{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008743874,0.00008406102,0.0002894379,0.0000990984,0.0004293027,0.000007385226,0.00005583298,0.0001226259,0.0002058922],"category_scores_gemma":[0.001436617,0.00007170389,0.00003726508,0.0002745554,0.00002186545,0.0001094473,0.00006740473,0.001110032,0.000002276139],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009675816,"about_ca_system_score_gemma":0.005820118,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2857891,"about_ca_topic_score_gemma":0.7312883,"domain_scores_codex":[0.9980674,0.0004308933,0.000855398,0.00008753919,0.0003261096,0.0002326293],"domain_scores_gemma":[0.9983066,0.0006919822,0.0004769131,0.00008031219,0.0003328085,0.0001114385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004122721,0.00002088443,0.9810932,0.000003855679,0.00004625006,0.00006304267,0.003730011,0.00004054361,0.00001358187,0.0001547013,0.01220925,0.002583398],"study_design_scores_gemma":[0.003519773,0.0001180325,0.8779069,0.0005650545,0.0000630364,0.00001736728,0.01470585,0.000003875181,0.00002760095,0.0003901565,0.1025317,0.0001507385],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858856,0.0003264979,0.00003991207,0.01130936,0.0008036224,0.0001686693,0.00002285529,0.000003998552,0.00143948],"genre_scores_gemma":[0.9984348,0.0001419548,0.00006542016,0.0003497119,0.0003296996,0.000005523893,0.000005395975,0.000008032836,0.0006594542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4454992,"threshold_uncertainty_score":0.9998159,"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."}}