{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007525612,0.0003206434,0.0007790372,0.001736174,0.00029669,0.0002847974,0.000525605,0.000421254,0.001779538],"category_scores_gemma":[0.003129605,0.0003229871,0.0002187972,0.00050931,0.00029746,0.0008704849,0.0007139883,0.0007047145,0.001206314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008668826,"about_ca_system_score_gemma":0.002778856,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01218105,"about_ca_topic_score_gemma":0.001142255,"domain_scores_codex":[0.9960347,0.00007559991,0.001101356,0.0007413465,0.001523307,0.0005236608],"domain_scores_gemma":[0.9936424,0.0004303496,0.0007378937,0.0003582725,0.004793403,0.00003761947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008709118,0.0002243013,0.08971179,0.001753877,0.00007205169,0.00000451006,0.00004834877,0.00009394959,0.00003839279,0.3742594,0.5306235,0.003082811],"study_design_scores_gemma":[0.00123325,0.00007966381,0.1655334,0.0005970373,0.0001380497,0.000006321866,0.00004577311,0.009180085,0.00003697649,0.1731093,0.6489761,0.001063967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3741156,0.001923752,0.000003066877,0.0005186544,0.001026441,0.001113695,0.00007564866,0.00004876798,0.6211744],"genre_scores_gemma":[0.975962,0.0009077191,0.0002492085,0.0001064273,0.00800107,0.0001378605,0.001354839,0.00007312262,0.01320778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6079667,"threshold_uncertainty_score":0.9999222,"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."}}