{"id":"W2136058446","doi":"10.1007/s11151-008-9178-8","title":"Incentive Complementarity in China’s Rural Enterprises","year":2008,"lang":"en","type":"article","venue":"Review of Industrial Organization","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture Food and Rural Development; University of Alberta","funders":"Giannini Foundation of Agricultural Economics","keywords":"Complementarity (molecular biology); Incentive; Economics; Panel data; China; Robustness (evolution); Instrumental variable; Microeconomics; Econometrics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004103596,0.00007037542,0.0002520714,0.00002654498,0.0001556772,0.000008023176,0.000157404,0.00006552144,0.000823184],"category_scores_gemma":[0.0006000764,0.00006313639,0.00004072673,0.0004280954,0.000111644,0.0002547064,0.00003896629,0.0001103144,0.00001534921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003542068,"about_ca_system_score_gemma":0.0002975549,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01027213,"about_ca_topic_score_gemma":0.0007425802,"domain_scores_codex":[0.9990839,0.0001218163,0.0003852503,0.00009681095,0.000183539,0.0001287339],"domain_scores_gemma":[0.999465,0.00002519898,0.0003028637,0.00008760303,0.00008188475,0.00003746411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004922142,0.00007942504,0.9790938,0.0001112478,0.000010207,0.000001335847,0.005192022,0.000001718282,0.000009280742,0.003511952,0.007180545,0.00480352],"study_design_scores_gemma":[0.00243325,0.00009388763,0.8590806,0.007125565,0.00004241342,0.000003779011,0.001891947,0.000003976756,0.0005968696,0.0005530768,0.1277312,0.0004434077],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907981,0.002709142,0.00004246269,0.003015023,0.000350889,0.0005841716,0.00002162083,0.00001806415,0.002460537],"genre_scores_gemma":[0.930711,0.06867466,0.00002503988,0.0002491404,0.0002005681,0.00000230094,0.0000399038,0.00000623075,0.00009109964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1205507,"threshold_uncertainty_score":0.9963186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03151906081218116,"score_gpt":0.2956991237404883,"score_spread":0.2641800629283071,"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."}}