{"id":"W4322734863","doi":"10.1287/mnsc.2023.4711","title":"Enforcement Waves and Spillovers","year":2023,"lang":"en","type":"article","venue":"Management Science","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Misrepresentation; Enforcement; Business; Misconduct; Quarter (Canadian coin); Economics; Finance; Monetary economics; Actuarial science; Political science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004731283,0.0002721582,0.0005679129,0.002502463,0.001617278,0.003958954,0.0008243159,0.001156699,0.02930328],"category_scores_gemma":[0.04106404,0.0004476208,0.0006378417,0.002142266,0.001605398,0.003177858,0.005192804,0.002433386,0.001215547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001693704,"about_ca_system_score_gemma":0.001359025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008793714,"about_ca_topic_score_gemma":0.006455796,"domain_scores_codex":[0.9958023,0.0009348025,0.0002909934,0.0008197329,0.001369309,0.0007828954],"domain_scores_gemma":[0.9448153,0.02292356,0.02068277,0.005753857,0.003625308,0.002199151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006939098,0.001300281,0.7422374,0.0003966204,0.0004660023,0.000949187,0.007468021,0.004294567,0.00258639,0.06332737,0.01607591,0.1602043],"study_design_scores_gemma":[0.00006442406,0.0002887231,0.9494123,0.0002449499,0.0002440962,0.0003191457,0.004205568,0.003589125,0.001143941,0.02238165,0.01803215,0.00007382418],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8755506,0.001668694,0.01248763,0.00481665,0.0001891703,0.0003234238,0.001737868,0.0002158671,0.1030101],"genre_scores_gemma":[0.9918705,0.0003756225,0.0006527203,0.00050491,0.0001143102,0.00006376316,0.0003506041,0.00002399324,0.006043554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02930328,"threshold_uncertainty_score":0.09802926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01071301615702134,"score_gpt":0.2192707916338755,"score_spread":0.2085577754768542,"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."}}