Abstract
AbstractThis 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.
Publisher
Springer Science and Business Media LLC
Subject
General Economics, Econometrics and Finance,General Psychology,General Social Sciences,General Arts and Humanities,General Business, Management and Accounting
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