{"id":"W4318476387","doi":"10.3390/su15032379","title":"Corporate Environmental Compliance in China: From Social Responsibility to Soft Law","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Regulation and Compliance Studies","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"National Social Science Fund of China","keywords":"Compliance (psychology); Environmental compliance; Business; Corporate social responsibility; Environmental law; Environmental management system; Social responsibility; China; Corporate governance; Public relations; Environmental resource management; Political science; Law; Economics; Ecology; Psychology","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":[0.002472311,0.0002171229,0.0002710086,0.001993724,0.004060782,0.002653549,0.0006364314,0.0007928945,0.002057639],"category_scores_gemma":[0.002452042,0.0001837315,0.0002756308,0.002852792,0.004297543,0.002002278,0.002429243,0.000900923,0.00005878911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0127987,"about_ca_system_score_gemma":0.01875038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1229242,"about_ca_topic_score_gemma":0.1270307,"domain_scores_codex":[0.9974653,0.000471915,0.0001662858,0.0003181479,0.0009056408,0.0006728592],"domain_scores_gemma":[0.9977646,0.000572517,0.0007196651,0.0001029596,0.0004574509,0.0003827221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001190228,0.0004519142,0.5634834,0.0005057635,0.00008566558,0.003567691,0.08373378,0.002516654,0.001486535,0.2153425,0.00513601,0.1235711],"study_design_scores_gemma":[0.00003098512,0.000167071,0.8972961,0.0003328761,0.00006621371,0.0003466338,0.03934411,0.005488912,0.0007923682,0.02315747,0.03289082,0.00008646213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729829,0.00114519,0.0005099348,0.005038159,0.00002892162,0.00003690653,0.00002639616,0.000009971697,0.02022168],"genre_scores_gemma":[0.9981247,0.0003388793,0.00006976403,0.0001721753,0.000009186366,0.000007011035,0.00001309117,0.000001099621,0.001264276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1229242,"threshold_uncertainty_score":0.2444174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03969731278593044,"score_gpt":0.2758394760978486,"score_spread":0.2361421633119181,"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."}}