Kim, Hannah H. & Hanlon, Aaron R.: LLM Outputs as Stochascript

We argue that textual large language model (LLM) outputs form an emergent genre, which we call stochascript. Following Ralph Cohen’s “empirical-historical” theory, we treat genres not as fixed sets of traits but as evolving categories shaped by social and technological change. LLM outputs resist placement as fiction, nonfiction, or bullshit: they lack fictive intent, do not always invite make-believe, are not reliably informational, and remain indifferent to truth while optimized to seem helpful