emotive functioning

McBride (2008)

Boys have less oxytocin than girls, which makes them uncomfortable with eye contact. They should be seated side-by-side, to avoid such

Gurian and Stevens (2004), McBride (2008)

Boys have less serotonin than girls, which makes them more fidgety and impulsive

Gurian and Stevens (2004), Hodgins (2007)

Girls can hear better than boys

Chadwell (2010), McBride (2008)

Girls can see better in dim light

Chadwell (2010)

Boys’ visual systems are wired to detect moving objects

Gurian and Stevens (2004), Chadwell (2010)

Girls’ visual systems are wired to respond best to the colors red or pink

Chadwell (2010)

Boys are most comfortable at a temperature of 69 °F whereas girls work best at 75 °F

Sax (2006)

Girls are able to see the details of a situation because the detailed area of the brain, called the crockus, is four times larger in girls than boys

Hodgins (2007)

The effect of such presentations on educational policy in the US was stunning. In 2012, the American Civil Liberties Union reported that of the single-sex education programs they investigated, nearly all cited pseudoscientific material from the popular press, not peer-reviewed literature (see Table 1), as justification for separating the sexes (American Civil Liberties Union 2012). In order to accommodate what they believed were scientifically proven sex differences , schools used different colors to decorate the classrooms, set thermostats at different temperatures, and arranged seating with girls face to face to promote social interactions and boys side by side to avoid eye contact. In an all-boys classroom in Idaho, teachers used microphones to adjust their voices to a level they were told is best for boys (Hollingsworth and Bonner 2012). Teachers at a school in West Virginia were told that girls need low light levels; the lighting was so low in a girls’ classroom that a visually impaired student could not see well enough to function (Khadaroo 2012). In some cases, parents sued to end mandatory single-sex instruction (e.g., Doe 2012) but were not always successful (e.g., A.N.A. 2011).

The use of pseudoscience to justify these new practices triggered a strong response from scientists and gender studies scholars. Several critical books and articles were published between 2009 and 2011 (Eliot 2009, 2011; Fine 2008, 2010; Halpern et al. 2011; Jordan-Young 2010; Rivers and Barnett 2011). Work remains to be done, however, as proponents of single-sex classrooms continue to perpetuate myths and stereotypes, and school administrators continue to listen. Those myths and assertions (see Table 1) have been thoroughly debunked elsewhere; my goal in this article is instead to consider the ways in which we have failed to adequately communicate the nature of sex differences to the public and to suggest ways in which we might help teachers and parents better evaluate them. First, we need to recognize that after our findings are published in scholarly journals, they are filtered and sensationalized by a series of non-expert translators, such as the popular media and teacher educators (Hardiman et al. 2012). Sex differences are packaged and sold to schools as evidence that boys and girls fall into dichotomous categories with non-overlapping distributions. Certainly, small differences do inform our understanding of the factors that contribute to learning and their value should not be discounted—yet, as scientists, we are obligated to respond to misrepresentation of our findings to promote a social agenda, and to establish a more effective dialog with policymakers. In addition, we need to address our own propensity to draw illogical inferences about the meaning of sex differences, particularly from neuroimaging data. Ultimately, because sex differences are so easily misunderstood and misinformation potentially harmful, we need to hold others and ourselves to a high standard when reporting them.

2 What is a Sex Difference?

Everyone understands intuitively that the sexes are different, because our sex organs are obviously different. With few exceptions, a child is categorized as one sex or the other from the moment he or she is born. Because of the widely recognized differences in genitalia, it is easy to believe that other differences between the sexes could be equally large. MRI technology affords unprecedented views inside areas that historically have been obscured from view. If educational consultants argue that newly discovered sex differences in the brain and behavior are large and meaningful enough to warrant different classrooms for girls and boys, teachers often listen.

