{"id":"W2332088928","doi":"10.1177/0001839216639577","title":"Whitened Résumés","year":2016,"lang":"en","type":"article","venue":"Administrative Science Quarterly","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":418,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Stanford Bio-X; University of Toronto; Harvard University","keywords":"Seekers; Diversity (politics); Transparency (behavior); Disadvantage; Audit; Racism; Racial diversity; Social psychology; Presentation (obstetrics); Equal employment opportunity; Inequality; Psychology; Sociology; Ethnic group; Political science; Economics; Law; Management; Gender studies; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003224398,0.0002544078,0.0002373425,0.0004357957,0.001847458,0.001880656,0.0005118299,0.0006156849,0.009491593],"category_scores_gemma":[0.01621086,0.0001686089,0.0001726004,0.000264506,0.001272461,0.001484583,0.001479,0.001047136,0.001268839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004597236,"about_ca_system_score_gemma":0.0007030211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000721238,"about_ca_topic_score_gemma":0.001295711,"domain_scores_codex":[0.9970821,0.00149995,0.0002168519,0.0003167378,0.0005148428,0.000369644],"domain_scores_gemma":[0.9909934,0.003393919,0.001962347,0.001807951,0.0008509578,0.0009913974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002325165,0.007113283,0.192279,0.0007965554,0.00006321441,0.003074227,0.3335999,0.0009362121,0.06588809,0.01943264,0.01445644,0.3600352],"study_design_scores_gemma":[0.00018347,0.007981687,0.3610862,0.0007139902,0.00006956382,0.002174317,0.3207751,0.002910857,0.03755064,0.009119885,0.2570466,0.0003877502],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885275,0.00009628335,0.001439548,0.0002952284,0.00009095787,0.0001655846,0.00006434654,0.00005606831,0.009264476],"genre_scores_gemma":[0.9799329,0.0001185789,0.002218803,0.0004550405,0.00002791548,0.0001354587,0.00007885176,0.00002725127,0.01700514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009491593,"threshold_uncertainty_score":0.03175253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1043334588649695,"score_gpt":0.4490576440112576,"score_spread":0.3447241851462881,"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."}}