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The Science of Sex Differences Is Complicated (and Biased)
IN THIS ARTICLE
Biology Gender
Michelle Rodrigues
Michelle Rodrigues
is a Postdoctoral Fellow with the Beckman Institute and the Department of Anthropology at University of Illinois.

There’s a lot of discussion about the problematic Google manifesto, and one of the issues brought up is the science of sex differences. Part of the problem is that it’s easy to cherry-pick evidence to support your own biases. Based on research on young chimpanzees, I could claim that humans have an evolutionary basis for females to be tool-oriented and males to be more socially-oriented. But it’s quite harder to truly understand human sex differences because we still don’t have the data to fully understand them. 

If you only know a little bit about human biology, it might sound simple. XX or XY? Ovaries or testicles? Estrogen or testosterone? But in reality, there’s a wider range of developmental possibilities. The development of sex-typical traits isn’t just determined by the sex chromosomes but is guided by multiple pathways that start in the womb, and continue through adulthood. For example, individuals with androgen insensitivity syndrome (AIS) may be XY, and produce androgens such as testosterone, but may develop female-appearing or intersex genitalia due to lack of functioning androgen receptors. Furthermore, the actions of any given hormone are interdependent on many other hormones, proteins that bind to them, and enzymes. For example, testosterone plays a role in male sex drive, but only because it’s converted to estradiol in the brain. Hormones can also have somewhat paradoxical effects. For example, administering oxytocin, a hormone associated with social bonding, in experimental settings can make people more trusting, but it can also make them more xenophobic. But most importantly, hormones are calibrated to the developmental environment and daily experiences, which means which we can’t attribute anything we measure in adult humans to “just” biology or genetics.

So, biology is complicated. But measuring biology is equally complicated, and very susceptible to biases. The impact of these biases in shaping scientific research was explained by Stephen Jay Gould in The Mismeasure of Man. Others such as Marlene ZukHolly Dunsworth, and Ambika Kamath have added to that. But we are still far from overcoming those biases. Biomedical research has only recently begun to require including female rodent models. Most of our understanding of mammalian biology and neuroscience comes from rodents, but it’s still largely biased toward understanding male rats. And most of our understanding of human psychology and neuroscience is biased toward Western, Industrialized, Educated, Rich, Democratic (WEIRD) populations. That means a lot of the science of sex differences is based on the norms of a limited set of cultures. Furthermore, the research process often requires weeding out ‘outliers.’ Imagine that you are researcher studying sex differences in personality in a population of university students. Are you going to include students who are intersex or trans? Probably not. Are you going include students who are gay or bi? Probably not. To get the nice, neat data you are looking for, your selection criteria requires omitting a lot of the variation that could obscure your results. And even the variation you do see at that stage is going to be shaped by the common cultural environment your participants were raised in.

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There’s an extensive body of literature on sex differences in children, but many of these are attributed to socialization. It’s impossible to separate the impact of biological sex from the influence of gender socialization that begins from birth. There’s a reason baby clothes are so strongly gendered–it gives people cues that impact how people respond to “girl” or “boy” babies. This makes it very hard for us to separate out the impact of biological sex versus the impact of cultural socialization in shaping sex-typical behavior.

But one area in which we have growing evidence is the impact of perceptions of gender (and ethnicity) in evaluating students and potential job candidates. Research indicates that simply switching a name can influence how someone is perceived. For example, candidates for a lab manager position with a female name are rated as less competent, and offered lower salaries, despite equal resumes. And manipulating the gender or ethnicity of a name can influence the likelihood of getting a response from prospective supervisors. There’s also research showing that class indicators help men receive positions, but decrease opportunities for women.

Add to that hostile or unsafe environments and harassment, and we can see evidence of cultural barriers to women’s participation and advancement in some areas of science and technology. So why are these discounted? Quite simply, it all comes back to those biases. We all have cognitive biases, and they are shaped by our cultural environment. In the study examining candidates for lab managers, female scientists were just as biased as male scientists in evaluating female-named candidates. We can take steps to critically examine our biases and account for them in our research and hiring practices. But nonetheless, part of “overcoming” those biases is realizing that we can never completely overcome biases, and instead recognize how they shape the science that we do and the way we evaluate the competency of the people around us.

