1
Department of Private Law, Faculty of Law and Political Science, Shiraz University, Shiraz, Iran.
2
PhD Candidate in Private Law. Department of Private Law, Faculty of Law, Islamic Azad University, Central Tehran Branch, Tehran, Iran.
Abstract
A significant portion of public and platform-based decision-making, previously anchored in human judgment, has increasingly been delegated to algorithmic scoring systems. This study offers a critical assessment of algorithmic scoring systems as an emerging paradigm of datafied governance within the dual realms of the state and digital markets. Drawing upon a transdisciplinary theoretical framework—comprising contextual integrity, procedural legitimacy, and legal anthropology—the paper analyzes the rights-based approach of the European Union in contrast to China’s order-centric utilitarianism, while diagnosing the structural pathologies of commercial platforms, including systemic data bias and the inherently biased nature of human feedback. The findings demonstrate that the logic of scoring erodes the traditional boundaries between public sovereignty and private authority, leveraging numerical authority to challenge institutional accountability. Finally, to facilitate a transition toward an effective regulatory model, this paper proposes a tiered and systemic framework consisting of five legitimizing normative conditions: meaningful transparency, effective contestability, functional equivalence, meaningful human oversight, and contextual integrity. Ultimately, this framework establishes an intelligent architecture for safeguarding individual rights and the rule of law in the algorithmic era.
kheirkhah, P., & Nakhjavani, A. (2026). A Critical Study of Algorithmic Scoring Systems in Data-Driven Governance: A Meta-Technical Approach. (e24269). Science and Technology Policy Letters, (), e24269
MLA
kheirkhah, P., & Nakhjavani, A. "A Critical Study of Algorithmic Scoring Systems in Data-Driven Governance: A Meta-Technical Approach" .e24269 , Science and Technology Policy Letters, , 2026, e24269.
HARVARD
kheirkhah P., Nakhjavani A. (2026). 'A Critical Study of Algorithmic Scoring Systems in Data-Driven Governance: A Meta-Technical Approach', Science and Technology Policy Letters, (), e24269.
CHICAGO
P. kheirkhah & A. Nakhjavani, "A Critical Study of Algorithmic Scoring Systems in Data-Driven Governance: A Meta-Technical Approach," Science and Technology Policy Letters, (2026): e24269,
VANCOUVER
kheirkhah P., Nakhjavani A. A Critical Study of Algorithmic Scoring Systems in Data-Driven Governance: A Meta-Technical Approach. STPL. 2026;():e24269 (In Persian).