{"id":"W2889122466","doi":"10.1177/2378023119881282","title":"A Meta-Analysis of the Association between Income Inequality and Intergenerational Mobility","year":2019,"lang":"en","type":"article","venue":"Socius Sociological Research for a Dynamic World","topic":"Intergenerational and Educational Inequality Studies","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gini coefficient; Inequality; Economic inequality; Demographic economics; Economics; Income distribution; Social mobility; Distribution (mathematics); Association (psychology); Econometrics; Income inequality metrics; Sociology; Psychology; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01439097,0.001558599,0.005434003,0.006091217,0.0007741425,0.002515017,0.001191891,0.001274091,0.00289406],"category_scores_gemma":[0.03720776,0.000710715,0.0235887,0.008357165,0.000493245,0.001108372,0.001314531,0.001403994,0.00022145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001241615,"about_ca_system_score_gemma":0.001663137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006069569,"about_ca_topic_score_gemma":0.01346542,"domain_scores_codex":[0.9911914,0.004758131,0.001815673,0.001232927,0.0007217376,0.0002801561],"domain_scores_gemma":[0.9752,0.01852578,0.00256008,0.002100386,0.001372013,0.0002417393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.001867535,0.00002710034,0.04758909,0.04603613,0.8798965,0.0002622162,0.0001447081,0.0006426547,0.0004410896,0.0004711469,0.001321485,0.0213004],"study_design_scores_gemma":[0.0001873409,0.0001713117,0.03063853,0.006652575,0.9584,0.0001710923,0.00008129785,0.0003098137,0.000264543,0.0005735905,0.002532922,0.0000169799],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.04569675,0.946081,0.003885599,0.0007006403,0.0004689514,0.000157268,0.002047752,0.00006973555,0.0008922847],"genre_scores_gemma":[0.7043243,0.2834489,0.006937559,0.001045409,0.0004605644,0.0006246861,0.0022988,0.00008464982,0.0007752115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01439097,"threshold_uncertainty_score":0.07610768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3999651006836782,"score_gpt":0.5103590414661235,"score_spread":0.1103939407824454,"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."}}