Actual sex differences in behavior and the brain, particularly in children, should certainly not compel educators to implement dramatic new policies. For example, consider sex differences in impulsivity or activity, the effect size (Cohen’s d) of which is typically about 0.2 (Hyde 2014). A hypothetical effect of this magnitude is plotted in Fig. 1a. Such sex differences, which might instead be called ‘sex effects’ to avoid the term ‘difference’ altogether, can be statistically significant, but only when sample sizes far exceed a typical elementary school class. In other words, such an effect would not be detectable within a class, a grade, or possibly even an entire school—an effect of the size depicted in Fig. 1a would require approximately 400 children to detect. Because distributions are almost never plotted in research reports, the degree of overlap between the sexes is usually lost when the finding is communicated to teachers. As a result, effects like the one in Fig. 1a are presented and interpreted as evidence that boys and girls cannot learn optimally in the same classroom. Yet, for every 50 boys above the mean, there are 46 girls also above it. Similarly, for every 50 girls below the mean, there are 46 boys below it. Thus, if it is true that children above and below the mean need different classroom environments, separating them according to their sex would do very little to address that need. Almost as many children would end up in the ‘wrong’ classroom as in the ‘right’ one. Such a strategy, which would benefit only the children at the extremes of the distribution, essentially constitutes teaching to the tails; it does not consider the needs of the majority of the children, for whom sex does not predict ability or behavior.
Fig. 1

Sex ‘differences’ in behavior and the brain typically show large overlap. (a) Normal distributions showing a typical sex difference in a behavior or personality trait, such as impulsivity or activity (reviewed by Hyde 2014). The number of boys or girls with scores on a hypothetical scale of 0–100 is plotted. For every 50 boys above the mean, there are also 46 girls above the mean; the sexes overlap by more than 80 %. This difference (effect size d = 0.2) is actually much larger than those typically reported for traits such as verbal or mathematic ability. Even for traits with larger sex differences , for example, interest in things vs. people (effect size = 0.93), the overlap is close to 50 %. (b) The size of the hippocampus and amygdala varies according to sex in children ages 8–15 (data from Neufang et al. 2009). If this sample of 30 children were split according to the median size of either structure (dashed lines), a large proportion of the children would be in the ‘wrong’ group for their sex. The ‘small hippocampus’ group would consist of 9 boys and 6 girls; the ‘small amygdala’ group would consist of 7 boys and 8 girls. Notably, each of the ‘girl-like’ groups would contain one or two boys with testosterone levels typical of mid-puberty

A more concrete example of overlapping distributions appears in Fig. 1b, which depicts a known sex effect on the sizes of two brain regions. According to Neufang et al. (2009), the hippocampus is larger in girls and the amygdala larger in boys. Educational consultants have used such findings to argue for large sex differences in information processing and emotive functioning (Gurian and Stevens 2004, 2005; Sax 2005). A close inspection of the actual data reveals large overlap; if we were to use the median hippocampus or amygdala size to divide the students into groups, the number of boys and girls would be approximately equal in each. The authors of the study found that the surge of testosterone in pubescent boys may explain the larger amygdala; importantly, our class with ‘girl-like’ amyg-dalae would even contain two older boys that had begun puberty. Thus, although these brain structures are different in that an effect can be detected, sex is a rather poor predictor of their size. Certainly, if a small hippocampus and large amygdala warrant a certain educational approach, dividing students by sex would not be a good strategy by which to implement that approach.

Neuroanatomical and psychological data almost never fall into distinct clusters corresponding to sex (e.g., see Carothers and Reis 2013). For this reason, looking to sex as a source of ‘difference’ in the brain has been criticized (Jordan-Young and Rumiati 2012). But because most people regard sex as a category rather than as a continuous variable, even the smallest effects are an easy sell. Single-sex education programs offer a convenient solution to a vexing, urgent problem. Just as Men are from Mars, Women are from Venus (Gray 1992) promised to improve relationships by showing us how to embrace difference, single-sex classrooms promise to save our failing school system. We will need better ways to convey to the public that boys and girls are in fact the same—not from Mars and Venus or even, as some have phrased it, from North and South Dakota (see Eliot 2009). Looking at Fig. 1, I would argue that although a couple of boys may hail from Hoboken and one or two girls from Hackensack, the rest of the children are all from New York City.

