{"id":"W3142686444","doi":"","title":"Pay Transparency and the Gender Gap","year":2019,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; Government of Canada","keywords":"Salary; Transparency (behavior); Gender pay gap; Demographic economics; Gender gap; Exploit; Political science; Business; Accounting; Labour economics; Economics; Wage; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001924564,0.0001399693,0.0002745002,0.001066021,0.001998536,0.00173721,0.0005734363,0.0006939691,0.006586941],"category_scores_gemma":[0.009600452,0.0001040472,0.0002928771,0.001494753,0.00196911,0.0006879469,0.00155019,0.001227821,0.0003252339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007723174,"about_ca_system_score_gemma":0.01174747,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6665108,"about_ca_topic_score_gemma":0.7248646,"domain_scores_codex":[0.9980647,0.0002826114,0.00003784192,0.0001417023,0.0006199384,0.0008532043],"domain_scores_gemma":[0.9915142,0.002872622,0.003259511,0.0003037075,0.0009117132,0.001138254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002760154,0.0001807288,0.8898897,0.00007413058,0.00008614451,0.0002595117,0.007417998,0.00145359,0.0003240338,0.04195691,0.007221606,0.05085974],"study_design_scores_gemma":[0.00002758123,0.00006580217,0.9658432,0.0001659217,0.0000559084,0.0001334122,0.007348661,0.001890132,0.0004500383,0.01068192,0.01331446,0.0000228805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9604683,0.00332582,0.0004559148,0.00874344,0.00007712855,0.00001361117,0.00113817,0.00001465281,0.02576295],"genre_scores_gemma":[0.9982926,0.0002507327,0.0000451744,0.0001988923,0.00001574794,0.00000220293,0.00009864126,0.00000269818,0.001093388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6665108,"threshold_uncertainty_score":0.6709063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0474023021964732,"score_gpt":0.2797627150749112,"score_spread":0.232360412878438,"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."}}