{"id":"W2061092425","doi":"10.1016/j.jeoa.2014.09.012","title":"Economic inequality and intergenerational transfers: Evidence from Mexico","year":2014,"lang":"en","type":"article","venue":"The Journal of the Economics of Ageing","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute on Aging; International Development Research Centre","keywords":"Economics; Inequality; Socioeconomic status; Asset (computer security); Economic inequality; Demographic economics; Transfer payment; Labour economics; Crowding out; Monetary economics; Sociology; Population; Demography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000905529,0.0002337673,0.0004430345,0.001431252,0.001412119,0.001136497,0.0005949005,0.0005639239,0.005623449],"category_scores_gemma":[0.00349966,0.0002191236,0.0002922954,0.004050352,0.0007353247,0.0008731754,0.001929179,0.0007446184,0.0002447254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009345093,"about_ca_system_score_gemma":0.0005631861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1752301,"about_ca_topic_score_gemma":0.2246722,"domain_scores_codex":[0.9995977,0.0001262463,0.00001981244,0.00006324997,0.00003893084,0.0001539917],"domain_scores_gemma":[0.9965005,0.001099856,0.001640984,0.0001812357,0.0003110014,0.0002663565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003715505,0.00024951,0.9826519,0.00007787594,0.0002382802,0.0002788893,0.003567669,0.0002403805,0.00008023008,0.001836824,0.001414492,0.00899236],"study_design_scores_gemma":[0.00002477981,0.00004335298,0.9935094,0.00007263554,0.0001443268,0.00004491321,0.004129392,0.0001093375,0.00004021876,0.0002665473,0.00160882,0.000006416018],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961631,0.0007396955,0.0000547636,0.000461664,0.000005429405,0.000004836335,0.0006789096,0.000001560474,0.001890066],"genre_scores_gemma":[0.9966908,0.001318537,0.00006462911,0.00007282131,0.00001695144,0.00001388975,0.0009103845,0.00000269639,0.0009092327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1752301,"threshold_uncertainty_score":0.3484203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01953036197670076,"score_gpt":0.2190058345523105,"score_spread":0.1994754725756097,"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."}}