3 When a Difference is not a Difference at All

Many sex differences reported in the media and presented to school administrators have uninteresting explanations or no support at all. Here, I will discuss just one example: the amounts of gray and white matter in the brain. Most of the relevant studies suggest that the average amount of gray matter in women is slightly higher than in men (reviewed by Cosgrove et al. 2007). Gray and white matter volumes are closely tied to overall brain volume, which is about 10 % larger on average in men than women. When gray matter volumes are corrected for overall brain size, the sex effect is substantially lessened (Leonard et al. 2008) or eliminated (Blatter et al. 1995; Courchesne et al. 2000). As an example, data from Lenroot et al. (2007) are shown in Fig. 2a and then redrawn corrected for brain volume in Fig. 2b. The relative amounts of both gray and white matter in children ages 7–19 appear to be exactly the same in boys and girls.
Fig. 2

Some sex differences in the brain may be explained by overall brain size, which is larger in boys. (a) Data from Lenroot et al. (2007) suggest that levels of both gray and white matter are higher in boys. (b) When the average values are divided by the average values given for overall brain size, the sex difference appears to be eliminated

Despite the large literature showing that the sexes have similar amounts of gray and white matter, professional development materials for teachers often paint a starkly different picture. They routinely assert that boys have 6.5 times as much gray matter as girls, and girls have a whopping ten times as much white matter as boys (Box 1). A difference that large would be obvious using techniques available before the dawn of recorded history (e.g., looking at the brain of a deceased person), and would be just as salient as sex differences in reproductive organs. As of this writing, a Google search on ‘women have 10 times more white matter’ produces more than 6,000 hits. The CBS Early Show covered this difference as if it were breaking news (CBS News 2010) but provided no source. With some effort, I traced the myth to media coverage of a paper by Haier et al. (2005). As I expected, these authors did not report sex differences in the amounts of gray or white matter. Rather, they used structural MRI to identify areas of gray and white matter in each participant’s brain and then searched for correlations between the sizes of those areas and scores on an intelligence test. The measures that were 6.5 times larger in men and 10 times larger in women were not the total gray or white matter volumes, but rather the volumes that predicted the score on the test—without regard to whether those correlations were statistically significant. The scores were significantly related to the size of only a few areas of gray matter in men, and one in women. In a press release, the authors commented that human evolution has created two different types of brains designed for equally intelligent behavior (Today@UCI 2005). The media then proceeded to run amok, giving rise to perhaps the most nonsensical neuroscience myth since the one about humans using only 10 % of their brains. If Haier et al. have attempted to address the confusion, their attempts have been swamped by the sheer volume of misrepresentations.

Box 1 An urban legend is born. A 2005 paper by Haier et al. was so grossly misinterpreted by the media that it gave rise to a now-pervasive urban legend: Men have 6.5 times as much gray matter as women, and women have 10 times as much white matter as men. The 2005 paper, which described a structural MRI study relating intelligence to certain voxels of gray and white matter in men and women, contained a version of the figure above. The figure has been reproduced hundreds of times on the internet, sometimes with an accurate caption but more often with a caption such as, “Activity in men and women while taking an IQ test” (no imaging was actually done during the test) or “Men have 6.5 times as much gray matter and women have 10X as much white matter”. Figure from Andrew-Sfeir (2012). Open image in new window

4 Leaps of Logic and the Allure of the Brain Scan

Proponents of brain-based single-sex education have argued that modern imaging techniques have revealed large differences between the brains of boys and girls (Chadwell 2010; Gurian and Stevens 2005). They present images of the BOLD response or white/gray matter distribution, chosen to illustrate differences that may or may not have ever been reported in peer-reviewed literature. Such images are quite powerful; one teacher wrote, ‘I was trained in the idea that each student is an individual. But when I saw the PET scans of boys’ and girls’ brains, I saw how differently those brains are set up to learn.’ (Gurian and Stevens 2004; italics added). Note that in addition to believing that the images represented a typical boy and girl, the teacher was convinced that they showed something about learning styles. Although that leap of logic is a large one, it is common. Such ‘reverse inferences ’ (Poldrack 2006) rest on the fallacy that if neuroanatomical differences exist, they must explain behavioral differences. The larger hippocampus of girls, according to materials distributed to teachers, endows them with better memory, social skills, and language skills (Gurian and Stevens 2004; McBride 2008). Similarly, the larger amygdala of boys supposedly makes them more aggressive, reduces their attention span, and increases the amount of space they require in the classroom (Gurian and Stevens 2005; Multiplying Connections 2012). The scientific basis for these claims is unclear, but to the non-expert, they apparently seem plausible.

