A standardized approach to measuring gender transparency in languages

Abstract

Languages can express grammatical gender through different ortho-phonological regularities present in nouns (e. g., the cues “-o” and “-a” for the masculine and the feminine respectively in Italian, Portuguese, or Spanish). The term “gender transparency” was coined to describe these regularities (Bates et al., 1995). In gendered languages, we can hence distinguish between transparent nouns, i.e., those displaying form regularities; opaque nouns, i.e., those with ambiguous endings; and irregular nouns, i.e., those that display the typical form regularities but are associated with the opposite gender. Following a descriptive analysis of such regularities, languages have been recently classified according to their degree of gender transparency, which seems relevant in regard to gender acquisition and processing. Yet, there are certain inconsistencies in determining which languages are overall transparent and which are opaque. In particular, it is not clear whether some other complex regularities such as derivational suffixes are also “transparent” cues for gender, what really constitutes an “opaque” noun, or which role orthography and morphology have in transparency. Given the existing inconsistencies in classifying languages as transparent or opaque, this work introduces a proposal to assess gender transparency systematically. Our methodology adapts the standardized factors proposed by Audring (2019) to analyse the relative complexity of gender systems. Such factors are adapted to gender transparency on the basis of the literature on gender acquisition and processing. To support the feasibility of such a proposal, the concepts have been instantiated in a quantitative model to obtain for the first time an objective measure of gender transparency using European Portuguese and Dutch as instances of target languages. Our results coincide with the theoretically expected outcome: European Portuguese obtains a high value of gender transparency while Dutch obtains a moderately low one. Future adaptations of this model to the gender systems of other languages could allow the continuum of gender transparency to sustain robust predictions in studies on gender processing and acquisition.