Abstract

Stories legitimate organizations, move markets, and increasingly reach people already narrated by AI systems — yet narrative is often dismissed as too soft to measure. This chapter presents two complementary, paired traditions: qualimetrics, which codes and counts symbolic patterns, and antenarrative analysis, which reads the unfinished, fragmentary story-strands that counting cannot capture. Together they let a researcher both measure a narrative and interpret how meaning is made, reframed, or suppressed. Written as a practical reference, it introduces the toolkit — discourse coding schemes, structured probe batteries, scoring rubrics (ABCD / ABCD+E), antenarrative reading, and Bakhtinian answerability protocols — and walks step by step through corpus and probe design, coding, AI-assisted verification, and reliability, before showing how to move from counts to meaning. The Ghost Vortex — the leadership shadow embedded in an AI product — serves as a signature illustration of what this reading can surface. Worked cases are drawn from the authors’ research program on AI, storytelling, and answerability. The chapter closes with guidance on studying narrative in the age of AI, where AI is both an analytic aid and an object of study.

How it fits the volume

It is the how-to backbone of the volume — the teachable bridge between “data analysis” and “storytelling.”

Proposed structure

• Why storytelling needs a method now — narratives as organizational reality; the measurement challenge in the AI era.
• Two paired traditions — qualimetrics, counting, and antenarrative analysis, reading the unfinished story.
• The toolkit — discourse coding, probe and protocol batteries, ABCD / ABCD+E scoring rubrics, antenarrative reading, and answerability protocols.
• Designing a study — building a corpus or probe set; turning a narrative grammar into codes.
• Coding in practice — procedure, AI-assisted verification, and establishing reliability.
• From counts to meaning — why frequency alone misleads; the Ghost Vortex as a worked reading.
• Doing it in the age of AI — AI as coder and as object of study; disclosure and ethics.

Worked illustrations from the authors’ research program

• AI Institutional Grammar in Three National Registers — qualimetric discourse coding of AI-legitimacy narratives across US, Chinese, and French–EU corpora.
• Ghost Vortex and AI Moral Answerability — an eight-probe battery and ABCD answerability rubric across named LLM interlocutor threads.
• The AI Storytelling Organization — antenarrative coding of AI story performances via the Ghost Vortex Protocol.
• The Tesseract Leader (XYZA) — the Bakhtinian Answerability Protocol applied to AI corporate leaders.
• Leadership Without Leaders — reading AI artifacts as cultural texts, delegated narrative editing, and the Ghost Vortex.
• Ghost Vortex in the Machine Room — the ABCD+E rubric applied to AI data-center accountability probes.

Contribution

A clear, replicable, teachable method for turning organizational stories into evidence — a reference entry, grounded in a coherent body of studies, that researchers and students can actually follow.