{"id":"W2767824257","doi":"10.1080/03155986.2017.1393728","title":"Corporate governance, women's participation and firm performance: empirical analysis using a non-parametric evaluation methodology","year":2017,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Corporate governance; Gender diversity; Accounting; Sample (material); Business; Diversity (politics); Point (geometry); Empirical research; Regression analysis; Field (mathematics); Economics; Finance; Political science; Computer science; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01471908,0.00008040251,0.0002028283,0.0003923332,0.003320031,0.001331023,0.0001813759,0.0001373215,0.00008985206],"category_scores_gemma":[0.002601915,0.00007445117,0.00002918208,0.0006252613,0.0003488309,0.003934177,0.0001254271,0.0001685463,0.00002762009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003337589,"about_ca_system_score_gemma":0.0005653747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003665818,"about_ca_topic_score_gemma":0.0001931225,"domain_scores_codex":[0.9971156,0.0006064214,0.0004032167,0.0001402284,0.001412111,0.0003223826],"domain_scores_gemma":[0.9973968,0.0003151775,0.0003661786,0.0001963792,0.001557366,0.0001681022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001845563,0.00004558825,0.8374931,0.0001921818,0.0003028192,6.830441e-7,0.07947373,0.01821755,0.00002491528,0.04321821,0.0006841538,0.02016254],"study_design_scores_gemma":[0.0004486633,0.00006473488,0.6066437,0.00001183069,0.00003993487,7.636806e-7,0.009480692,0.3756098,0.000009936834,0.0001552393,0.00742901,0.0001057011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896326,0.00003870433,0.002169106,0.0002981052,0.0001544592,0.0005406792,0.00002794363,0.000007568785,0.007130848],"genre_scores_gemma":[0.998965,0.0001497311,0.0003608686,0.00007196294,0.00008441673,0.00007891974,0.00004197397,0.000001865487,0.0002452852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3573923,"threshold_uncertainty_score":0.9997057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6811853699541113,"score_gpt":0.5315803692977326,"score_spread":0.1496050006563787,"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."}}