Abstract
This paper proposes a textual analytics approach to the discovery of trends and variations in social development. Specifically, we have designed a linguistic index that measures the marked usage of gendered modifiers in the Chinese language; this predicts the degree of occupational gender segregation by identifying the unbalanced distribution of males and females across occupations. The effectiveness of the linguistic index in modelling occupational gender segregation was confirmed through survey responses from 244 participants, covering 63 occupations listed in the Holland Occupational Codes. The index was then applied to explore the trends and variations of gender equality in occupation, drawing on an extensive digital collection of materials published by the largest newspaper group in China for both longitudinal (from 1946 to 2018) and synchronic (from 31 provincial-level administrative divisions) data. This quantitative study shows that (1) the use of gendered language has weakened over time, indicating a decline in occupational gender stereotyping; (2) conservative genres have shown higher degrees of gendered language use; (3) culturally conservative, demographically stable, or geographically remote regions have higher degrees of gendered language use. These findings are discussed with consideration of historical, cultural, social, psychological, and geographical factors. While the existing literature on gendered language has been an important and useful tool for reading a text in the context of digital humanities, an innovative textual analytics approach, as shown in this paper, can prove to be a crucial indicator of historical trends and variations in social development.
Highlights
Occupational gender segregation refers to the tendency of men and women to work in different professions (Blackburn et al, 2002)
In this paper, we designed an innovative method of digital humanities research to discover social development trends
We proposed and implemented a data analytics-based approach that measures gender segregation in occupations in a language without gender; we developed a new linguistic index that is grounded in gender markedness theory and has been validated using a questionnaire survey
Summary
Occupational gender segregation refers to the tendency of men and women to work in different professions (Blackburn et al, 2002). Previous studies have attempted to attribute this inequality to aptitudes differences between the sexes This can been seen in (Baker and Cornelson, 2018) which claims that males’ higher tolerance for noise is the reason for their disproportionately higher levels of employment in noisy occupations. The perception, or assumption, of occupational gender distributions leads to biased associations, or in other words, an ‘automatic stereotyping’ (Banaji and Hardin, 1996). This stereotyping can be operated through a spontaneous reflection of cognitive expectancy (Kunda and Oleson, 1997; Yzerbyt et al, 1999), the adaptation to motivational and interpersonal communication goals, or the consideration of interpersonal context and interaction between individuals (Beukeboom, 2014). The ‘women’s work–men’s work’ phenomenon is perpetuated by gender typing in language, which affects the occupational aspirations of both men and women, their entry into an occupation, and their treatment and advancement within an organisation (Reskin and Hartmann, 1986; Ruble, 1983)
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