Gender beyond the binary: computationally mapping gender to a spectrum using sex differences in the brain

Abstract

Biological sex is far more complex than simply two categories: male and female. The mere existence of transgender and intersex individuals displays this complexity clearly on the surface, while the differences between cisgender people within their own respective categories brings this idea to a deeper level. While sex differences reveal themselves in many different scientific disciplines, this study will focus on findings in the field of neuroscience; specifically, it will narrow in on volumetric measurements of brain regions known to have differing trends across the male and female sexes. The construction of a surrogate data set driven by measurements extracted from existing literature will be used to fit a logistic regression model. The resulting probability function will be used to first create a base Biological Sex Spectrum; this refers to a representation of biological sex as a spectrum in the absence of societal influence. This probability function will then be modified to produce a Societally Influenced Gender Spectrum; this refers to a spectrum that has been influenced by the concept of the gender binary and more closely represents our current world. The comparison of these two spectra will reveal the space for an increase in gender diversity as societal views continue shifting further away from restricting gender stereotypes.