Binary or nonbinary? An evolutionary learning approach to gender identity

Fuente: arXiv
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Main Author: Truong, Hung
Format: Preprint
Published: 2024
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author Truong, Hung
author_facet Truong, Hung
contents Is gender identity binary or nonbinary? My analysis shows that while both are possible, the latter is a more attracting equilibrium under an adaptive learning perspective. I frame the gender identity problem as a modified \textit{battle of the sexes} game, where individuals define their gender identity under pairwise matching motives. From a baseline game-theoretical standpoint, I demonstrate that the binary-only world and the nonbinary-only world are both Nash equilibria in the stage game and are locally stable in the infinitely repeated game. Thus, any state of gender identity could theoretically persist. I then adopt a genetic learning algorithm as an equilibrium selection criterion to investigate evolutionary dynamics further and provide a rationale for the transition from binary to nonbinary gender identity. Specifically, in a binary-origin world, divergence occurs as individuals identifying as nonbinary gender evolve to become the majority due to their higher flexibility in matching outcomes. My framework captures how adaptive learning drives identity evolution, offering a parsimonious tool to analyze how diversity and exclusivity emerge in varying economic environments.
format Preprint
id arxiv_https___arxiv_org_abs_2412_10959
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Binary or nonbinary? An evolutionary learning approach to gender identity
Truong, Hung
General Economics
Economics
Is gender identity binary or nonbinary? My analysis shows that while both are possible, the latter is a more attracting equilibrium under an adaptive learning perspective. I frame the gender identity problem as a modified \textit{battle of the sexes} game, where individuals define their gender identity under pairwise matching motives. From a baseline game-theoretical standpoint, I demonstrate that the binary-only world and the nonbinary-only world are both Nash equilibria in the stage game and are locally stable in the infinitely repeated game. Thus, any state of gender identity could theoretically persist. I then adopt a genetic learning algorithm as an equilibrium selection criterion to investigate evolutionary dynamics further and provide a rationale for the transition from binary to nonbinary gender identity. Specifically, in a binary-origin world, divergence occurs as individuals identifying as nonbinary gender evolve to become the majority due to their higher flexibility in matching outcomes. My framework captures how adaptive learning drives identity evolution, offering a parsimonious tool to analyze how diversity and exclusivity emerge in varying economic environments.
title Binary or nonbinary? An evolutionary learning approach to gender identity
topic General Economics
Economics
url https://arxiv.org/abs/2412.10959