Matriarchy Classics: A Computational Approach to Swap Only Gendered Words in Classic Novels

A paper posted to arXiv (2611.07134v1) proposes a computational method that gender-swaps public-domain novels while guaranteeing that only gendered words are inverted and all other words remain unchanged, a task the authors say both large language models and naive rule-based methods fail to complete. The method combines a custom whitespace-preserving tokenizer, gender-swap mappings across plural and possessive forms, pronoun handling, and a character renaming strategy, cutting the work from weeks of manual labor to minutes. The authors demonstrate it on Pride and Prejudice and The Great Gatsby, and argue gender-swapped novels could serve as tools to investigate the gender biases of readers, authors, societies, and AI systems.

arXiv:2611.07134v1 Announce Type: new Abstract: This paper proposes a trustworthy computational method to gender-swap public domain novels, with programmatic guarantees that only gendered words are inverted and all other words are left unchanged. This may seem like a simple task, but both large language models and naive rule-based methods fail to complete it. The proposed method includes a custom whitespace-preserving tokenizer, gender-swap mappings across plural and possessive forms, pronoun handling, and a character renaming strategy. It shortens the time required to gender-swap a novel from weeks of manual labor to minutes. The method is demonstrated on two public-domain novels. Pride and Prejudice is transported to matriarchal Regency England, where inheritance flows through daughters, mothers rule the household, and a frantic Mr. Bennet is determined to secure advantageous marriages for his sons. The Great Gatsby pivots to a matriarchal Jazz Age where newly-rich Ms. Gatsbee throws lavish parties in the hopes of reuniting with her lost love, David, who is now married to the violent Thelma Buchanan. Gender-swapped novels could serve as useful tools to investigate the gender biases of readers, authors, societies, and AI systems.