
Current research on foundation model alignment concentrates on preference optimization and reward model design, yet it does not explain how these mechanisms become enforceable linguistic structures in model outputs. This paper introduces a formal bridge between training choices and governance-level effects by defining the operative rule as a compiled constraint that determines which clause types a model may produce. The framework maps policy inputs such as statutes, institutional directives, and redline restrictions into a preference graph over clause types, then compiles those directives into executable constraints that control decoding. It proposes measurable clause-level metrics including coverage, leakage, authority-bearing density, and constraint satisfaction, together with an auditable chain of custody that links governance inputs to observable textual outcomes. Cross-domain simulations in healthcare, securities disclosure, and administrative reporting demonstrate how governance parameters can be enforced without access to proprietary weights. The result is a verifiable clause calculus that operationalizes accountability and replaces abstract alignment narratives with testable governance artifacts connecting preference models to the operative law embedded in generated text.DOIPrimary archive: https://doi.org/10.5281/zenodo.17533075Secondary archive: https://doi.org/10.6084/m9.figshare.30589940SSRN: Pending assignment (ETA: Q4 2025)
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Artificial Intelligence/legislation & jurisprudence, Microwave technology, Anesthetists/ethics, Linguistics/legislation & jurisprudence, Machine ciphers, Machine-tools, Machine sewing, Unsupervised Machine Learning/classification, Science/history, Data science, Supervised Machine Learning/economics, Ethics Committees/ethics, Healthcare Financing, Linguistics/organization & administration, Tertiary Healthcare/standards, Technology/instrumentation, Linguistics/standards, Aerial observation (Military science)--History, Philosophy, Medical/history, Science/standards, Artificial Intelligence/ethics, Supervised Machine Learning/ethics, Linguistics/methods, Machine guns, Liability, Legal, Aquatic science libraries, Linguistics/education, Supervised Machine Learning/classification, Machine Learning/trends, FOS: Philosophy, ethics and religion, Water science, Machine Learning/history, Linguistics/legislation & jurisprudence, Embroidery, Machine, Aquatic sciences--Study and teaching (Elementary), Supervised Machine Learning, Physical science, Information Technology, Energy technology, Science/education, Humidifiers/ethics, History of philosophy, Artificial Intelligence/economics, Science, Supervised Machine Learning/trends, Unsupervised Machine Learning/history, Technology/ethics, Technology/education, Linguistics/ethics, Technology/methods, Food technology, Machine theory, Drum machine, Science/instrumentation, Applied science, Machine Learning/classification, Machine learning, Machine learning--Experiments, Agreement (legal), Philosophy, Nursing, Artificial Intelligence/trends, Philosophy, Medical, Machine Learning/legislation & jurisprudence, Anaphora (Linguistics), Tertiary Healthcare/ethnology, Ethics Committees, Clinical/ethics, Proteogenomics/ethics, Neuropathology/ethics, Environmental technology, Defamation/ethics, Machine learning--Technique, Science/trends, Materials science, Artificial Intelligence/supply & distribution, Coal technology, Military Science, Human science, Cartesian linguistics, Accounting/ethics, Airtankers (Military science)--Cost control, Machine translating, Legal text, Linguistics/statistics & numerical data, Machine Learning/ethics, Artificial intelligence, Technology, Artificial Intelligence/statistics & numerical data, Areal linguistics, Applied linguistics--Data processing, Near Miss, Healthcare, Philosophy, Dental/history, Artificial Intelligence/standards, Machine Learning, Linguistics/history, Legal Guardians, Heuristics/ethics, Legal profession, Archaisms (Linguistics), Healthcare Disparities/economics, Machine Learning/standards, Machine shops, Linguistics/trends, Science/ethics, Legal Services/education, Clean technology, Behavioural science, Machine quilting, Healthcare Disparities/classification, Artificial Intelligence/supply & distribution, Computational science, Healthcare Disparities/ethics, Philosophy of language, Machine Learning/supply & distribution, Legal regulation, Machine parts, Linguistics/classification, Linguistics/organization & administration, Philosophy, Dental, Analogy (Linguistics), Artificial Intelligence/statistics & numerical data, Legal Services/ethics, Technology Addiction, Unsupervised Machine Learning/ethics, Philosophy, Nursing/history, Classifiers (Linguistics), Legal basis, Artificial Intelligence/classification, Abortion, Legal, Legal system, Christian Science, Satellite technology, Ethics Committees, Research/ethics, Machine Learning/supply & distribution, Causative (Linguistics), Legal remedy, Machine-to-machine communications, Machine appliqué, Machine Learning/legislation & jurisprudence, Disruptive Technology, Tertiary Healthcare/history, Machine knitting, Artificial Intelligence/history, Applied linguistics--Research, Linguistics/statistics & numerical data, Artificial Intelligence, Supervised Machine Learning/standards, Science journalism, Aerial observation (Military science), Abortion, Legal/veterinary, Technology, Radiologic, Categorization (Linguistics), Legal procedure, Technology/classification, Legal Epidemiology, Data Science, Ethnic Cleansing/ethics, Linguistics/economics, Technology/trends, Linguistics, Thoracentesis/ethics, Airtankers (Military science), Machine Learning/economics, Artificial Intelligence/legislation & jurisprudence, Philosophy, Electrocorticography/ethics, Applied linguistics--Statistical methods, Machine learning--Evaluation, FOS: Languages and literature, Machine design, Cognitive Science, Linguistics/instrumentation, Abortion, Legal/economics, Legal Services, Administrative Claims, Healthcare, Unsupervised Machine Learning
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