{"id":"W2950138639","doi":"10.1108/jfrc-07-2017-0060","title":"The impact of public scrutiny on executive compensation","year":2019,"lang":"en","type":"article","venue":"Journal of Financial Regulation and Compliance","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Scrutiny; Executive compensation; Compensation (psychology); Treasury; Originality; Accounting; Value (mathematics); Wage; Economics; Business; Corporate governance; Public economics; Labour economics; Finance; Law; Political science","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":[0.004164508,0.0001839918,0.0004666054,0.001353029,0.0008197157,0.003415592,0.0004888095,0.0007976188,0.004952483],"category_scores_gemma":[0.03247857,0.0001796759,0.0003230593,0.001164088,0.001577022,0.001544161,0.001793437,0.001476465,0.0003765679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003552106,"about_ca_system_score_gemma":0.001899765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007212696,"about_ca_topic_score_gemma":0.009994157,"domain_scores_codex":[0.9934887,0.001643952,0.0004788811,0.0006446877,0.002165888,0.001577952],"domain_scores_gemma":[0.8905382,0.02271997,0.07600619,0.00343927,0.004468611,0.002827757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004322616,0.0004089519,0.9527758,0.0001319522,0.0001912233,0.0002589448,0.001428832,0.001857604,0.001044041,0.003806404,0.001969315,0.03569455],"study_design_scores_gemma":[0.000009994867,0.0001700608,0.9943581,0.00004948193,0.00002612697,0.00003796293,0.001549291,0.0006857243,0.0005301717,0.0008887851,0.001678867,0.00001549786],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840576,0.0006308496,0.0003273538,0.001717071,0.00002800926,0.00002827846,0.0001995692,0.00001543318,0.01299577],"genre_scores_gemma":[0.9992626,0.00006051182,0.00003255039,0.00009884356,0.0000346823,0.0000034623,0.00005244433,0.000002192668,0.0004526122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007212696,"threshold_uncertainty_score":0.02577245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04254692871242265,"score_gpt":0.2629095139826957,"score_spread":0.220362585270273,"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."}}