Perhaps the most pervasive of illogical reverse inferences is the attribution of cognitive abilities to the relative volumes of white and gray matter, which is presumed to be related to the degree of interconnectedness among brain regions. The evidence for sex effects on both white matter volume and connectivity has been reviewed elsewhere (e.g., Bishop and Wahlsten 1997; Bruner et al. 2012) and is tangential to my point here: How and whether these factors affect abilities is unknown. Sex differences in connectivity and white matter volume have nonetheless been cited as evidence of either male or female superiority in spatial orienting, language skills, empathizing, map reading, mathematics, and multitasking (reviewed by Fine 2010). To a non-expert, the absence of a known function may not be particularly relevant because a sex difference implies function. For example, if women are found to have more white matter and men more gray matter, then white matter is said to be responsible for multitasking and gray matter confers mathematical ability (CBS News 2010). Conversely, if men are found to have more white matter and women more gray matter, then white matter is reported to confer mathematical ability, while gray matter is important for multitasking (Chamberlain 2009). Ignored are the findings that mathematical ability does not vary with sex (reviewed by Hyde 2014), and the only two studies on multitasking showed no female advantage (Hambrick et al. 2010; Mäntylä 2013). A sex difference in the brain appears to be enough to convince many people that a difference in ability must exist, despite the maddening circularity of the logic.

Why are such tenuous arguments so convincing? First, they support stereotypes. The combination of reverse inference and social stereotypes is a dangerous one, as was famously illustrated by Gould in The Mismeasure of Man (1981). Gould debunked nineteenth-century research alleging that intellectual superiority of white men could be explained by their larger cranial capacity, compared with women and men of other races. Gould argued that the conclusions of the researchers were shaped by their own expectations. The stereotypes of that century ensured that the research would be accepted, even embraced. Likewise today, brain-based explanations for effects of sex on achievement capitalize on long-held stereotypes, often triggering aha moments for parents and teachers as they become convinced that their own personal beliefs are validated by science (Kaufmann, n.d.). The more dearly held those beliefs, the harder it is to convince the believer that such arguments are flawed. As one New York Times reader commented, ‘[Feminists] just love to pretend there are no hard differences between the brains of men and women,’ which the reader called a ‘brazen denial of what is not only real but thunderingly obvious’ (comment on Schott 2010).

Sadly, the use of reverse inference to perpetuate stereotypes is not limited to amateurs. Neuroscientists themselves are guilty (see Bluhm 2012). In a recent imaging study, Ingalhalikar et al. (2014) described effects of sex on the ‘connectome’ of the brain, arguing that women showed stronger interhemispheric connections, whereas men’s brains were better connected within hemisphere. In the discussion section of the paper, the authors inferred that the male-typical pattern would confer an efficient system for coordinated action, whereas the female-typical interhemispheric connections would better integrate the ‘analytical’ left hemisphere with the ‘spatial and intuitive’ right hemisphere. The degree of overlap between the sexes was not reported; in the institution’s press release, however, the authors described the sex difference as “stark” and “striking” and suggested it might explain why men are better at cycling and women better at socializing and multitasking (Penn Medicine 2013). In an interview, an author remarked, ‘I was surprised that it matched a lot of the stereotypes’ (Sample 2013). Thus, the authors themselves overinterpreted their own work, providing media-ready sound bytes both in interviews and in the paper itself. If the authors make such claims, can we blame the media, educational consultants, or teachers and parents for doing the same?

