{"id":"W4384282546","doi":"10.2308/horizons-2020-207","title":"Do Gender-Diverse Boards Enhance the Linguistic Features of Corporate Financial Reporting?","year":2023,"lang":"en","type":"article","venue":"Accounting Horizons","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; University of Ottawa","funders":"Ministerio de Ciencia e Innovación","keywords":"Readability; Accounting; Tone (literature); Gender diversity; Corporate governance; Audit; Business; Transparency (behavior); Representation (politics); Quality (philosophy); Diversity (politics); Sample (material); Narrative; Political science; Finance; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00233433,0.0003504016,0.0004324421,0.0003120602,0.0007223391,0.0004614516,0.0008474915,0.0001194335,0.0001238131],"category_scores_gemma":[0.07271528,0.0002992063,0.0002143745,0.002100868,0.0002162007,0.0005926591,0.0008976781,0.0005197325,0.000596906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005372212,"about_ca_system_score_gemma":0.000102656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001089159,"about_ca_topic_score_gemma":0.0001530397,"domain_scores_codex":[0.9965813,0.00002355833,0.001066797,0.0006474958,0.0008582876,0.0008225642],"domain_scores_gemma":[0.9600015,0.0001522367,0.03853977,0.0007324317,0.0005531706,0.00002094161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000101821,0.000173038,0.3016364,0.001374026,0.000260516,0.0005722141,0.001581807,0.001333101,0.004034732,0.1626491,0.3655795,0.1607038],"study_design_scores_gemma":[0.0004874088,0.00002804305,0.5658839,0.0002937345,0.0002762611,0.000006849902,0.0009734279,0.0006704979,0.0004533577,0.01432512,0.4158158,0.0007855649],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444919,0.0001617227,0.005037827,0.0006173691,0.002807318,0.000545274,0.00001568801,0.0007683851,0.04555456],"genre_scores_gemma":[0.9931116,0.00004565536,0.000192628,0.0006662682,0.003434011,0.00003948907,0.00003607208,0.00007182522,0.002402444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2642475,"threshold_uncertainty_score":0.999946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02949658255005808,"score_gpt":0.2601917207958347,"score_spread":0.2306951382457767,"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."}}