{"id":"W2270759522","doi":"10.1111/imig.12235","title":"The Human Capital Model of Selection and Immigrant Economic Outcomes","year":2016,"lang":"en","type":"article","venue":"International Migration","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Immigration; Earnings; Human capital; Demographic economics; Educational attainment; Earnings growth; Economics; Political science; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001826139,0.0004535146,0.0004606796,0.001209489,0.001060651,0.002141483,0.0008078577,0.0007137388,0.007660559],"category_scores_gemma":[0.005081633,0.0001965286,0.0004388646,0.00116607,0.002683786,0.0008866974,0.001250154,0.0008233426,0.0005989887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003453763,"about_ca_system_score_gemma":0.003761481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2167549,"about_ca_topic_score_gemma":0.1390642,"domain_scores_codex":[0.9994769,0.0001806983,0.000008343994,0.00005653709,0.00005741959,0.0002201298],"domain_scores_gemma":[0.9976914,0.0009972769,0.0004348833,0.00009841071,0.0002526691,0.0005253852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003249608,0.0003839392,0.5420929,0.0001053403,0.0003335957,0.001753013,0.003017466,0.09472954,0.0004409136,0.3001001,0.008361176,0.04835695],"study_design_scores_gemma":[0.000208323,0.0004076918,0.5038773,0.0002626684,0.0002996514,0.0006019752,0.003662345,0.2169621,0.0002306913,0.2628686,0.01051851,0.0001001667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.953183,0.001151052,0.01117052,0.005761595,0.00007582155,0.0001003009,0.0006592629,0.00006118572,0.02783731],"genre_scores_gemma":[0.9928567,0.0004532808,0.0002888869,0.00009570215,0.00002873812,0.00001902991,0.0001108368,0.000003277272,0.00614352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2167549,"threshold_uncertainty_score":0.4309865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323971893820301,"score_gpt":0.2920916670510071,"score_spread":0.2788519481128041,"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."}}