Neuroscientists and psychologists worldwide reacted to these statements with disappointment. Dorothy Bishop of the University of Oxford commented, ‘The behavior of the scientists doing the study is hard to understand. When they talk of hardwired differences in brains of males and females, and link their results to putative behavioral differences that fit stereotypes but which they haven’t measured, they lose credibility among their scientific peers… Do they really believe what they are saying - in which case they are bad scientists? Or are they so swept up in a brief moment of media fame that they don’t care about their reputations?’ (Bishop 2013). During the days following publication, bloggers posted analyses of the degree of overlap, which they estimated to be large (see Lindeløv 2013; Ridgeway 2013), and raised a multitude of alternative explanations for the results, including experience, head motion in the scanner, and age (e.g., Fine 2013; Scott 2013). The longevity of these online criticisms, compared with the impact of the study itself, remains to be determined, but the authors likely got the message that their interpretations were not universally well received. The swift, scholarly response, which Bishop illustrated online using, serves as an excellent example of the kind of post-publication peer review now possible using social media.

Just as flawed arguments can be masked by seeming to support stereotypes, they can also be bolstered by compelling pictures of the brain in action. Weisberg et al. (2008) elegantly showed that faulty explanations for psychological phenomena can be made significantly more convincing, at least to non-experts, by mentioning a brain scan. The addition of ‘neuroscience’, even if irrelevant, successfully masked flawed logic in a scientific report for everyone but neuroscientists. Since few teachers and school administrators are experts in neuroscience, they are especially vulnerable to the allure of the scan. MRI scans have a troubling tendency to be interpreted by laypersons, and even some researchers, as windows into a brain untouched by experience—a brain in its raw, hardwired state. It should not be so hard to believe that behavior could change the brain—after all, the public generally accepts that exercise changes muscles and eating changes fat. Nonetheless, if a neural structure varies in size or activity between the sexes, that difference is almost invariably communicated to the public as the cause, not an effect, of a behavioral difference. This phenomenon extends far beyond sex differences ; brain scans are so convincing of hardwiring that they have led some to question whether criminals are responsible for their actions, or even whether humans have free will (Mobbs et al. 2007; Smith 2011). As human imaging grows out of its adolescence, and as more research emphasizes plasticity, the exquisite sensitivity of the brain to its environment will certainly be recognized. In the meantime, we need to remind ourselves to consider the hypothesis that a sex effect might be explained by experience and speak up when that hypothesis is not considered.

5 Moving Forward

Some authors have argued that because most sex effects in the brain are small and hard to interpret, the benefits of reporting them do not outweigh the tremendous costs (e.g., Jordan-Young and Rumiati 2012). Not all research on the topic is done for the purposes of division or understanding the construct of ‘sex’. Such effects can provide important clues about other factors, for example, genes or hormones, that shape the development of the brain. In a sense, sex is simply a natural manipulation of these factors that allows researchers to test their effects conveniently. Discovering a sex effect, particularly in a non-human model for which the effects of experience can be better controlled, provides a valuable starting point for further investigations into causal mechanisms. Rarely, however, does any discovery of an effect provide a valid reason for treating the sexes differently, and should not be used indiscriminately as justification for such (Roy 2012).

Perhaps in response to recent critiques (e.g., ACLU 2012; Halpern et al. 2011; Eliot 2009; Fine 2010), some proponents of single-sex education programs appear to be shifting their focus away from the brain. On the website of the National Association for Single-Sex Public Education, the Gender Differences in the Brain page now redirects to an unrelated page that duplicates material on a different topic. David Chadwell, who for years served as the coordinator of single-sex education programs for the South Carolina Department of Education, now takes a more agnostic view of brain-based approaches. In a 2011 interview, he noted that evidence for brain-based sex differences ‘will always be argued by researchers. There are books and research reports that say that there are differences and then there are books and research that say there aren’t differences’ (Whitmire 2011). His views echo those of teachers at my mother’s school, who found the arguments on both sides equally compelling. Ultimately, they decided against expanding their single-sex program because they could not reach a consensus. These signs are encouraging, but of course not satisfying. Although the number of single-sex classrooms is dwindling, the downturn can be attributed to a fear of lawsuits and lack of funds, not the rejection of pseudoscience (Meder 2012). Single-sex programs remain popular with teachers and parents, and misrepresentations of neuroscience data remain a commonly cited justification.