To examine your own biases, check out Harvard’s Project ImplicitFor further reading on the role of hormones in development, I recommend Randy Nelson’s An Introduction to Behavioral Endocrinology. For more background in biases in studying human traits, I recommend Stephen Jay Gould’s The Mismeasure of Man.

6 Comments

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6 Comments

  1. Ted Howard says:

    Yes it is complex.
    Yes there are many factors present.
    Yes there can be biases.
    And the google memo in question does seem to me to be a very accurate description of the evidence available today. Why someone would get fired for using evidence based science is beyond me, unless those doing the firing were dogmatically opposed to science as a methodology.

    A difference of only .2 sd in distributions means that those near the middle are almost identical, yet at the extreme of the trail of the distributions (3.5sd) it is a 3:1 difference.
    People at the leading edge of any field tend to be on the tails of distributions.
    Relatively small difference between the sexes can and do produce very big differences at the tails of the distributions. That is basic statistics, nothing whatever to do with bias or power or control.
    And saying that is not to deny that bias and power and control can be present.
    Situations are complex – really complex.

    Over simplifying them in any set of dimensions leads to model failure.

    I am all for equality of opportunity for all individuals, and I am also for meritocracy in the particulars of any situation. That may mean differences in the ratios of sexes or any other metric in practice in any specific situation. Small changes in contexts can have big changes in outcomes, that is how species get to exist.

    The firing of James Damore from Google looks to me to be the result of management ideology dominating over scientific evidence.

    And I am sure that there are many cases of real discrimination present in Google and elsewhere. It exists. We need to each work against it, where-ever we find it.

    And I am no fan of equality.
    I don’t want to be exactly like anyone else – no fun in that, it is dangerous to promote monocultures.
    I am a fan of diversity.
    And everyone needs to be empowered to be as diverse as they responsibly choose (where ecological and social responsibility and necessary constraints on naive freedom), that actually allow individual life and individual liberty to be our highest rational values.
    In our modern context of our exponentially expanding ability to automate any process, that seems to demand we implement some sort of universal basic income (UBI) as a transition strategy to a secure future.

  2. LFP2016 says:

    The author is obfuscating the literature a bit, perhaps due to a “postmodern” bias so often taught in anthropology. Yes, biology is complicated. But the current preponderance of evidence from neurobiology, endocrinology, developmental psychology, primatology, etc all point to a clear biological basis for many sex/gender-specific behaviors.

    Across the world and throughout time, “masculine” behaviors (eg, aggression, violence, status-seeking) are much more associated with the male/XY sex and “feminine” behaviors (eg, social intelligence, verbal ability) are much more associated with the female/XX sex. That’s not a coincidence.

    Ideology cannot trump biology, no matter how hard third-wave feminists try. The “gender essentialism” they mock is an inconvenient fact.

  3. Rory Short says:

    The biological fact is that we are each unique individuals within whatever gender or non-gender we fall into and where we fall within it and we want to be valued by others for our uniqueness pure and simple.

  4. Stephan says:

    “So why are these discounted?”

    By whom?

    Why isn’t affirmative action accounted for? Why are “micro-aggressions/discriminations” employed to do explanatory and moral work, but not “micro-affirmative-action”?

    Why is the research on stereotype accuracy biased, and why don’t you mention stereotype accuracy? Why don’t you mention that “implcit association” (and “stereotype threat”) are contested? Why don’t you mention that blind hiring can lead to more men being hired? Why don’t you notice that it’s fine to claim “gender similarity” while speculating about “gender dissimilarity” gets one fired (see Summers, Google guy)? Is that perchance problematic? Why haven’t you undertaken it to measure the net outcome of these battling biases? Why haven’t you mentioned the political composition or researchers? There are more questions. I’ll suspend them in favor of asking one, are you biased and hypocrtical about your bias?

    • Stephan says:

      One may call that motivated interference (Gould on skulls): link to nytimes.com

      Have you looked at the media reception of the Google memo? Whatt kind of bias does that show? Check for words like “screed” and whether content and context were misrepresented. (How accurate is reporting on the “pay gap”? Compare. Is there an [economic] analysis of the “death gap”? What is the “unequal representation” among college students – much fewer men – attributed to?)

      Importantly, what is the assumption underlying policy and (antidiscrimination) law? It has a bias in favor of gender similarity. Is that problematic?

      Further reading: link to heterodoxacademy.org ; link to slatestarcodex.com ; link to ncbi.nlm.nih.gov