When Victorian Becomes a Prompt: Literary Periodization as a Generative Constraint in 100 AI-Generated Novels

Abstract:Generative AI inverts the typical periodization of literary history: the periodizing tag Victorian can now come first and influence what is written. Generative periodization, defined and tested here, describes the use of literary-period designations in generating texts. I test this approach on 100 book-length novels produced under Victorian and Zero-Style conditions using GPT, Qwen, and Llama workflows. The Period Alignment Score (PAS), trained on nineteenth-century literature and benchmarked against human Zero-Style prose, assesses alignment using topic-reduced grammatical features. Victorian prompts produce consistent historical-direction shifts in GPT and Qwen, but not robustly in Llama. Victorian-only recalibration and harder comparison corpora preserve the GPT and Qwen effects. Cross-model transfer also shows a shared direction of grammatical change. The measurable target is the broader nineteenth century rather than the Victorian period per se.

Computation and Language (cs.CL)

arXiv:2609.08689 [cs.CL]

(or arXiv:2609.08689v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.08689 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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