Before being tempted to cite a ‘sex difference’ as justification for division, I suggest that educators ask a series of questions about that difference (see also Roy 2012). First, is there actually a difference? As seen in Box 1, careful fact checking is critical. Non-scholarly sources, such as the media and popular press, are not reliable. Second, if there is in fact an effect, what is the degree of overlap between the sexes? Given that the majority of sex ‘differences’ are no larger than depicted in Fig. 1a, even a statistically significant sex effect is unlikely to justify splitting an entire group by sex. Instead, the only clear separation of boys and girls is likely to occur in the tails of the distribution—students in these tails can be targeted for intervention, but note that such targeting would be best accomplished using something other than sex, for example, test scores, to identify students who might benefit. Finally, in the event that a difference actually does meaningfully distinguish the sexes, does that difference suggest sex-specific needs? Is it possible, for example, to develop teaching materials that actually maximize learning accomplished by a particular part of the brain? Such a program would be ambitious indeed, and likely not in line with sound scientific research (Hardiman et al. 2012).

As neuroscientists, we can improve communication with the public by adopting a few changes in the way we report effects of sex. First, I suggest that unless the effect is quite large, the term ‘sex effect’ is preferable to ‘sex difference.’ Second, when possible, data are best presented in a way that allows readers to see the degree of overlap. For example, individual value plots, scatterplots, or distributions can be provided and effect sizes reported. Third, authors should consider factors that covary with sex, for example, experience, hormonal milieu, brain size, etc., as explanations for the effect rather than using terms such as ‘hardwired’. Finally, when we see that our results have been misinterpreted or misrepresented, we should publicly take issue. Now, more than ever before, venues are readily available for public commenting and discussion (see Bishop 2013). Of course, even before beginning a study, we should ask ourselves whether the goal is to understand how sex contributes variation to a biologically complex system or simply to divide the sexes. As eloquently pointed out by Roy (2012), research ‘primarily driven by an urge to neatly place people into pre-ordained categories… should be accompanied by a warning label’ (p. 223).

6 The Future of Neurosexism : Is the Quality of Health Care at Risk?

What has happened in public education should serve as a cautionary tale for medical practitioners, who are under increasing pressure to take the patient’s sex into account when considering treatment options. A large number of psychiatric and neurological conditions differ in prevalence or severity between men and women, including depression, anxiety, and pain (Greenspan et al. 2007; Mogil 2012), and some authors have called for more research to understand these effects (Cahill 2006; Beery and Zucker 2011; McCarthy et al. 2012). Some go so far as to suggest we should work toward sex-specific medicines (Gillies and McArthur 2010; Melcangi and Garcia-Segura 2010). In many cases, this strategy will undoubtedly prove to be beneficial, and performing clinical trials with both sexes is critical. As is the case for sex-specific education, however, the size of a sex difference must be considered before implementing any strategy to account for it. If the effect requires a large sample size to detect, or is sometimes not detected, we should proceed toward sex-specific treatment with extreme caution. Sex differences in physiology could be explained by any number of factors that covary with sex, such as body size, fat content, or plasma levels of hormones. In other words, a patient’s sex is unlikely to be the best predictor of his or her response to treatment. Our goal should ultimately be to move beyond sex to identify those predictors, particularly if they can be assessed by physicians, in order to make more informed decisions about treatments and maximize their efficacy.

For some disorders, we may not know the true size of a sex difference because the data are colored by gender stereotypes. In a study by Aragonès et al. (2006), physicians made erroneous diagnoses of depression much more often for female than male patients. In other words, overdiagnosis of depression was higher for women than men. Women are more likely to suffer from idiopathic pain and other syndromes with poorly understood etiology (e.g., chronic fatigue syndrome, irritable bowel syndrome), which contributes further to the risk of misdiagnoses of depression and generalized anxiety disorder (Bowman 2001; Meana 1998). A sex effect on the rate of overdiagnosis may contribute to or even explain a sex difference in the prevalence of any illness. Thus, less sexist and more accurate methods of diagnosis may be called for before, or in concert with, the development of sex-specific treatments.

