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Sexual Dimorphism in Language, and the Gender Shift Hypothesis of Homosexuality - PubMed

  • ️Fri Jan 01 2021

Sexual Dimorphism in Language, and the Gender Shift Hypothesis of Homosexuality

Severi Luoto. Front Psychol. 2021.

Abstract

Psychological sex differences have been studied scientifically for more than a century, yet linguists still debate about the existence, magnitude, and causes of such differences in language use. Advances in psychology and cognitive neuroscience have shown the importance of sex and sexual orientation for various psychobehavioural traits, but the extent to which such differences manifest in language use is largely unexplored. Using computerised text analysis (Linguistic Inquiry and Word Count: LIWC 2015), this study found substantial psycholinguistic sexual dimorphism in a large corpus of English-language novels (n = 304) by heterosexual authors. The psycholinguistic sex differences largely aligned with known psychological sex differences, such as empathising-systemising, people-things orientation, and men's more pronounced spatial cognitive styles and abilities. Furthermore, consistent with predictions from cognitive neuroscience, novels (n = 158) by lesbian authors showed minor signs of psycholinguistic masculinisation, while novels (n = 167) by homosexual men had a female-typical psycholinguistic pattern, supporting the gender shift hypothesis of homosexuality. The findings on this large corpus of 66.9 million words indicate how psychological group differences based on sex and sexual orientation manifest in language use in two centuries of literary art.

Keywords: LIWC; cognition; computerised text analysis; evolutionary psychology; personality; psycholinguistics; sex differences; sexual orientation.

Copyright © 2021 Luoto.

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Conflict of interest statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1

A summary of sex difference effect sizes (Cohen’s ds) with 95% confidence intervals (CI) on 24 psycholinguistic variables. The sample comprised 304 novels by 86 heterosexual male novelists and 85 heterosexual female novelists, published between 1800 and 2018. Cohen’s ds for each psycholinguistic variable are depicted as filled circles, which are scaled to reflect the prevalence of each word category in the overall sample: the larger the circle, the more frequently do words in that category occur in the overall sample. Positive ds represent male advantage; negative ds indicate female advantage. Psycholinguistic categories that are used more frequently by male authors appear on the right side of the figure, and psycholinguistic categories favoured by female authors appear on the left side of the figure. Error bars represent 95% confidence intervals. The effect sizes and CIs are calculated based on a multilevel model which controls for variation in publication year and author’s age at publication (Supplementary Table 8).

FIGURE 2
FIGURE 2

A summary of multilevel sexual orientation effect sizes (Cohen’s ds) with 95% confidence intervals (CI) on 24 psycholinguistic variables. The sample comprised 318 novels by 86 heterosexual male novelists (n = 151 novels) and 55 homosexual male novelists (n = 167 novels). Cohen’s ds for each psycholinguistic variable are depicted as filled circles, which are scaled to reflect the prevalence of each word category in the sample: the larger the circle, the more frequently do words in that category occur in the sample. Positive ds represent higher scores in heterosexual male authors’ novels; negative ds indicate higher scores in homosexual male authors’ novels. Error bars represent 95% confidence intervals. The effect sizes and CIs presented here are calculated based on a multilevel model which includes publication year and author’s age at publication as covariates. The symbols are colour-coded based on the sex difference results (Supplementary Table 8) so that blue = male-typical; magenta = female-typical; black = no sex difference.

FIGURE 3
FIGURE 3

A summary of multilevel sexual orientation effect sizes (Cohen’s ds) with 95% confidence intervals (CI) on 24 psycholinguistic variables. The sample comprised 311 novels by 85 heterosexual female novelists (n = 153 novels) and 54 homosexual female novelists (n = 158 novels). Cohen’s ds for each psycholinguistic variable are depicted as filled circles, which are scaled to reflect the prevalence of each word category in the sample: the larger the circle, the more frequently do words in that category occur in the sample. Positive ds represent higher scores in homosexual female authors’ novels; negative ds indicate higher scores in heterosexual female authors’ novels. Error bars represent 95% confidence intervals. The effect sizes and CIs presented here are calculated based on a multilevel model which includes publication year and author’s age at publication as covariates. The symbols are colour-coded based on the sex difference results (Supplementary Table 8) so that blue = male-typical; magenta = female-typical; black = no sex difference.

FIGURE 4
FIGURE 4

Estimated marginal means and standard errors for article frequency in each group of authors. The estimated marginal means are adjusted for differences in publication year and author’s age at publication. ∗∗∗p < 0.001. ns, non-significant.

FIGURE 5
FIGURE 5

Estimated marginal means and standard errors for personal pronoun frequency in each group of authors. The estimated marginal means are adjusted for differences in publication year and author’s age at publication. ∗∗∗p < 0.001, ∗∗p < 0.01. ns, non-significant.

FIGURE 6
FIGURE 6

Estimated marginal means and standard errors for frequency of numbers and numerical words in each group of authors. The estimated marginal means are adjusted for differences in publication year and author’s age at publication. ***p < 0.001, **p < 0.01. ns, non-significant.

FIGURE 7
FIGURE 7

The evolutionary–developmental origins and proximate mechanisms underlying psychobehavioural sex differences, including those in language use. Figure adapted from Luoto and Varella (2021).

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