{"id":"W4232210518","doi":"10.15185/izalwol.48","title":"http://wol.iza.org/articles/anonymous-job-applications-and-hiring-discrimination","year":2014,"lang":"en","type":"article","venue":"IZA World of Labor","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001178447,0.0001066617,0.0001790002,0.0003024795,0.0004996097,0.0001310002,0.0003286293,0.00006414513,0.0003712406],"category_scores_gemma":[0.0006335887,0.0001081137,0.00005566844,0.0009213416,0.0004487601,0.0003362186,0.00009462551,0.0001217546,0.0001195311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006945075,"about_ca_system_score_gemma":0.0001335601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001898419,"about_ca_topic_score_gemma":0.01201558,"domain_scores_codex":[0.9981863,0.0002304271,0.0003076136,0.0002764114,0.000674417,0.0003248125],"domain_scores_gemma":[0.9986705,0.0002681068,0.0001322054,0.0002644346,0.0004827113,0.0001820797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001957781,0.000202871,0.1438864,0.0001190261,0.0000171626,0.000001076538,0.004673234,0.000007855982,0.001627488,0.8037167,0.003490046,0.04223866],"study_design_scores_gemma":[0.001294494,0.0001073587,0.4933646,0.00008811771,0.0001092581,9.050111e-7,0.006184897,0.0005555549,0.005168483,0.05307539,0.439521,0.0005299581],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8340409,0.0007347977,0.002338791,0.01359353,0.0002955221,0.0008266754,0.00002295335,0.000192012,0.1479548],"genre_scores_gemma":[0.9760989,0.0001603103,0.000585431,0.0002503886,0.0002846492,0.00007487787,0.000007269455,0.00001474922,0.02252342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7506412,"threshold_uncertainty_score":0.6704977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03430197064312236,"score_gpt":0.3528054380611194,"score_spread":0.318503467417997,"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."}}