{"id":"W3158348143","doi":"10.1111/gove.12594","title":"Institutional proximity and judicial corruption: A spatial approach","year":2021,"lang":"en","type":"article","venue":"Governance","topic":"Judicial and Constitutional Studies","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Operationalization; Politics; Language change; Context (archaeology); Political science; China; Complement (music); Law and economics; Law; Sociology; Geography","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":[0.001457201,0.0003072693,0.0004272415,0.004220868,0.002442092,0.00504194,0.001027945,0.0009564606,0.008756817],"category_scores_gemma":[0.008212711,0.000280451,0.0006489439,0.00395948,0.01019664,0.005533908,0.006416881,0.0007322497,0.0004031098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003617075,"about_ca_system_score_gemma":0.002149817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007998498,"about_ca_topic_score_gemma":0.006627659,"domain_scores_codex":[0.9975726,0.001434768,0.0001011964,0.0003268949,0.0003280874,0.0002364498],"domain_scores_gemma":[0.995371,0.001782283,0.001438807,0.0005029617,0.000598102,0.0003067218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003201167,0.00004532444,0.04306171,0.0001354621,0.0000353832,0.0003767307,0.005732798,0.00689378,0.0002093459,0.9278719,0.0006734763,0.01493196],"study_design_scores_gemma":[0.00006490976,0.0001952802,0.1063217,0.0005615075,0.0002339705,0.001115331,0.0457393,0.04684573,0.0007272513,0.7596694,0.03844283,0.00008285703],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6403578,0.003420792,0.1326472,0.01004992,0.0001375274,0.0001738995,0.0004314519,0.000119269,0.2126622],"genre_scores_gemma":[0.9974188,0.0002658271,0.001549405,0.00003712455,0.00001744217,0.00001582703,0.00002115364,0.000003879565,0.0006704425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008756817,"threshold_uncertainty_score":0.02929449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0272471462032246,"score_gpt":0.2656881602014818,"score_spread":0.2384410139982572,"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."}}