{"id":"W7056601577","doi":"","title":"Explaining the earnings disadvantage of visible minority immigrants in Canada","year":2008,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Disadvantage; Earnings; Immigration; Wage; Ordinary least squares; Race (biology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001334715,0.0002322247,0.0003707706,0.002295004,0.003109864,0.002282635,0.0007032881,0.0005385012,0.003468239],"category_scores_gemma":[0.003902789,0.0001221725,0.000431513,0.004479288,0.0008052004,0.0005062615,0.001026453,0.0006372161,0.0002176967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02072955,"about_ca_system_score_gemma":0.04478497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9720928,"about_ca_topic_score_gemma":0.9764379,"domain_scores_codex":[0.9994051,0.00004957265,0.00002063538,0.00004761022,0.0002482541,0.0002287231],"domain_scores_gemma":[0.9987575,0.0003054563,0.0002882117,0.00003053119,0.0004898141,0.0001284785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001450035,0.0001238466,0.5862612,0.000941614,0.0001549232,0.001082225,0.03029706,0.003348849,0.001018641,0.07500163,0.04506285,0.2565622],"study_design_scores_gemma":[0.00002241216,0.00003168384,0.9003896,0.001033594,0.0001506349,0.0001129231,0.02614765,0.003471082,0.0003778704,0.006867822,0.06133335,0.00006138612],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8939639,0.02252039,0.001185973,0.02158622,0.0002192346,0.00008649105,0.002597096,0.00004363884,0.05779707],"genre_scores_gemma":[0.9645653,0.01944658,0.0009371752,0.0009819141,0.00008176093,0.00002443337,0.0008529354,0.00001425569,0.01309562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02790719,"threshold_uncertainty_score":0.1504041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042610411944197,"score_gpt":0.2382711228897842,"score_spread":0.2278450187703422,"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."}}