Validating a Computational Legal Corpus: Doctrinal Foundations for Quantitative Research on Hungary’s Deputy Ombudsman for Future Generations (2012–2026)

Abstract

This article examines the Hungarian Deputy Commissioner for Fundamental Rights responsible for the interests of future generations, using it as a case study to test how legal-doctrinal validation should ground computational governance research on environmental institutions. The public trust doctrine and the non-derogation principle that anchor Hungarian environmental constitutionalism have already been established in prior scholarship; this article’s contribution is threefold and empirical rather than purely descriptive. First, it reconstructs, through primary-source verification against a full-text corpus of 6,484 Constitutional Court decisions, how these doctrines were extended across three previously untraced steps—from forests to water resources, to climate mitigation targets—and surfaces three substantively relevant decisions absent from prior indexes. Second, it builds and reports a multi-layered digital research corpus (a retrieval-augmented report corpus, an AI-assisted case database, and the full-text decision corpus) and documents specific, reproducible failure modes of AI-assisted legal corpus construction—context bleeding, index-page label contamination, and full-text boundary defects—that carry methodological relevance beyond this case study. Third, it confronts an effectiveness tension the doctrinal narrative alone would obscure: the institution’s most sustained campaign, a nine-round legislative cycle on well-permitting, concluded in materially unconstrained deregulation despite five years of doctrinal consolidation, a result situated here within Beckman and Uggla’s, Tattay’s, and Gardiner’s theoretical accounts of the structural limits of future-generations representation. The article concludes by specifying legal-validation preconditions for a future quantitative Sustainability Ombudsman Index, which this study does not itself construct.