{"id":"W2547066015","doi":"10.6082/m11n7z2t","title":"Assessing the Effects of Mandated Compensation Disclosures","year":2016,"lang":"en","type":"preprint","venue":"Knowledge@UChicago (University of Chicago)","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College","funders":"Booth School of Business, University of Chicago; Washington University in St. Louis; University of Chicago; Yale University","keywords":"Compensation (psychology); Executive compensation; Accounting; Business; Identification (biology); Actuarial science; Demographic economics; Economics; Finance; Psychology; Corporate governance","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003944796,0.0003382083,0.0006409542,0.000246267,0.0003181733,0.0001048944,0.001071134,0.0002936576,0.0001317892],"category_scores_gemma":[0.0001687867,0.000272662,0.0003192415,0.0004443858,0.0003886615,0.0008267657,0.001209073,0.0004868991,0.0001134608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005344862,"about_ca_system_score_gemma":0.000156067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005147859,"about_ca_topic_score_gemma":0.0006747079,"domain_scores_codex":[0.9984678,0.00007117884,0.0003215086,0.0005023797,0.0003608321,0.0002762827],"domain_scores_gemma":[0.9969182,0.0002947335,0.001526022,0.000752775,0.0004907044,0.00001753874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001419983,0.004032994,0.3240979,0.05039049,0.002889393,0.0002593631,0.008144558,0.0006051479,0.04011948,0.2253013,0.1357792,0.2069601],"study_design_scores_gemma":[0.002223422,0.00003522183,0.9137335,0.004199807,0.0006914596,0.000001439003,0.0004128808,0.00199783,0.0006539663,0.02374366,0.05156382,0.0007430167],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9653333,0.0005751672,0.004891786,0.002030293,0.001233398,0.0006206731,0.00004100655,0.0001042823,0.0251701],"genre_scores_gemma":[0.998253,0.0001355646,0.00009768766,0.00006114827,0.0005039882,0.000001510189,0.00006198823,0.00002983204,0.0008552402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5896356,"threshold_uncertainty_score":0.9999726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675950164980619,"score_gpt":0.2297373857546884,"score_spread":0.2129778841048822,"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."}}