{"id":"W2890549248","doi":"10.3386/w21307","title":"Technological Change, Occupational Tasks and Declining Immigrant Outcomes: Implications for Earnings and Income Inequality in Canada","year":2015,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"University of Waterloo; Canadian Institutes of Health Research; Dalhousie University; Social Sciences and Humanities Research Council of Canada; University College London","keywords":"Earnings; Immigration; Inequality; Cohort; Demographic economics; Labour economics; Economics; Wage; Cohort effect; Task (project management); Medicine; Political science; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008144645,0.0003048588,0.0003817141,0.001740877,0.0042442,0.001861601,0.001024233,0.0005017043,0.003814842],"category_scores_gemma":[0.002895148,0.0001218644,0.0004557339,0.003684891,0.001315608,0.000563225,0.001496165,0.0008960466,0.0001821471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02206002,"about_ca_system_score_gemma":0.03352683,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9960718,"about_ca_topic_score_gemma":0.9970689,"domain_scores_codex":[0.9994074,0.00002540811,0.00001908468,0.0000709249,0.0001258265,0.0003513417],"domain_scores_gemma":[0.9983639,0.000132573,0.0003337315,0.00006292159,0.0006226999,0.0004841428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001606929,0.00004535825,0.9750137,0.00003141047,0.00004359781,0.0001600014,0.002592532,0.0006565616,0.0002083986,0.002940335,0.002175919,0.01597142],"study_design_scores_gemma":[0.000006196733,0.000008473953,0.9946263,0.00003440412,0.00001761859,0.00002144259,0.003057014,0.0005238348,0.00006534449,0.0002979862,0.001330519,0.00001070532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990576,0.0009039291,0.00009793958,0.001795288,0.00001657854,0.00001135929,0.001898988,0.000006843465,0.00469305],"genre_scores_gemma":[0.9971309,0.0004681422,0.0000657924,0.00008123487,0.00000617573,0.000004085904,0.0008114849,0.000003848296,0.001428363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02206002,"threshold_uncertainty_score":0.1600574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4532899744687846,"score_gpt":0.5500995247204742,"score_spread":0.09680955025168964,"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."}}