{"id":"W4412864583","doi":"10.2139/ssrn.5374760","title":"Genderized Names and Financial Misreporting","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Economics; Business","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01567916,0.0002551098,0.0004894116,0.002128211,0.001879375,0.004004753,0.0007639301,0.002583779,0.01230641],"category_scores_gemma":[0.1023727,0.0002341573,0.0002356767,0.003770343,0.004927687,0.004951643,0.001822158,0.001974852,0.0007816807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051409,"about_ca_system_score_gemma":0.001169261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003673413,"about_ca_topic_score_gemma":0.003136683,"domain_scores_codex":[0.9898032,0.006617744,0.000567125,0.0007581469,0.001458256,0.0007955092],"domain_scores_gemma":[0.861078,0.08288822,0.04154452,0.007702467,0.004939777,0.001847103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00112017,0.0007799722,0.5686123,0.0002961688,0.0001727958,0.001008065,0.0288904,0.0008693472,0.0004063977,0.2687415,0.02012081,0.1089821],"study_design_scores_gemma":[0.0001784522,0.0003493462,0.4554877,0.0005950422,0.0002438902,0.001545624,0.05702869,0.003141032,0.001324152,0.451508,0.02846091,0.0001371363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9095935,0.004385026,0.003207175,0.03055515,0.0005024903,0.00003296287,0.0005552748,0.00001536988,0.05115306],"genre_scores_gemma":[0.9958762,0.0008443524,0.0002286838,0.0007478232,0.0002325907,0.00001034216,0.00005353966,0.000005138251,0.002001298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01567916,"threshold_uncertainty_score":0.08292037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03017272878099809,"score_gpt":0.3668113640150989,"score_spread":0.3366386352341008,"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."}}