{"id":"W3037194489","doi":"10.1353/ces.2020.0011","title":"Aboriginal Earnings in Canada: The Importance of Gender, Education, and Industry","year":2020,"lang":"en","type":"article","venue":"Canadian ethnic studies","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indigenous; Socioeconomic status; Earnings; Wage; Demographic economics; Inequality; Occupational prestige; Geography; Political science; Economic growth; Socioeconomics; Sociology; Economics; Demography; Labour economics; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001029098,0.0002413165,0.000358376,0.001482787,0.005164222,0.002361179,0.001177839,0.0003427348,0.004373742],"category_scores_gemma":[0.00304644,0.0001462224,0.0002944598,0.003255783,0.001512936,0.0006035534,0.001540386,0.0008872206,0.0002365999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02731414,"about_ca_system_score_gemma":0.04951433,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9970713,"about_ca_topic_score_gemma":0.9986343,"domain_scores_codex":[0.9988517,0.00008743742,0.00002828525,0.00009896408,0.0004028436,0.0005307838],"domain_scores_gemma":[0.998118,0.0001648235,0.0002615135,0.00004626123,0.0008097784,0.0005995628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001358961,0.0000492555,0.8951317,0.0001747012,0.00007690876,0.0005172461,0.02829674,0.0003981226,0.0002259911,0.006292649,0.01057925,0.05812153],"study_design_scores_gemma":[0.000004316969,0.00001222096,0.9640376,0.0002382109,0.00003392446,0.00007420241,0.02455865,0.0003275382,0.00007532709,0.0004768444,0.01013758,0.00002352185],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9610949,0.004984206,0.0002093446,0.006951959,0.00008631989,0.0000338201,0.0028203,0.00001461438,0.02380461],"genre_scores_gemma":[0.9916819,0.001968374,0.0001933033,0.0002457424,0.00001803126,0.000007735604,0.0005443472,0.000008636919,0.005331859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02731414,"threshold_uncertainty_score":0.1981788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08433587719085697,"score_gpt":0.381334397525899,"score_spread":0.296998520335042,"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."}}