{"id":"W3125588622","doi":"10.2139/ssrn.3417181","title":"China’s Industrial Policy: an Empirical Evaluation","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Economic Zones and Regional Development","field":"Economics, Econometrics and Finance","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"China; Industrial policy; Empirical research; Business; Political science; International trade; Mathematics; Statistics; Law","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":[0.005017566,0.0004278125,0.0007065793,0.003035696,0.001068435,0.002402924,0.0009992383,0.0009437258,0.005767329],"category_scores_gemma":[0.009608899,0.0002135635,0.0006183119,0.004599582,0.001504676,0.00137511,0.0010625,0.0008322218,0.0004038206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007397382,"about_ca_system_score_gemma":0.008036646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1167969,"about_ca_topic_score_gemma":0.1107828,"domain_scores_codex":[0.9980369,0.0007170982,0.0001059717,0.0001908082,0.0004796062,0.0004695678],"domain_scores_gemma":[0.9898993,0.004735378,0.001994319,0.000520543,0.001911819,0.0009385969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001597645,0.0008922176,0.9125876,0.0003759137,0.0005967372,0.0006560673,0.001312961,0.01946123,0.0005277193,0.02844486,0.005590572,0.02795646],"study_design_scores_gemma":[0.0002880802,0.0008108848,0.9627849,0.00008907242,0.0004796965,0.00006817406,0.003343546,0.01949923,0.001038453,0.002608517,0.008955511,0.00003404946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856234,0.000744019,0.0001617541,0.0008977356,0.0000176253,0.00003850752,0.0006581213,0.00001451273,0.01184438],"genre_scores_gemma":[0.9979382,0.0002812993,0.00005125924,0.00006786409,0.00002704291,0.000014903,0.0004747138,0.000003171111,0.001141531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1167969,"threshold_uncertainty_score":0.2322342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05636124913441358,"score_gpt":0.2820139393070483,"score_spread":0.2256526901726347,"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."}}