{"id":"W3036445944","doi":"10.5430/rwe.v11n3p36","title":"The Impact of New Rural Cooperative Insurance on Migrant Workers' Consumption: Empirical Analysis Based on China Migrants Dynamic Survey","year":2020,"lang":"en","type":"article","venue":"Research in World Economy","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shantou University","keywords":"Consumption (sociology); Propensity score matching; Migrant workers; Per capita; China; Demographic economics; Medical insurance; Business; Per capita income; Socioeconomics; Matching (statistics); Commission; Economics; Economic growth; Environmental health; Actuarial science; Geography; Demography; Population; Medicine; Sociology","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":[0.00157747,0.0002516641,0.0003555539,0.0009242575,0.0003918675,0.0006469773,0.000459802,0.0004408493,0.001709374],"category_scores_gemma":[0.003285774,0.0001765977,0.001145915,0.001278226,0.0003701122,0.0004938283,0.0006232994,0.0006280156,0.0001493278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008226721,"about_ca_system_score_gemma":0.0008512739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04542995,"about_ca_topic_score_gemma":0.04868271,"domain_scores_codex":[0.99923,0.0002862322,0.00005436605,0.0001151366,0.000113753,0.00020059],"domain_scores_gemma":[0.997617,0.0006894485,0.0009793073,0.0001852452,0.0001956624,0.0003333044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005817075,0.00005553419,0.9963007,0.0000119315,0.0001048703,0.0001286096,0.0002040886,0.0005619648,0.00007324824,0.0001677424,0.0001664289,0.002166778],"study_design_scores_gemma":[0.000007859155,0.00005231765,0.994769,0.000009583047,0.0001098731,0.00004051661,0.0006401152,0.003931312,0.00006759168,0.00007494436,0.000290938,0.000005848616],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993387,0.000120654,0.0000936439,0.0001360576,0.000002824079,0.000005212115,0.0001330929,0.000001852824,0.0001680231],"genre_scores_gemma":[0.9992691,0.0001092733,0.00005858297,0.00002962943,0.000008832332,0.000004957685,0.0002429714,9.625677e-7,0.0002757226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04542995,"threshold_uncertainty_score":0.09033102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.184007530880833,"score_gpt":0.4160306602111378,"score_spread":0.2320231293303048,"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."}}