{"id":"W122466728","doi":"10.1515/bejeap-2013-0184","title":"Income Inequality and Health: Panel Data Evidence from Canada","year":2015,"lang":"en","type":"article","venue":"The B E Journal of Economic Analysis & Policy","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research","keywords":"Decile; Gini coefficient; Economic inequality; Inequality; Theil index; Economics; Income distribution; Income inequality metrics; Econometrics; Index (typography); Robustness (evolution); Demographic economics; Panel data; Health equity; Statistics; Mathematics; Health care; Economic growth","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002905273,0.0003862134,0.0008148332,0.003203405,0.00280839,0.001976762,0.001283139,0.0005680713,0.005729307],"category_scores_gemma":[0.007845178,0.0003622959,0.001097377,0.01157406,0.0008282326,0.0005520163,0.001342867,0.001302758,0.0004149284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02011508,"about_ca_system_score_gemma":0.03218029,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996901,"about_ca_topic_score_gemma":0.9971765,"domain_scores_codex":[0.9982936,0.0003038869,0.0000970468,0.000204848,0.0005931356,0.0005075521],"domain_scores_gemma":[0.9890602,0.001760534,0.001964023,0.0007160417,0.005294597,0.001204585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000228242,0.00007718158,0.9598244,0.0002156597,0.0008321699,0.0001845954,0.0008347615,0.001456342,0.00006115671,0.002132674,0.02168931,0.01246352],"study_design_scores_gemma":[0.00003700158,0.00001792626,0.9882903,0.0003406143,0.0004086434,0.00003921262,0.001169121,0.001275919,0.00006834889,0.0004024235,0.007915405,0.00003513274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8324669,0.01792799,0.001039587,0.008804412,0.0001913747,0.0001599429,0.1140218,0.00005471469,0.02533338],"genre_scores_gemma":[0.9642735,0.006108156,0.000581931,0.0007211148,0.00005126783,0.00004052986,0.02590755,0.00001796198,0.002297947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02011508,"threshold_uncertainty_score":0.1459458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3322552679594217,"score_gpt":0.4546214424758462,"score_spread":0.1223661745164246,"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."}}