{"id":"W1904878326","doi":"10.25071/1874-6322.17482","title":"Macro/Micro Modelling and Gini Multi-Decomposition: An Application to the Philippines","year":2010,"lang":"en","type":"article","venue":"Journal of Income Distribution","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Economics; Macro; Partial equilibrium; Welfare; General equilibrium theory; Decomposition; Econometrics; Inequality; Gini coefficient; Income distribution; Yield (engineering); Distribution (mathematics); Macroeconomics; Applied general equilibrium; Economic inequality; Mathematics; Computer science; Thermodynamics","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":[0.001813962,0.00008114652,0.000135613,0.00003909799,0.0007034199,0.0001234664,0.0002473916,0.00008967314,0.00002317124],"category_scores_gemma":[0.000114756,0.00005901846,0.00006031142,0.0001876921,0.0001107474,0.0004260952,0.00002810965,0.0002741608,0.000008311292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009685699,"about_ca_system_score_gemma":0.00007161506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004291451,"about_ca_topic_score_gemma":0.0006987395,"domain_scores_codex":[0.9989424,0.0001416148,0.0003522099,0.0001101533,0.0002847164,0.0001689281],"domain_scores_gemma":[0.9989508,0.00006210443,0.0002618233,0.0001440285,0.000428952,0.0001522874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001284269,0.002913616,0.2203891,0.0002209514,0.0002613353,0.00002659306,0.06607598,0.01754903,0.1393567,0.4124211,0.005388229,0.1341131],"study_design_scores_gemma":[0.003681771,0.0009269855,0.3999544,0.0001975377,0.0002167788,0.0003013951,0.01116398,0.06926145,0.009742232,0.03707876,0.4660919,0.001382839],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7404156,0.00004646416,0.2549463,0.003811576,0.000471731,0.0001405849,0.00004575718,0.0000128958,0.0001090404],"genre_scores_gemma":[0.9972316,0.00006256948,0.001488297,0.0001814149,0.0009733675,0.000004419949,0.00003003833,0.000004619302,0.00002364901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4607037,"threshold_uncertainty_score":0.5410208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02568192654322999,"score_gpt":0.3415037730087026,"score_spread":0.3158218464654726,"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."}}