Epistemological Orchestration over Language Models: A Functional Architecture with Preliminary Evidence
Current applications of large language models to complex analytical tasks typically operate under a single inferential regime, which tends to produce structural convergence across systems and outputs. This technical note proposes a functional architecture for orchestrating heterogeneous epistemological frameworks over language models, in which distinct reasoning regimes interact through a shared canonical interface and a restricted family of typed transition operators. The architecture includes a formal criterion for distinguishing genuine inter-framework emergence from surface thematic overlap or output continuity inherited from prior framing. Preliminary evidence is presented from a multi-model validation study across four generative systems from distinct architectural families, showing structural convergence in framework outputs under shared orchestration constraints, together with a documented case of inter-framework emergence with complete result traceability. Results are presented at the level of functional architecture rather than reproducible technical specification. This note establishes existence, operating principle, and preliminary evidence as a foundation for subsequent full empirical validation.
Authors
- Marcelo Manucci (ORCID: https://orcid.org/0000-0002-9990-2316)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-03-28
- DOI
- https://doi.org/10.5281/zenodo.19287671
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00