{"id":"W1576183699","doi":"10.1080/10920277.2004.10596169","title":"Social Transfers And Income Inequality In Old Age","year":2004,"lang":"en","type":"article","venue":"North American Actuarial Journal","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Waterloo","funders":"","keywords":"Economic inequality; Pension; Economics; Income distribution; Inequality; Demographic economics; Income inequality metrics; Welfare; Transfer payment; Government (linguistics); Household income; Distribution (mathematics); Labour economics; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005681945,0.0001303674,0.00016396,0.001543277,0.0006061638,0.0005752545,0.0001719873,0.0002148189,0.002580558],"category_scores_gemma":[0.002986345,0.00005503703,0.0001610457,0.001415923,0.0006170369,0.0007240184,0.000985104,0.0003828369,0.0001704755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005117106,"about_ca_system_score_gemma":0.0001890614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006110389,"about_ca_topic_score_gemma":0.01001737,"domain_scores_codex":[0.9996521,0.0001205633,0.00001578603,0.00002641886,0.00005351705,0.0001315811],"domain_scores_gemma":[0.9987587,0.0003416791,0.0005211498,0.00004426785,0.0001268425,0.0002073976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009117057,0.0001176993,0.9768434,0.00002017942,0.0000721211,0.0001377428,0.001887378,0.000675042,0.00008545844,0.006504632,0.0004862419,0.01307899],"study_design_scores_gemma":[0.00000229508,0.00002895571,0.9951037,0.00001693696,0.00001014869,0.00005393536,0.001002718,0.0004224782,0.00003161409,0.002445247,0.0008785306,0.000003469697],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945235,0.0006841092,0.0001614817,0.0003370224,0.000009302899,0.000002817301,0.0001395818,0.000002032517,0.004140223],"genre_scores_gemma":[0.99949,0.0001462163,0.00002149611,0.00001341734,0.00001262646,0.000001657445,0.00005491459,5.186823e-7,0.0002590937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006110389,"threshold_uncertainty_score":0.01214969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03176804629383927,"score_gpt":0.3248204451275984,"score_spread":0.2930523988337591,"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."}}