{"id":"W3033231924","doi":"10.1111/joca.12304","title":"Gender differences in financial knowledge, attitudes, and behaviors: Accounting for socioeconomic disparities and psychological traits","year":2020,"lang":"en","type":"article","venue":"Journal of Consumer Affairs","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Financial literacy; Socioeconomic status; Psychology; Survey data collection; Population; Contrast (vision); Gender gap; Demography; Demographic economics; Social psychology; Finance; Economics; Sociology","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":[0.001990793,0.0003296687,0.0003194934,0.001008748,0.0009824206,0.0008773015,0.0006401697,0.0003910357,0.003810175],"category_scores_gemma":[0.007307996,0.0001472698,0.000928043,0.001191593,0.0006189971,0.0004711544,0.0007360377,0.0006115244,0.0001990645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00121035,"about_ca_system_score_gemma":0.003094498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3864525,"about_ca_topic_score_gemma":0.4462951,"domain_scores_codex":[0.9991413,0.0001886641,0.00005030613,0.0001434266,0.0002010621,0.0002752806],"domain_scores_gemma":[0.9974999,0.0008145359,0.0006821973,0.0003018949,0.0003076494,0.0003938155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003667438,0.00002545541,0.9965141,0.000008769326,0.00007133462,0.00002910208,0.00025306,0.0001077749,0.0000625864,0.0002757742,0.0001870503,0.002428273],"study_design_scores_gemma":[0.000002275053,0.00002586216,0.9975274,0.00002283775,0.00005025242,0.00003372778,0.0007986312,0.0007509866,0.00008823739,0.000277549,0.0004178003,0.000004501787],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996174,0.0002650764,0.0004932497,0.0002315964,0.00001462738,0.00002016173,0.001014269,0.000005552884,0.001781406],"genre_scores_gemma":[0.9991043,0.00004158409,0.0002156843,0.00002037796,0.000003199094,0.000006687219,0.0003139786,0.00000146197,0.000292679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3864525,"threshold_uncertainty_score":0.7684062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0475939070241856,"score_gpt":0.2854194164215044,"score_spread":0.2378255093973188,"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."}}