RECAP Framework v1.0: A Multi-Layer Inheritance Architecture for Evidence Synthesis
By: Hung Kuan Lee
Evidence synthesis has advanced through improved reporting standards, bias assessment tools, and analytic methods, but current workflows remain limited by a single-layer structure in which conceptual, methodological, and procedural decisions are made on the same level. This forces each project to rebuild its methodological foundations from scratch, leading to inconsistencies, conceptual drift, and unstable reasoning across projects. RECAP Framework v1.0 introduces a three-layer meta-architecture consisting of methodological laws (Grandparent), domain-level abstractions (Parent), and project-level implementations (Child). The framework defines an inheritance system with strict rules for tiering, routing, and contamination control to preserve construct clarity, enforce inferential discipline, and support reproducibility across multi-project evidence ecosystems. RECAP provides a formal governance layer for evidence synthesis and establishes the foundation for a methodological lineage designed to stabilize reasoning across research programs.
Similar Papers
Procrustean Bed for AI-Driven Retrosynthesis: A Unified Framework for Reproducible Evaluation
Machine Learning (CS)
Helps computers design new medicines faster.
A Leakage-Aware Data Layer For Student Analytics: The Capire Framework For Multilevel Trajectory Modeling
Computers and Society
Finds students likely to quit school early.
Towards a unified framework for programming paradigms: A systematic review of classification formalisms and methodological foundations
Programming Languages
Builds code styles from simple math pieces