{"id":"W7117300867","doi":"10.2139/ssrn.5968175","title":"Before Doctrine and Data Institutional Ontology as a Pre-Analytical Discipline in Law","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Normative; Discretion; Harm; Doctrine; Ontology; Rendering (computer graphics); Jurisprudence; Ambiguity","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02923453,0.0006129356,0.001527691,0.004642503,0.008991613,0.02193522,0.002559928,0.007902015,0.007279533],"category_scores_gemma":[0.03783798,0.001285609,0.001741182,0.004660796,0.08337367,0.02841447,0.00832395,0.02085944,0.001566549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01187843,"about_ca_system_score_gemma":0.01470851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006851291,"about_ca_topic_score_gemma":0.005147532,"domain_scores_codex":[0.9782572,0.01152297,0.002163282,0.003305743,0.003601869,0.00114904],"domain_scores_gemma":[0.9459085,0.03149442,0.002394235,0.01321803,0.005484296,0.001500539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001016868,0.000001774094,0.0000163849,0.000003697155,0.000001040257,0.000002814427,0.0002932422,0.00002938111,0.000008853034,0.9988993,0.0002455824,0.0004968329],"study_design_scores_gemma":[0.000003401333,0.000002811713,0.00002430166,0.00002844419,0.000002519901,0.000009710653,0.0001994652,0.0002738608,0.00009132764,0.9897238,0.00963588,0.000004501713],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0241265,0.003814297,0.5657956,0.09399779,0.00217022,0.0002080869,0.0005480372,0.0004597076,0.3088799],"genre_scores_gemma":[0.8613846,0.001700194,0.09453211,0.007821811,0.00185927,0.0004729297,0.0003308227,0.0006822314,0.03121604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02923453,"threshold_uncertainty_score":0.1546088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03353159323447522,"score_gpt":0.3702159174883801,"score_spread":0.3366843242539048,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}