{"id":"W2152840954","doi":"10.3386/w17368","title":"Managerial Attributes and Executive Compensation","year":2011,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":217,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Bank of Canada; Wilfrid Laurier University; Brock University; York University; University of Toronto; University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Executive compensation; Variation (astronomy); Compensation (psychology); Accounting; Fixed effects model; Business; Variable (mathematics); Econometrics; Economics; Microeconomics; Corporate governance; Panel data; Finance; Psychology; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001946292,0.0002317003,0.0002244883,0.001409288,0.0005179042,0.001458976,0.0003095454,0.0004220528,0.007053298],"category_scores_gemma":[0.01396855,0.00008052604,0.000203728,0.001973757,0.0004227412,0.0007959703,0.0006417393,0.0006104198,0.0007527974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006708337,"about_ca_system_score_gemma":0.0004083408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654466,"about_ca_topic_score_gemma":0.002816824,"domain_scores_codex":[0.9990337,0.0003452052,0.00007349275,0.0001071016,0.0002438619,0.000196695],"domain_scores_gemma":[0.9725685,0.009205659,0.01377335,0.001018549,0.001060919,0.002373007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006602749,0.0001810105,0.9778672,0.0000203807,0.00005165583,0.00007423415,0.0003704439,0.001024499,0.0001320901,0.003372761,0.0005166921,0.01632303],"study_design_scores_gemma":[0.000006433445,0.00007112097,0.9938906,0.00001910318,0.00001316686,0.0000621615,0.0003687966,0.0008601623,0.0000910717,0.00320258,0.001408296,0.000006502232],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874308,0.0009854386,0.0006451574,0.0004447826,0.00002112253,0.00001242995,0.00025904,0.000007029158,0.01019414],"genre_scores_gemma":[0.9982388,0.0001565458,0.0001324878,0.00002612683,0.000033142,0.000003728642,0.0001437063,0.000001453902,0.001263844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007053298,"threshold_uncertainty_score":0.02359557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3251565248578127,"score_gpt":0.4178119341648404,"score_spread":0.09265540930702765,"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."}}