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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
SSRN Electronic Journal
Article . 2025 . Peer-reviewed
Data sources: Crossref
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Regulatory Legitimacy without Referents: On the Syntax of AI-Generated Legal Drafts

Authors: Startari, Agustin V.;

Regulatory Legitimacy without Referents: On the Syntax of AI-Generated Legal Drafts

Abstract

This article analyzes how AI-generated legal texts simulate legitimacy without referencing a sovereign authority. Based on a provenance-verified corpus of machine-generated documents, including contracts, terms of service, and automated policy clauses, the study shows that the legislator is structurally displaced by recurring patterns of passive voice, normative conditionals, and chains of subordinate clauses. The result is legalidad sin fuente (sourceless legality), where the appearance of regulatory authority is produced by syntactic form rather than institutional attribution. Comparing these drafts with traditional legislative writing, the article outlines a typology that instantiates autoridad no referencial and identifies a dual risk: loss of authority traceability and an accountability gap in the binding effects of these texts. This syntactic delegation constitutes a paradigm of regla compilada, situated within the tradition of formal grammars, in which language enacts governance without a governing subject. DOI Primary archive: https://doi.org/10.5281/zenodo.16746581 Secondary archive: https://doi.org/10.6084/m9.figshare.29829101 SSRN: Pending assignment (ETA: Q3 2025)

Keywords

Artificial Intelligence/legislation & jurisprudence, Linguistics/legislation & jurisprudence, Federal law, Supervised Machine Learning/economics, Law (individual), Abortion, Legal/ethics, Linguistics/organization & administration, Administrative law, Linguistics/standards, Artificial Intelligence/ethics, Planning law, Supervised Machine Learning/ethics, Linguistics/methods, linguistics, Linguistics/education, Supervised Machine Learning/classification, Machine Learning/trends, Machine Learning/history, Labour law, Linguistics/legislation & jurisprudence, Supervised Machine Learning, Legal Services/trends, Artificial Intelligence/economics, Supervised Machine Learning/trends, International law, Linguistics/ethics, Unsupervised Machine Learning/economics, Machine Learning/classification, Machine learning, Machine learning--Experiments, Unsupervised Machine Learning/trends, Agreement (legal), Comparative linguistics, Artificial Intelligence/trends, Machine Learning/legislation & jurisprudence, Family law, Civil law, Machine learning--Technique, Artificial Intelligence/supply & distribution, Legal text, Implementation law, Machine Learning/ethics, Linguistics/statistics & numerical data, Artificial intelligence, Artificial Intelligence/statistics & numerical data, Applied linguistics--Data processing, Comparative linguistics--Statistical methods, Artificial Intelligence/standards, Machine Learning, Linguistics/history, Legal Guardians, Legal profession, Machine Learning/standards, Linguistics/trends, Legal Services/education, Artificial Intelligence/supply & distribution, Machine Learning/supply & distribution, Legal regulation, Acupuncturists--Legal status, laws, etc., Abortion, Legal/standards, Linguistics/classification, Linguistics/organization & administration, Artificial Intelligence/statistics & numerical data, Legal Services/ethics, Unsupervised Machine Learning/ethics, Legal basis, Criminal law, Organisation (law), Artificial Intelligence/classification, Abortion, Legal, Legal system, Comparative law, Machine Learning/supply & distribution, Legal remedy, Machine Learning/legislation & jurisprudence, Law branch, Artificial Intelligence/history, Legal advertising, Linguistics/statistics & numerical data, Artificial Intelligence, Abortion, Legal/veterinary, Categorization (Linguistics), Legal procedure, Doctrine (law), Legal Epidemiology, Law (science), Linguistics/economics, Linguistics, Artificial Intelligence/legislation & jurisprudence, Machine Learning/economics, Ensemble learning (Machine learning), Unsupervised Machine Learning/standards, Community law, Applied linguistics--Statistical methods, Componential analysis (Linguistics), Machine learning--Evaluation, FOS: Languages and literature, Linguistics/instrumentation, Abortion, Legal/economics, Legal Services, Competence and performance (Linguistics), Unsupervised Machine Learning, Mining law

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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