{"id":"W4378806116","doi":"10.1111/1911-3846.12878","title":"Audit partner identification, matching, and the labor market for audit talent","year":2023,"lang":"en","type":"article","venue":"Contemporary Accounting Research","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Audit; Business; Quality audit; Identification (biology); Joint audit; Accounting; Competition (biology); Audit evidence; Matching (statistics); Unintended consequences; Internal audit","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.00344546,0.0004354933,0.001082927,0.0009974759,0.001788522,0.005000683,0.001485547,0.0027654,0.02613019],"category_scores_gemma":[0.0141765,0.0004624607,0.0005694263,0.001362778,0.002443603,0.002729964,0.00228921,0.001398775,0.001315688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003790485,"about_ca_system_score_gemma":0.002952023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009973282,"about_ca_topic_score_gemma":0.00901057,"domain_scores_codex":[0.9979048,0.0006915887,0.00009462976,0.0002720383,0.0002567784,0.0007802005],"domain_scores_gemma":[0.9857544,0.007041284,0.004397707,0.0006164349,0.0004513695,0.001738778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002145499,0.003164959,0.373605,0.0002692299,0.0001722774,0.001854124,0.001774762,0.2159247,0.003250859,0.3090679,0.007273462,0.08149725],"study_design_scores_gemma":[0.0005339509,0.001275123,0.1638472,0.0002630834,0.0002321694,0.0005623426,0.005457142,0.5448003,0.00175173,0.2741322,0.006948409,0.0001962818],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9498047,0.0005937162,0.02087549,0.003302536,0.00006705269,0.0002259279,0.0003734439,0.00007370601,0.02468334],"genre_scores_gemma":[0.9929026,0.0001244036,0.0004848147,0.00005783479,0.00002378788,0.0000291876,0.00004544304,0.000003243815,0.006328666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02613019,"threshold_uncertainty_score":0.08741421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06252782929287196,"score_gpt":0.3177063109285339,"score_spread":0.2551784816356619,"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."}}