DFAS-MRL-01: TOWARD A META-SCIENCE STANDARD FOR RESEARCH LEGITIMACY
DOI:
https://doi.org/10.61421/IJSSMER.2026.4503Keywords:
Meta-Science Research Legitimacy (MRL), Research Governance, Path Integrity, Process-Governed Science, Temporal Coherence, Decision-Path Traceability, Scientific Legitimacy, Artificial Intelligence, DFASAbstract
Introduction: Contemporary academic systems evaluate scientific work primarily through outputs, results, methods, and narrative coherence, while the research path itself remains comparatively under-governed. This structural limitation becomes increasingly consequential under acceleration driven by artificial intelligence, automation, and high-volume research production.
Methods: This paper adopts a normative meta-scientific approach to conceptualize research legitimacy through governance rather than outcomes alone. It develops the framework through conceptual separation of methodological rigor, result validity, and path integrity, integrating research path governance, causal discipline, and temporal knowledge traceability while intentionally withholding operational mechanisms.
Results: The analysis establishes traceable, temporally coherent, and governed decision paths as a distinct condition of scientific legitimacy, independent of result correctness or institutional acceptance. It identifies process-governed science as an alternative to reliance on output-based validation alone and establishes the meta-scientific conditions under which future research-governance standards may emerge.
Discussion: The framework positions governance of the research path as a prerequisite for sustaining scientific legitimacy under accelerated knowledge production. Rather than introducing tools, metrics, or enforcement systems, it establishes a foundational conceptual standard for governing how scientific knowledge is produced, revised, and justified.
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Alaali, H. M. H. (2025a). DFAS Meta-Science Philosophy Constitution. DOI: https://zenodo.org/records/16283522
Alaali, H. M. H. (2025b). DFAS-EEP: Editorial Ethics Protocol for Governance Integrity in Scientific Publishing. SSRN. DOI: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5375339
Alaali, H. M. H. (2025c). The DFAS-FEP Protocol: A Global Governance Standard for Responsible AI Use and Authorship Integrity in Financial Modelling. DOI: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5260517
Alaali, H. M. H. (2026d). DFAS-CM: The Foundational Evolution of the DFAS Causal Method - From Dynamic Financial Algorithms (AFMF) to a Behavioral–Temporal Causal Doctrine. OSF Preprint. https://osf.io/9z4kj/overview Zenodo. https://zenodo.org/records/22261860
Alaali, H. M. H. (2026e). DFAS-RJ: The Research Journey: From Contradiction to Doctrine. OSF Preprint. https://osf.io/9z4kj/overview Zenodo. https://zenodo.org/records/22261905
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Copyright (c) 2026 Hasan Mohamed Husain Alaali

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