Sex Is a Biological Variable

Many suggest learning and eliminating “gender bias” can erase any sex differences in non-reproductive behavioral traits. I disagree, believing instead that the brain is sexually dimorphic; there are significant differences between the sexes in cognition, “processes involved in acquiring, storing, and using information from the environment” (Shettleworth, 2013; Williams, 2017). The National Institutes of Health joins me in this assumption, issuing notice NOT-OD-15-102, reading in part, “NIH expects that sex as a biological variable will be factored into research designs, analyses, and reporting in vertebrate animal and human studies (NIH, 2015).

Everybody champions gender equity (or should), a social goal striving for equal treatment of males and females. I propose that we can reach this lofty goal by assuming brains are sexually dimorphic and weighting selection and reward criteria so that total male- and female-dominated traits are equal.

Before continuing, let’s understand what “women exhibit X behavioral trait” and “predisposition” mean. The former means the trait is a population characteristic; any single woman or man may “violate” the population’s characteristic. Moreover, most behavioral traits are complex, are continuous rather than discrete. A bell curve results when plotting individual variation. The curve might be smooth and balanced, like charting variation in height. There are equal numbers of shorter- and taller-than-average humans. Or, the curve might be skewed to one side or the other for another continuous trait. Thus, for all behavioral traits there are two bell curves, one for women and one for men (it’s okay to disagree, because whether the trait is sexually dimorphic or not, my proposal ensures equal treatment). When the two curves describing the same behavior are overlaid, areas under the two curves overlap. Thus, men are taller than women, but some women are much taller than some men.

Now, what does “predisposed” mean? Most humans (like most animals) exhibit consistent behavioral patterns in response to an environmental context (their “temperament”); they are “predisposed to X.” They don’t always show this behavior, but the chances are greater they will display X rather than Y behavior. People can change and learn new behavior, but we can put this aside. We only need to accept the common-sense observation that learning to change behavioral predispositions is not an easy task.

All organizations—businesses, schools, non-profits, and government agencies—establish behavioral criteria for hiring, salary, promotion, and other types of rewards. For instance, sales or “customer counts” are vital to most organizations, directly or indirectly. Organizations seek and reward individuals who successfully “get customers,” and “getting a customer” means competing with others. Thus, organizations hire and reward people who perform well in a competitive environment. Men (probably) thrive in competition whereas women eschew it. That is, men want to “win” whereas women want to create mutually rewarding relationships. If you assess people on competitiveness, you favor the population of all men over the population of all women. Inequity results.

That’s the case in America. Like, “is competitive,” most selection criteria favor men. As a result, more men than women occupy sales-oriented positions, which includes leadership or management. Leaders are good sales people, must “sell” the organization’s goals. Embracing the sexually dimorphic brain means organizations should balance “competitiveness” with an assessment of an individual’s skills at maintaining relationships, which favors women because they are (purportedly) better than man in affiliative behavior.

Thus, embracing the sexually dimorphic brain means the list of rewarded traits now contains at least two criteria: “is competitive” and “demonstrates affiliative behavior.” There’s no need to train women to be more competitive or men to exhibit more affiliative behavior (although it’s desirable). We simply need to ensure that the total weight of all (purportedly) male- and female-dominated traits are equal in any decision matrix for hiring and rewarding people. The list of sexually dimorphic traits that David Schmidt compiled is helpful (Schmidt, 2017).

In conclusion, let’s stop arguing that males and females are equal or can be trained to be so in any behavioral trait. Instead, let’s embrace the sexually dimorphic brain, balance the weight given to male- and female-dominated traits, and finally achieve gender equity.

References

NIH (2015. National Institute of Health Notice Number: NOT-OD-15-102: Consideration of Sex as a Biological Variable in NIH-funded Research. Release date: Release Date: June 9, 2015 https://grants.nih.gov/grants/guide/notice-files/NOT-OD-15-102.html

Schmidt, D. (2017). Sculpted by Evolution. Psychology Today, November, 2017. https://www.psychologytoday.com/articles/201711/sculpted-evolution?collection=1107987

Shettleworth, S. J. (2013). Fundamentals of Comparative Cognition. New York, N.Y.: Oxford University Press, Inc. Williams, CA (2017). What is Cognition? CogQuiz blog. https://cogquiz.com/Blog/index.html

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