{"id":"W4416288077","doi":"10.2139/ssrn.5753682","title":"State Ownership and Corporate Compliance: Evidence from China's Cybersecurity Law","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"State (computer science); Constraint (computer-aided design); Enforcement; Compliance (psychology); Politics; State ownership; Law enforcement; Government (linguistics); Forbearance","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":[0.003158956,0.0001888214,0.0004185833,0.002570615,0.002114222,0.002567132,0.0008635749,0.001201036,0.005269558],"category_scores_gemma":[0.01055935,0.0002073004,0.0004079941,0.004817997,0.004307352,0.001567542,0.001919883,0.001248347,0.0002209984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004240868,"about_ca_system_score_gemma":0.007751806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1189818,"about_ca_topic_score_gemma":0.1536036,"domain_scores_codex":[0.9971934,0.0005216246,0.000199465,0.000286501,0.0008162935,0.0009827322],"domain_scores_gemma":[0.9724689,0.008083282,0.01237773,0.001845639,0.003281523,0.001942983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001762799,0.0002870949,0.9702321,0.00004661821,0.0001132269,0.0003446054,0.002356187,0.000729604,0.0002842411,0.01317965,0.001497515,0.01075284],"study_design_scores_gemma":[0.00004523111,0.0001102527,0.9919264,0.00002617412,0.0001052578,0.00003706189,0.002387458,0.001282259,0.0002919571,0.001981599,0.001789354,0.00001707995],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936329,0.0001416599,0.00008499233,0.0009527105,0.00000632143,0.00001467906,0.0001298399,0.00000551631,0.005031367],"genre_scores_gemma":[0.9994572,0.00005822663,0.00001167583,0.00007579916,0.000005769799,0.00000373209,0.00005872126,6.534432e-7,0.0003281878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1189818,"threshold_uncertainty_score":0.2365784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04278790145638319,"score_gpt":0.3011209827696549,"score_spread":0.2583330813132717,"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."}}