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At Meaningfulness Media Group, our research endeavors bridge philosophy, systems engineering, and speculative inquiry to forge rigorous frameworks for human purpose in an AI-accelerated era. Below is a curated selection of our published papers, available on Zenodo for open access.
These works explore foundational concepts—from AI authorship ethics and ontological modeling to free will, causal determinism, and compassionate media stewardship—laying the groundwork for ethical innovation and deeper existential understanding.
Dive in to explore the "paperwork of becoming" and join the dialogue shaping tomorrow's meaningful realities.
A Methodology for Generative Narrative and Civilization-Modeling
This paper presents the Speculative Ontological Engine (SOE), a versatile, systems-theory-based framework for modeling civilizations in narrative design, treating stories as emergent outcomes of simulated societal dynamics rather than traditional "world-building."
It introduces Speculative Procedural Ontopunk (SPO) as a reference genre-agnostic implementation, emphasizing administrative, legal, and ontological protocols as key conflict drivers. At its core is the recursive Antivalent Cycle algorithm, guided by the Antivalent Design Principle from complex systems theory, to simulate historical evolution via crisis responses.
The MODEL Framework comprises four components—the Kernel (foundational rules), Variable (dynamic elements), Cycle (iterative processes), and CORE (comprehensive database output)—constrained by THREAD Axioms for logical consistency. This creates transparent "Societal Flight Simulators" akin to computational social science, with the Codex Totalis as its canonical example for speculative social modeling.
DOI: [10.5281/zenodo.17797037]
A Technical Standard for the Multi-Tiered Disclosure of Generative AI in Creative Works
This paper proposes the Authorship Transparency Statement (ATS) Framework v1.0 as a multi-tiered technical standard to address the nomenclature gap in GenAI-assisted creativity, replacing vague binary disclosures ("Did you use AI?") with an objective, methodology-focused audit that promotes honest human-AI collaboration.
Anchored by the Bright Line of Prose Origin—a clear distinction based on first-pass drafting source—it defines a six-tier scale (ATS-0 to ATS-5) categorizing human roles from pure authorship (Traditional Artisan, ATS-0; Architect, ATS-1) to increasing AI autonomy (Director, ATS-3; Systems Architect, ATS-4).
Additional features include the Extent Axis (E-Scale, E0–E4) for quantifying AI volume in mixed works, domain-specific adaptations for fields like visual arts or code, machine-readable JSON/JSON-LD schemas interoperable with C2PA provenance standards, and institutional triage tools for automated policy enforcement. The framework aims to resolve the "transparency paradox" by fostering verifiable integrity and a "paperwork of becoming" in creative industries.
DOI: [10.5281/zenodo.18091713]
Principles of Pragmatic Veracity and Ontological Stewardship
Compassionate Logic is a practical ethical framework for communicating difficult truths responsibly in today’s fractured information environment. It avoids the false choice between brutal honesty and paternalistic deception, offering a way to remain truthful while managing timing, framing, and pace to reduce unnecessary harm.
The paper introduces a clear taxonomy of high-stakes harm, an auditable step-by-step disclosure protocol, and a shift from “oracle” truth-telling to guidance and resilience-building. It also includes usable artifacts: a printable assessment worksheet and an institutional audit-log template.
DOI: [10.5281/zenodo.18294160]
Distinguishing Causal Determinism from Pre-Destination in Complex Systems
As AI prediction and brain science advance, it is becoming popular to claim that human agency is meaningless because “everything is determined”. This paper argues that this conclusion is a mistake: even in a lawful universe, the long-term future of complex systems cannot be fully known or reliably predicted by any real observer inside the system.
It introduces the Unpredictability Horizon, the point where prediction breaks down in practice, and reframes agency not as a binary “free will vs. no free will” debate, but as a matter of Agency Depth: the richness of internal processing that shapes outcomes. The result is a scientifically grounded case that agency remains real, dignified, and functionally essential—even under determinism.
DOI: [10.5281/zenodo.18455937]
Defining Free Will via Computational Irreducibility and the Halting Problem
This paper offers a rigorous, non-mystical way to understand what people usually call “free will”. Building on the idea that complex agents cannot be perfectly predicted from the outside, it argues that agency is a real functional feature of certain systems—especially those that model themselves and make decisions through internal deliberation.
It replaces vague metaphysical debates with a practical concept: Functional Agency, the capacity of an agent to remain non-reducible to an external controller or predictor in any realistic setting. It then introduces a measurable view of Agency Depth and Effective Agency, showing how agency can strengthen or weaken depending on cognitive conditions and environmental pressures—providing a foundation for protecting human dignity in an era of increasingly powerful prediction.
DOI: [10.5281/zenodo.18511450]
These papers are maintained as living documents. If you find an ambiguity, a missing citation, a weak argument, or an opportunity to strengthen the standard, you are invited to contribute directly.
The official source is the public GitHub repository, where the full LaTeX text is available for transparent review and community improvement.
You can:
All content is released under CC BY 4.0, so you are free to reuse and build upon it with attribution.
Repository: https://github.com/MeaningfulnessMediaGroup/
License: CC BY 4.0
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