Generative Relations in Legal Judgment: Evidence, Historical Trajectories, and Norm-Relevant Similarity
Legal comparison depends on the relationship between general norms and particular histories. Identical words or recorded outcomes can arise through different dependencies, while different expressions can perform comparable functions within a relationship. This discussion paper develops an account of norm-relevant similarity through the reconstruction of generative relations: the processes through which resources, expectations, interpretations, and available actions become connected over time. It distinguishes evidentiary support, causal reconstruction, normative characterization, and institutional authority. A fictional reimbursement rule and a controlled family of cases make the comparison criteria explicit without asserting current doctrine. A relational-field formulation then separates observation from retained history and counterfactual response, while requiring role-preserving mappings, justified time scales, and independently defended normative constraints. Completed synthetic calculations show how shared trajectories, attractors, action values, or boundary amplitudes can coexist with differences in dynamics or interior histories. These results supply mathematical examples of limited inference; they provide no empirical validation of legal decision-making. The paper grounds reason-giving, contestation, and proportionate correction in stated commitments to equal standing, protection against material error, and accountable public authority. Its contribution is an inspectable connection between historical reconstruction and issue-specific comparison, with established legal analogy and case-based reasoning as substantive baselines.
Authors
- Wanhong HUANG
Institutions
- Creative Commons (US)
Publication Details
- Journal
- Knowledge Commons (Lakehead University)
- Published
- 2026-09-11
- DOI
- https://doi.org/10.17613/ppeyf-tz833
- Primary Topic
- Judicial and Constitutional Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00