{"id":"W3150274753","doi":"10.1111/cjag.12273","title":"How does land titling affect credit demand, supply, access, and rationing: Evidence from China","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Land Rights and Reforms","field":"Agricultural and Biological Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credit rationing; Collateral; China; Land titling; Rationing; Economics; Business; Land reform; Economic growth; Agriculture; Finance; Land tenure; Interest rate; Geography","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":[0.001373508,0.0002234406,0.0003758164,0.001143694,0.0006526777,0.0007385517,0.0005489604,0.0003441973,0.002501549],"category_scores_gemma":[0.003609517,0.000190703,0.0005917554,0.002475887,0.001528295,0.0005821988,0.0006772943,0.0004454103,0.0001419608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001699963,"about_ca_system_score_gemma":0.001824169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1987239,"about_ca_topic_score_gemma":0.2283778,"domain_scores_codex":[0.9991549,0.0002726528,0.00006846857,0.000154135,0.0001609973,0.0001887784],"domain_scores_gemma":[0.9943616,0.00130749,0.002700466,0.0003722515,0.0006091838,0.0006489034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005341758,0.00006439212,0.9956372,0.00002734573,0.00008867752,0.0001043429,0.0004547493,0.0001963019,0.0001305655,0.0002694966,0.0001439434,0.002829578],"study_design_scores_gemma":[0.000007552691,0.00003787285,0.9986298,0.000008485647,0.00003430296,0.00001238042,0.0004664303,0.0003614662,0.00006313661,0.00007544308,0.0002988146,0.000004356497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987483,0.0001979688,0.00004363807,0.0001762109,0.000002314378,0.00000648199,0.0001660633,0.000001259651,0.000657748],"genre_scores_gemma":[0.9995396,0.0001112428,0.00002273993,0.00003597501,0.000003218142,0.000002547182,0.0001399696,4.973526e-7,0.000144169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1987239,"threshold_uncertainty_score":0.3951344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02306073900377725,"score_gpt":0.1749528688112853,"score_spread":0.1518921298075081,"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."}}