project

Unraveling the interactions between culture and language: Does grammatical gender foster gender inequality and vice versa?

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Marc Allassonnière-Tang (CNRS, National Museum of Natural History, Paris)

Neige Rochant (Paris Nanterre University)

Olena Shcherbakova (Max Planck Institute for Evolutionary Anthropology)

Pei-Ci Li (Université de Lorraine)

Chundra Cathcart (Universität Zurich)

The human cognitive system interacts with the cultural environment. Within this interaction, the interplay between grammatical gender and sociocultural gender represents a societal challenge. The presence of grammatical gender (such as masculine and feminine) in language has an effect on how men and women are perceived by humans. Most studies compared languages with sex-based gender (such as masculine/feminine in Spanish) with languages that do not have a grammatical gender system (e.g., in English and Mandarin). However, other nominal classification systems such as noun classes (e.g., in Swahili) or classifiers (e.g., in Japanese) also categorize nouns of the lexicon into categories based on features such as animacy or shape. Furthermore, most languages considered in existing studies are Indo-European. Nevertheless, sex-based grammatical gender system are not restricted to this language family. For example, grammatical gender systems are also found in languages such as Mian (Ok family, Papua-New-Guinea).

We expand the data pool for testing the effect of nominal classification systems on gender parity. Information on grammatical gender is extracted from the data already gathered during the respective research of the project members. The data of sociocultural gender will be extracted from D-PLACE. The preliminary database will then be developed during consultation at the targeted institutions. In terms of method, two main types of analyses are considered: At the synchronic level, we use generalized linear mixed effect models that control for phylogenetic and geographic non-independence of societies and conditional inference trees to capture the multilevel interaction between the variables. At the diachronic level, Bayesian phylogenetic methods and confirmatory path analysis are used to establish the robustness of correlated evolution and the underlying causal relationships between the variables. Additional methods for testing the interaction between grammatical gender and sociocultural gender will be developed by consulting experts at the visited institutions.