{"id":"W2557530242","doi":"10.1111/cars.12124","title":"Catching Up or Falling Behind? Continuing Wealth Disparities for Immigrants to Canada by Region of Origin and Cohort","year":2016,"lang":"en","type":"article","venue":"Canadian Review of Sociology/Revue canadienne de sociologie","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Immigration; Demographic economics; Geography; Human capital; Demography; Political science; Economics; Sociology; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001490382,0.0003131493,0.001087862,0.0002219288,0.0002530617,0.00001690583,0.0004382357,0.000213949,0.00004536351],"category_scores_gemma":[0.002887697,0.0002481595,0.000169615,0.000203486,0.0003343399,0.0001885369,0.00006734534,0.0001619305,0.000002165585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001137961,"about_ca_system_score_gemma":0.00108982,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9398461,"about_ca_topic_score_gemma":0.9934014,"domain_scores_codex":[0.9974297,0.00007185178,0.0008133762,0.0005206925,0.00008451605,0.001079814],"domain_scores_gemma":[0.9978022,0.0005259099,0.0006306475,0.0003351982,0.0004892801,0.0002167678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003023044,0.000005970701,0.9436124,0.004314709,0.00006784654,0.00002382127,0.0007223392,0.000001484791,0.0002169699,0.004282969,0.04082982,0.005891428],"study_design_scores_gemma":[0.001770187,0.0002000665,0.7364221,0.02230906,0.001212902,0.00002438067,0.00604822,0.0001429476,0.00005410748,0.005874569,0.224035,0.001906504],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829121,0.008137342,0.00006881741,0.007160795,0.00039121,0.0009436756,0.0003182197,0.00002019463,0.00004767543],"genre_scores_gemma":[0.9859628,0.004439938,0.0001838841,0.008420789,0.0002804301,0.0001242993,0.0001527843,0.00003776143,0.000397296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2071903,"threshold_uncertainty_score":0.9999971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02927152186191974,"score_gpt":0.2503350931662255,"score_spread":0.2210635713043058,"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."}}