{"id":"W2794416703","doi":"10.3138/cpp.2017-033","title":"Do Large Employers Treat Racial Minorities More Fairly? An Analysis of Canadian Field Experiment Data","year":2018,"lang":"en","type":"article","venue":"Canadian Public Policy","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Callback; Disadvantage; Audit; Test (biology); Diversity (politics); Scale (ratio); Race (biology); Business; Personnel selection; Public relations; Psychology; Political science; Management; Sociology; Accounting; Law; Geography; Economics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02163007,0.0003307668,0.0008764284,0.001915482,0.009065693,0.003287519,0.001742662,0.0012029,0.006536973],"category_scores_gemma":[0.06906416,0.0002825632,0.0005292012,0.004341382,0.003329688,0.001843622,0.00160881,0.001788971,0.0004965788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02072105,"about_ca_system_score_gemma":0.02865072,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9592533,"about_ca_topic_score_gemma":0.9738477,"domain_scores_codex":[0.9855074,0.00444856,0.0004447385,0.001389153,0.005139575,0.003070541],"domain_scores_gemma":[0.9471217,0.02401774,0.01031995,0.005733746,0.009563897,0.00324299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001250467,0.0006364818,0.8435655,0.0002526952,0.0003244225,0.0001854856,0.02325306,0.0005981053,0.00111556,0.01624021,0.01971941,0.09285875],"study_design_scores_gemma":[0.00008196038,0.00007386075,0.9704158,0.00009222051,0.00009080687,0.00001844853,0.01449322,0.0005845447,0.0003770426,0.001622273,0.01210056,0.00004933827],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9419883,0.001250961,0.001766995,0.01410092,0.0001054013,0.0004927,0.002506186,0.00003451041,0.03775381],"genre_scores_gemma":[0.9909991,0.0003853761,0.0006861573,0.00382618,0.00002827956,0.0001011244,0.0006056342,0.00001695668,0.003351157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04074669,"threshold_uncertainty_score":0.1503424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1175589638002823,"score_gpt":0.4291320443695143,"score_spread":0.3115730805692321,"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."}}