{"id":"W4281556401","doi":"10.1111/labr.12226","title":"Worse than a double whammy: The intersectional causes of wage inequality between women of colour and White men over time","year":2022,"lang":"en","type":"article","venue":"Labour","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Wage; Current Population Survey; White (mutation); Race (biology); Demographic economics; Ethnic group; Population; Inequality; Economics; Distribution (mathematics); Demography; Labour economics; Gender studies; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001635019,0.0001308777,0.0002859175,0.00135587,0.001057144,0.00154671,0.0003937696,0.0005957031,0.003381348],"category_scores_gemma":[0.004948028,0.0001181,0.00045426,0.001356319,0.00135201,0.001247972,0.002131728,0.0008669837,0.0003063348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005356431,"about_ca_system_score_gemma":0.0007903569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03800255,"about_ca_topic_score_gemma":0.06010513,"domain_scores_codex":[0.9991364,0.0002207072,0.00003247624,0.0001788784,0.0001453179,0.0002861969],"domain_scores_gemma":[0.9972419,0.0006391596,0.001183471,0.0002308635,0.0003293508,0.0003753947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009035008,0.00003390724,0.9757956,0.00001715107,0.00007214797,0.0001579191,0.005429312,0.0001896544,0.0002433515,0.004678844,0.001286837,0.01200497],"study_design_scores_gemma":[0.000001962562,0.00003305373,0.9860432,0.00004558649,0.00002817215,0.00009036875,0.008993822,0.0003841318,0.0001368825,0.001837885,0.002394795,0.00001003756],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904727,0.001297232,0.0005758549,0.002718528,0.00006668267,0.000006579719,0.0004572887,0.000007755915,0.004397415],"genre_scores_gemma":[0.99898,0.0001274701,0.00007046997,0.000145958,0.00002777847,0.000002716179,0.0001112704,0.000003356165,0.0005310419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03800255,"threshold_uncertainty_score":0.07556272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997773394955484,"score_gpt":0.226439087682843,"score_spread":0.2064613537332881,"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."}}