{"id":"W2890399122","doi":"10.3386/w18669","title":"Optimal Financial Knowledge and Wealth Inequality","year":2013,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Network for Studies on Pensions, Aging and Retirement; U.S. Social Security Administration; University of Pennsylvania; RAND Corporation","keywords":"Inequality; Economics; Finance; Business; Financial economics; 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":[0.0006692223,0.0001720625,0.0003263888,0.00037835,0.0003009679,0.001098456,0.0002817065,0.0006755537,0.004446784],"category_scores_gemma":[0.006465888,0.0001923514,0.0002258485,0.0002857361,0.0005323729,0.001052679,0.0008440498,0.0004616597,0.0001807901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104694,"about_ca_system_score_gemma":0.0005449379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006630093,"about_ca_topic_score_gemma":0.005160125,"domain_scores_codex":[0.9998066,0.00005766593,0.000006254203,0.00002480123,0.00001623793,0.00008854753],"domain_scores_gemma":[0.9983833,0.0008825707,0.0003569801,0.0001040257,0.00007589614,0.0001973052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0006023653,0.0005882956,0.1968663,0.00006959159,0.0001184425,0.0005988895,0.0004196656,0.5976421,0.001249784,0.1611544,0.00350518,0.03718492],"study_design_scores_gemma":[0.0001029202,0.0002399943,0.1181276,0.00006867163,0.00005532527,0.0002234775,0.0006235774,0.7093157,0.0006808809,0.1686018,0.001920798,0.00003929642],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818414,0.0001400889,0.006227173,0.0007371405,0.000007209352,0.00001493073,0.0003192173,0.00001758755,0.01069506],"genre_scores_gemma":[0.998961,0.00004245425,0.0003130218,0.00002363061,0.000002166642,0.000003947679,0.0000554224,0.00000148084,0.0005968754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006630093,"threshold_uncertainty_score":0.01487595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2709341496374954,"score_gpt":0.4762432397519614,"score_spread":0.205309090114466,"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."}}