{"id":"W1902995064","doi":"10.25336/p6t89m","title":"Studying immigrant earnings with alternative data sources and model specifications: A reply to DeVoretz’s comment","year":2013,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Earnings; Immigration; Econometrics; Economics; Actuarial science; Demographic economics; Accounting; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.03481752,0.001047468,0.001732042,0.002490466,0.006003707,0.005378322,0.006560121,0.02445137,0.007113604],"category_scores_gemma":[0.2810602,0.00105048,0.002445818,0.005345753,0.007625373,0.006727506,0.004507578,0.03864585,0.003148695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006818509,"about_ca_system_score_gemma":0.008548597,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07306895,"about_ca_topic_score_gemma":0.07653449,"domain_scores_codex":[0.9808064,0.008153916,0.001936418,0.002594283,0.005580687,0.00092837],"domain_scores_gemma":[0.6551059,0.283558,0.006189556,0.007777705,0.04439947,0.002969242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00002860534,0.00001255627,0.000867315,0.00008561251,0.00004596921,0.0001691953,0.0008411321,0.0001772738,0.00007089382,0.005624874,0.9894783,0.002598326],"study_design_scores_gemma":[0.0002663275,0.00009344322,0.0135448,0.00214802,0.0002728233,0.001060258,0.01046405,0.004157935,0.001688866,0.05975506,0.9058696,0.0006787415],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0004772104,0.0006197711,0.0004846133,0.9865355,0.01105097,0.000006483126,0.0002271884,0.00003408497,0.0005641314],"genre_scores_gemma":[0.01404086,0.001056488,0.001708379,0.9582804,0.02196029,0.00008636509,0.0001906997,0.0001416427,0.002535002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.926931,"threshold_uncertainty_score":0.1841348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1385612267442783,"score_gpt":0.3473384494434275,"score_spread":0.2087772226991493,"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."}}