{"id":"W3125083133","doi":"","title":"Executive Compensation, Earnings Management and Shareholder Litigation","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Wilfrid Laurier University","funders":"","keywords":"Settlement (finance); Shareholder; Executive compensation; Affect (linguistics); Dismissal; Class action; Earnings; Earnings management; Business; Compensation (psychology); Accounting; Litigation risk analysis; Actuarial science; Economics; Finance; Law; Psychology; Political science; Corporate governance; Social psychology","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":[0.002635059,0.0003488094,0.0005130903,0.001104031,0.0006602634,0.002553736,0.0006586821,0.001544284,0.007017183],"category_scores_gemma":[0.02197864,0.0001712888,0.0004144797,0.0012637,0.001486312,0.001866677,0.001121487,0.001479013,0.0006077932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001351907,"about_ca_system_score_gemma":0.000981063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003533181,"about_ca_topic_score_gemma":0.004300538,"domain_scores_codex":[0.9976834,0.0008609684,0.000159603,0.0001833841,0.0005518472,0.0005607472],"domain_scores_gemma":[0.9250028,0.0395292,0.03056879,0.000877331,0.0009412154,0.003080622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004844056,0.0009510008,0.957928,0.00006656007,0.00020937,0.0007641576,0.0003217836,0.007736435,0.0004308298,0.01089679,0.0007110244,0.01949975],"study_design_scores_gemma":[0.00003776058,0.000526994,0.9787928,0.00004821167,0.00008924672,0.0003549592,0.0005819873,0.005616565,0.0002559251,0.01230658,0.0013549,0.00003404361],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891307,0.001735781,0.0004971539,0.0009441482,0.00001340413,0.00001775298,0.00008520856,0.000009004122,0.007566711],"genre_scores_gemma":[0.99872,0.0002368409,0.00005549459,0.00004478422,0.00003009702,0.000004455705,0.0000453827,0.00000115015,0.0008617808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007017183,"threshold_uncertainty_score":0.02347487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240976958413592,"score_gpt":0.1983303061317395,"score_spread":0.1859205365476036,"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."}}