A recent example from cardiovascular medicine illustrates how the reporting of sex effects could potentially cause harm. The past decade has seen many public health campaigns to raise awareness that symptoms of heart attack can be atypical in women. News stories such as Women’s Heart Attack Symptoms Are Different from Men’s (Longley 2013) and Recognizing the Female Heart Attack (Kam 2009) typically assert that symptoms in men and women are ‘drastically different’ (Forer 2011). Such articles commonly state that chest pain is a ‘man’s symptom’, whereas ‘female heart attack symptoms’ are fatigue, anxiety, and indigestion (Tytus 2010). The actual research shows that although symptoms of heart attack do differ somewhat between men and women, those differences are too small to be clinically informative (Gimenez et al. 2014) or to warrant sex-specific public health messages (Canto et al. 2007). Nonetheless, like claims that boys and girls learn differently, the concept of sexually dimorphic heart attacks has been embraced by the public and vigorously defended. For example, when a 2009 study showed no sex difference in rates of chest pain during myocardial ischemia (Mackay et al. 2009; see also Mackay et al. 2011), members of a women’s heart health support group posted that the lead author of the study was ‘full of garbage’ and needed to be ‘whacked upside the head’ (comment on Tobin 2009). Many websites continue to perpetuate the notion that women’s heart attacks do not resemble men’s, and cardiologists continue to call for more research on ‘fundamental biological differences’ between men and women (Maas et al. 2011). In this case, the likely interpretation of those differences by the public could have life-threatening consequences, for example, if women ignore chest pain or men brush off fatigue. A more effective public health strategy would emphasize that anyone, male or female, can present with atypical symptoms (Humphries et al. 2012).

7 Conclusion

If sex-specific educational policies and medical treatments are to be implemented in a fair and logical way, sex must explain an unprecedented proportion of the variability in the relevant trait such as a learning style or response to treatment. Otherwise, sex-specific solutions cannot efficiently address the problem at hand and will only serve to obscure the true source of variability (Jordan-Young and Rumiati 2012). In reality, sex differences in the human brain that meet this criterion—in other words that are absolute (McCarthy et al. 2012) or qualitative (Mogil 2012)—are vanishingly few. Even in other species, absolute sex differences in the brain are relatively rare and relate directly to absolute differences in copulatory or courtship behaviors (McCarthy et al. 2012). The apparent absence of such differences in humans does not mean we will never find them. Mogil and colleagues have shown that the molecular mechanisms underlying inflammatory and neuropathic pain appear to be qualitatively different in male and female mice (Sorge et al. 2011); Woolley and colleagues have shown an interesting dimorphism in the way estradiol modulates synaptic transmission in the hippocampus of rats (Hoang and Woolley 2012). The discovery of both effects was delayed because initial studies were conducted in just one sex, highlighting the need for research that includes both males and females (Cahill 2006; McCarthy et al. 2012; Mogil 2012). Although absolute sex differences do exist, they are not, as many laypersons believe, ‘thunderingly obvious’ (see Schott 2010), particularly before puberty. Quite the opposite—what is remarkable is not the difference, but the sameness (Carothers and Reis 2013; Hyde 2005, 2014)—a concept that has been explored in depth in psychology and gender studies but not yet embraced by neuroscience. It is the sameness we should be communicating to the public, because without that understanding, forthcoming discoveries of large and meaningful sex differences will not rise above the noise.



I am grateful to Shirley K. Maney, former teacher in the Winston-Salem/Forsyth County School system, for originally calling this controversial topic to my attention, and to Stephan Hamann for his advice and assistance. I also thank Chris Goode, Steve Nowicki, Deboleena Roy, and Kim Wallen for comments on the manuscript.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of PsychologyEmory UniversityAtlantaUSA

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