Dataset
The Coherence Method ; A Framework for Systematic Paradigm Discovery
| Τίτλος: | The Coherence Method ; A Framework for Systematic Paradigm Discovery |
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| Συγγραφείς: | Campbell, William Preston |
| Στοιχεία εκδότη: | Zenodo |
| Έτος έκδοσης: | 2025 |
| Συλλογή: | Zenodo |
| Θεματικοί όροι: | Scientific Methodology, First-Principles Reasoning, Paradigm Construction, Epistemic Framework, Ontology Engineering, Relational Logic, Paradigm Shift Design, Coherence Field Paradigm, Closed-System Reasoning, Foundational Science Architecture, Meta-Scientific Framework, Paradigm Discovery Process, Ontological Design, Relational Epistemology, AI Reasoning Architecture, Causal Structure Replacement, Epistemic Compression, Theory-Building Methodology, Post-Newtonian Science, Computational Ontology |
| Περιγραφή: | Coherence Method: A Framework for Systematic Paradigm Discovery This document presents the first systematic methodology for engineering scientific paradigms from first principles. Unlike traditional approaches that rely on incremental hypothesis testing, the Coherence Method provides a structured six-phase process for discovering foundational theoretical frameworks. Key Contributions: • First operational framework for paradigm engineering rather than accidental discovery • Integration of AI as Coherence Simulation Instrument (CSI) for rapid cross-domain validation • Systematic approach that reduces paradigm development time from decades to months • Documented methodology used to develop the Coherence Field Paradigm • Replicable process applicable across all scientific disciplines The Six Phases: 1. Recognition - Pattern resonance before formal concepts 2. Articulation - Translation into logical structure 3. Amplification - AI-assisted rapid iteration and stress testing 4. Validation - Cross-domain coherence verification 5. Formalization - Mathematical and predictive precision 6. Distribution - Strategic dissemination for field uptake Significance: This methodology transforms paradigm discovery from rare genius events to structured cognitive engineering. It represents the first systematic human-AI collaboration framework for theoretical breakthroughs and could accelerate scientific revolution across multiple fields. Applications: Researchers, graduate programs, and institutions seeking to systematically generate breakthrough theoretical frameworks rather than waiting for accidental discoveries. Published under Creative Commons ShareAlike license to ensure open access and collaborative development. |
| Τύπος εγγράφου: | dataset |
| Γλώσσα: | unknown |
| Relation: | https://zenodo.org/records/15834022; oai:zenodo.org:15834022; https://doi.org/10.5281/zenodo.15834022 |
| DOI: | 10.5281/zenodo.15834022 |
| Διαθεσιμότητα: | https://doi.org/10.5281/zenodo.15834022 https://zenodo.org/records/15834022 |
| Rights: | Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode |
| Αριθμός Καταχώρησης: | edsbas.FF4DCCB7 |
| Βάση Δεδομένων: | BASE |
| DOI: | 10.5281/zenodo.15834022 |
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