{"id":"W3035969311","doi":"10.5539/ass.v16n7p46","title":"How Can We Account for Persisting Educational Inequalities in Rural China","year":2020,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Underdevelopment; China; Economic growth; Government (linguistics); Inequality; Sociology; Higher education; Political science; Economics","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":[0.001854492,0.0005836681,0.0008432942,0.002784888,0.002372528,0.003465457,0.001196767,0.0009918304,0.00343575],"category_scores_gemma":[0.005728247,0.0001965972,0.0007851495,0.002912138,0.002814522,0.005185906,0.002859804,0.001741542,0.0002017159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005207841,"about_ca_system_score_gemma":0.00957999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1548779,"about_ca_topic_score_gemma":0.1288657,"domain_scores_codex":[0.9991407,0.0001964963,0.00004737897,0.0001442087,0.0001271371,0.0003440898],"domain_scores_gemma":[0.9982894,0.0004748967,0.000471973,0.0001816166,0.0002648061,0.0003173407],"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":[0.00004982247,0.000123857,0.3912739,0.0005595149,0.0004738577,0.0007875561,0.01560898,0.009393339,0.0003058643,0.4697408,0.01654175,0.0951407],"study_design_scores_gemma":[0.00003781387,0.0001266772,0.3875958,0.001203198,0.000479784,0.0002305463,0.02848084,0.02969378,0.000311786,0.4719105,0.07978082,0.0001484863],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6330079,0.02333106,0.02787844,0.2368047,0.002146589,0.0002656085,0.003016219,0.0002935158,0.07325599],"genre_scores_gemma":[0.9888647,0.003601837,0.002603588,0.00189301,0.0002720253,0.00009046766,0.0002410875,0.00001414175,0.002419089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1548779,"threshold_uncertainty_score":0.3079528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02947535614153322,"score_gpt":0.3066333925986547,"score_spread":0.2771580364571215,"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."}}