Continuity Writing: AI-Mediated Writing and Cripping the Academy

Scholarly authorship has long rested on an inscription model — the assumption that legitimate knowledge production requires unmediated, independent textual production. For disabled scholars whose capacity to think and whose capacity to write have been decoupled by aphasia, chronic pain, fatigue, or any condition that severs the connection between thought and inscription, this model does not merely disadvantage. It excludes. A growing conversation about the ethics of AI use in scholarly writing has proceeded without disabled scholars, without augmentative and alternative communication (AAC), and without the question that most urgently requires an answer: what happens when AI-mediated writing is not a productivity choice but the condition under which a disabled scholar can participate in knowledge production at all? This paper introduces Continuity Writing — a seven-phase methodology for AI-mediated long-form scholarly argumentation developed through practice by a disabled scholar using Large Language Models as AAC. Theorized through AAC scholarship, crip technoscience, and epistemic justice frameworks, the methodology is guardrailed, documented, and accountable, exceeding every criterion the AI writing ethics consensus has proposed. It also introduces two original concepts: crip accumulation, proposed as a seventh interpretation of crip time describing the thickening of conceptual structures during expressive silence imposed by the inscription model; and community of accountability, naming the readership relationship in which governance decisions are documented and legible to evaluators with standing. This paper was written using the methodology it describes. Continuity Writing does not accommodate the academy’s terms. It crips them.