{"id":"W1975219866","doi":"10.2139/ssrn.2403826","title":"Income Growth, Inequality and Poverty Reduction: A Case Study of Eight Provinces in China","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Poverty reduction; China; Inequality; Poverty; Development economics; Economic inequality; Economics; Socioeconomics; Demographic economics; Geography; Economic growth; Mathematics","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":[0.000622757,0.0004125045,0.0004849905,0.001338699,0.00555922,0.001323575,0.001224563,0.0008956971,0.001417156],"category_scores_gemma":[0.001081557,0.0003209668,0.0004954859,0.003987677,0.002091561,0.0006591027,0.001517006,0.000747271,0.00007725108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01160207,"about_ca_system_score_gemma":0.0107793,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7936366,"about_ca_topic_score_gemma":0.8735768,"domain_scores_codex":[0.9991817,0.0001702579,0.00002083835,0.000054589,0.00007687396,0.0004958242],"domain_scores_gemma":[0.9993317,0.0001738454,0.0001158544,0.00004423415,0.0001221388,0.0002122079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003909685,0.0009197602,0.9004412,0.0001876553,0.0001620301,0.01807754,0.04238324,0.006295451,0.001136614,0.005598022,0.001493735,0.02291365],"study_design_scores_gemma":[0.0001040175,0.0004145654,0.7514843,0.00009497404,0.0001843682,0.001489909,0.2276282,0.01109315,0.0008092425,0.001050442,0.005558393,0.00008838365],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990496,0.00005546333,0.00004571504,0.00008000699,0.000001139653,0.00001363154,0.00003768416,0.000001854099,0.0007147777],"genre_scores_gemma":[0.9991943,0.00009476858,0.0001270549,0.0000129999,0.000001121845,0.000008346377,0.00004182277,0.000001015435,0.0005185981],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7936366,"threshold_uncertainty_score":0.4151574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135375095287893,"score_gpt":0.2929147471837954,"score_spread":0.2793772376550061,"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."}}