{"id":"W3165973152","doi":"10.1177/00221856211021128","title":"Nonstandard Employment and Indigenous Earnings Inequality in Canada","year":2021,"lang":"en","type":"article","venue":"Journal of Industrial Relations","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Indigenous; Earnings; Inequality; Human capital; Work (physics); Labour economics; Economics; Demographic economics; Economic growth; Finance","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":[0.0006775732,0.0001722677,0.0003141934,0.001352063,0.005444561,0.001454691,0.001126328,0.0002599536,0.005120589],"category_scores_gemma":[0.002032371,0.0001304649,0.0003031832,0.003131925,0.001041328,0.0004042828,0.001441841,0.0008004454,0.0002151729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02506604,"about_ca_system_score_gemma":0.05270693,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9971337,"about_ca_topic_score_gemma":0.9988757,"domain_scores_codex":[0.9991214,0.00004028273,0.00002928983,0.0000815917,0.0002418712,0.0004855831],"domain_scores_gemma":[0.9984338,0.00009146288,0.0002716849,0.00005125565,0.0006353434,0.0005164004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001878407,0.0001102116,0.9415707,0.000114144,0.00006353219,0.0004121256,0.01034602,0.0003277534,0.0003781419,0.004461328,0.00534982,0.0366785],"study_design_scores_gemma":[0.0000088833,0.00001778816,0.9836517,0.0001029938,0.00002215724,0.00006532235,0.009738982,0.0003577733,0.00009503014,0.0002944027,0.005627266,0.00001778209],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845672,0.0009997031,0.0001016026,0.001499512,0.00003397676,0.00002193679,0.00182405,0.000008436394,0.01094367],"genre_scores_gemma":[0.9960962,0.0006505228,0.0001055063,0.0001245755,0.000007766868,0.000004965403,0.0003681696,0.000004004963,0.002638361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02506604,"threshold_uncertainty_score":0.1818677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09184643828317483,"score_gpt":0.3788356521211125,"score_spread":0.2869892138379376,"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."}}