{"id":"W4410798068","doi":"10.54517/jelp3486","title":"Soft law governance of enterprise data compliance in the context of environmental protection","year":2025,"lang":"en","type":"article","venue":"Journal of Environmental Law & Policy","topic":"Digital Transformation in Law","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Compliance (psychology); Corporate governance; Context (archaeology); Business; Soft law; Accounting; Data Protection Act 1998; Environmental compliance; Environmental law; Enterprise data management; Law; Public administration; Law and economics; Political science; Public relations; Process management; Sociology; Psychology; Geography; Finance; Enterprise software; Social psychology; International law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03122107,0.0002911285,0.0005256091,0.002996387,0.005515736,0.01965767,0.002121242,0.004127264,0.005802818],"category_scores_gemma":[0.06205632,0.0005979317,0.0006626841,0.004056073,0.01452805,0.01251405,0.01064656,0.004413594,0.0008919002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009043382,"about_ca_system_score_gemma":0.02332017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01401101,"about_ca_topic_score_gemma":0.01095469,"domain_scores_codex":[0.969889,0.01436341,0.002303844,0.004659266,0.00555393,0.003230554],"domain_scores_gemma":[0.9340535,0.03457027,0.010666,0.008941303,0.007567839,0.004200976],"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":[0.00002642772,0.00010543,0.01550576,0.0001130489,0.00003534609,0.0007375236,0.01058819,0.003354513,0.0007328314,0.9333307,0.004999378,0.03047084],"study_design_scores_gemma":[0.00004387479,0.00009441494,0.02332602,0.0006833052,0.00006293962,0.0004999546,0.0186525,0.02715176,0.001778454,0.7889522,0.1386266,0.0001277709],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3283328,0.001811969,0.164687,0.06426693,0.0003178279,0.0009577364,0.0004152536,0.0006970894,0.4385135],"genre_scores_gemma":[0.9815156,0.0002808946,0.007397071,0.001021245,0.00008442379,0.0001411165,0.00008760545,0.00005848931,0.009413472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03122107,"threshold_uncertainty_score":0.1651148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0361624626954352,"score_gpt":0.2461156029807996,"score_spread":0.2099531402853644,"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."}}