{"id":"W2948422090","doi":"","title":"Social Mobility Trends in Canada: Going up the Great Gatsby Curve","year":2019,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Intergenerational and Educational Inequality Studies","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credence; Social mobility; Gini coefficient; Socioeconomic status; Demographic economics; Inequality; Economic inequality; Economics; Income distribution; Distribution (mathematics); Social inequality; Causality (physics); Development economics; Public economics; Sociology; Demography; Population; Social science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003937723,0.0001803355,0.0003579246,0.0001995954,0.0006817693,0.0001197099,0.0006800088,0.0001982014,0.0003160721],"category_scores_gemma":[0.000660066,0.0001611575,0.0001279013,0.0001749646,0.0004247112,0.0000825828,0.0005577015,0.001162755,0.00000996224],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.007449987,"about_ca_system_score_gemma":0.007800995,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8751163,"about_ca_topic_score_gemma":0.9946403,"domain_scores_codex":[0.9968082,0.0009324795,0.0005323635,0.0005577526,0.00049683,0.0006723881],"domain_scores_gemma":[0.9982451,0.00100714,0.0001324149,0.0003283345,0.000208967,0.00007801329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002255569,0.0003554669,0.565497,0.0002224253,0.00034774,0.00001367191,0.09314734,0.01883183,0.000007785289,0.05451155,0.03425525,0.2325844],"study_design_scores_gemma":[0.0005162728,0.00003322777,0.6347817,0.0001446072,0.00001289749,9.877838e-7,0.0570441,0.004459681,0.00001760275,0.0148411,0.2872522,0.0008957408],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7818847,0.0001303608,2.82144e-7,0.01940409,0.001874767,0.0004335303,0.00009422063,0.000009711893,0.1961684],"genre_scores_gemma":[0.9773421,0.001026765,0.00001418445,0.000212801,0.00086904,0.0002223523,0.00007556332,0.00001428285,0.02022297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2529969,"threshold_uncertainty_score":0.9978238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1218129125765459,"score_gpt":0.4072423506263935,"score_spread":0.2854294380498477,"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."}}