These volumes are working proposals, not
fixed assignments. They will be refined collaboratively
through the Wednesday Lab as editors and contributors
develop the questions, relationships, and chapters that the
field requires.
Volume 1 · Working proposal
Generative AI, Quantum Storytelling, and
Organizational Futures
Possible editors: David M. Boje and
Grace Ann Rosile
Explores quantum antenarratives, living-machine
storying, ethical guardrails, and the organizational
futures produced when generative systems become actors
in sensemaking.
Submitted chapter proposal · Data
Analysis and Storytelling in the Age of AI
September 30 agenda · 10-minute
presentation
Reading Stories as Data: Qualimetric and Antenarrative
Methods for Studying AI and Organizational Storytelling
Farzaneh Fatemi, University of Tabriz,
with D. M. Boje
This submitted chapter is the proposed how-to backbone
of the volume: a teachable bridge between data analysis
and storytelling. Farzaneh Fatemi will present this
chapter proposal for ten minutes at the September 30
World Scientific Encyclopedia Series 3 Working Lab.
Open the chapter proposal, abstract, structure,
worked illustrations, and contribution
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.
Volume 2 · Working proposal
Narrative Authority, Cognitive Access, and
Institutional Legitimacy
Proposed volume editor: Jillian Saylors
Examines AI-supported cognition, disability and
neurodiversity, authorship, scholarly labour, expertise,
provenance, trust, surveillance, and governance—asking
who may think, know, decide, and count as a legitimate
knower.
Volume 3 · Working proposal
True Storytelling, DEI, and the Age of AI
Proposed volume editor and contributing
author: Oscar Edwards
Investigates diversity, equity, inclusion, belonging,
representation, and voice in AI-mediated organizations,
using True Storytelling to ask whose experiences are
amplified, stereotyped, excluded, or made answerable.
Volume 4 · Working proposal
Human–AI Co-Creation in Entrepreneurship and Strategy
Proposed volume editor: Anton
Shufutinsky
Centers human factors, sociotechnical systems, and
human-systems integration. Contemporary Sociotechnical
Systems Theory provides a path for examining when AI
augments rather than displaces human judgment.
Volume 5 · Working proposal
Strategy Storytelling Against Cognitive Surrender
Proposed editor or co-editor: Yue Cai ·
Introduction in development: Mark Hillon
Draws together strategic renewal, storytelling in
multinational corporations, financial-story
deconstruction, management ethics and aesthetics,
socio-economic world-building, and community-based
prosperity. The developing introduction connects these
chapters to the Age of AI and positions grounded
storytelling as an antidote to cognitive surrender.
Volume 6 · Working proposal
SEAM: Socio-Economic Consultation in the Age of AI
Editorial team to be decided · Amandine
Savall, Véronique Zardet, and Marc Bonnet will
contribute as editors and/or authors
This volume brings the Socio-Economic Approach to
Management (SEAM) into direct conversation with AI
transformation. It would examine consultation, hidden
costs, untapped human potential, work design, and
socially responsible capitalism in organizations
adopting AI. Rather than treating technology as a reason
for human replacement, the volume would develop
practical and answerable ways to co-design AI-enabled
change with the people and communities affected by it.