{"id":"W1990736050","doi":"10.1016/j.jpubeco.2010.08.003","title":"Welfare rankings from multivariate data, a nonparametric approach","year":2010,"lang":"en","type":"article","venue":"Journal of Public Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Economic and Social Research Council","keywords":"Social planner; Nonparametric statistics; Data envelopment analysis; Weighting; Economics; Welfare; Econometrics; Multivariate statistics; Incentive; Social Welfare; Measure (data warehouse); Public economics; Computer science; Microeconomics; Mathematics; Statistics; Data mining","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":[0.02584195,0.0009713374,0.002938388,0.003756697,0.00103583,0.004022652,0.00219427,0.001238553,0.004087363],"category_scores_gemma":[0.0936664,0.000978841,0.002026166,0.003668835,0.003090202,0.004863405,0.002862133,0.003832862,0.0004188193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407944,"about_ca_system_score_gemma":0.001911999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0037077,"about_ca_topic_score_gemma":0.004980735,"domain_scores_codex":[0.9752449,0.02106038,0.0005076475,0.001137134,0.001475442,0.0005744768],"domain_scores_gemma":[0.9071608,0.0773667,0.003428109,0.008515998,0.002779234,0.0007491388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006921893,0.0005600729,0.02047925,0.0005731663,0.001159246,0.0002740104,0.0006719263,0.2501862,0.0008540918,0.4178188,0.00999031,0.2967407],"study_design_scores_gemma":[0.00006478136,0.0001561714,0.007018012,0.00007680648,0.00008852748,0.00008092522,0.000238225,0.6224893,0.0002907231,0.367553,0.001866584,0.00007691804],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04718539,0.0004240038,0.9479384,0.0009037103,0.00005695041,0.0001245226,0.0009154528,0.0002088383,0.00224271],"genre_scores_gemma":[0.7818587,0.0006011036,0.2112841,0.0002300677,0.0003608846,0.0006390323,0.001950366,0.0001468347,0.002928894],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02584195,"threshold_uncertainty_score":0.136667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08000601884022815,"score_gpt":0.31664299404618,"score_spread":0.2366369752059519,"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."}}