Computational Analysis of Gender Depiction in the Comedias of Calder\'on de la Barca

TL;DR

This paper develops quantitative methods to analyze gender portrayal in Calderón de la Barca's comedias, revealing distinct gendered language patterns and enabling scene-level predictions of cross-dressing characters.

Contribution

Introduces a novel computational approach combining gender classification and explainability techniques to study gender depiction in 17th-century Spanish theatre.

Findings

Gendered language can be identified with high accuracy (up to 83%).

Semantic differences in male and female character portrayals are revealed.

Model effectively predicts cross-dressing characters scene-by-scene.

Abstract

In theatre, playwrights use the portrayal of characters to explore culturally based gender norms. In this paper, we develop quantitative methods to study gender depiction in the non-religious works (comedias) of Pedro Calder\'on de la Barca, a prolific Spanish 17th century author. We gather insights from a corpus of more than 100 plays by using a gender classifier and applying model explainability (attribution) methods to determine which text features are most influential in the model's decision to classify speech as 'male' or 'female', indicating the most gendered elements of dialogue in Calder\'on's comedias in a human accessible manner. We find that female and male characters are portrayed differently and can be identified by the gender prediction model at practically useful accuracies (up to f=0.83). Analysis reveals semantic aspects of gender portrayal, and demonstrates that the model is even useful in providing a relatively accurate scene-by-scene prediction of cross-dressing characters.