{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007974617,0.0001264525,0.0002344612,0.005861382,0.001192302,0.0005253531,0.001322094,0.0001627676,0.00385884],"category_scores_gemma":[0.001331475,0.0001419236,0.00008807456,0.003730282,0.0005094717,0.0008870983,0.00008334284,0.00009960398,0.00002724394],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009900389,"about_ca_system_score_gemma":0.01388323,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9988711,"about_ca_topic_score_gemma":0.9999017,"domain_scores_codex":[0.9975643,0.0001985242,0.0002396949,0.0003886671,0.0005327574,0.001076093],"domain_scores_gemma":[0.9962621,0.00005523292,0.00005760904,0.0008532322,0.0004048292,0.002367032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006932693,0.00009199592,0.2524793,0.00001529024,0.0003217447,0.00002738871,0.05424886,4.433372e-7,0.00001088509,0.4922457,0.1865752,0.01397625],"study_design_scores_gemma":[0.0003208588,0.00008776812,0.0757098,0.000005475722,0.0001470586,4.714163e-7,0.04952738,0.0001724548,0.00004185878,0.0005757406,0.8730987,0.0003124007],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6329449,0.0003068181,0.00001790816,0.05572536,0.0004207696,0.0004281083,0.00586277,0.00005554033,0.3042378],"genre_scores_gemma":[0.9917139,0.00005509927,0.00003142453,0.001744919,0.0009545599,0.00001462872,0.0004745342,0.00001156715,0.004999407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6865235,"threshold_uncertainty_score":0.9970518,"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."}}