{"id":"W2553816796","doi":"10.1016/j.irle.2016.10.003","title":"An empirical analysis of advance notice provisions in corporate bylaws: Evidence from Canada","year":2016,"lang":"en","type":"article","venue":"International Review of Law and Economics","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Social Sciences and Humanities Research Council","funders":"","keywords":"Shareholder; CONTEST; Tender offer; Corporate governance; Accounting; Proxy (statistics); Business; Notice; Stock exchange; Event study; Stock (firearms); Empirical evidence; NOMINATE; Finance; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003815953,0.000348022,0.0006031886,0.005853551,0.008283173,0.005549722,0.002660829,0.001884952,0.006310608],"category_scores_gemma":[0.03474679,0.0005435106,0.0005894487,0.01409056,0.004261884,0.001758644,0.001909471,0.002871909,0.0007162798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08878383,"about_ca_system_score_gemma":0.1280512,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961514,"about_ca_topic_score_gemma":0.998162,"domain_scores_codex":[0.9900921,0.0005928893,0.000338254,0.0008107506,0.00584201,0.00232392],"domain_scores_gemma":[0.9154475,0.02281604,0.01572396,0.001913278,0.03776918,0.00632999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003754466,0.0006331413,0.9101751,0.0002751451,0.000181657,0.0005823425,0.01456738,0.001113905,0.0005645875,0.01626569,0.02583407,0.02943154],"study_design_scores_gemma":[0.00007890729,0.00006732679,0.9589651,0.0002325788,0.0001742596,0.00007259553,0.01592204,0.001148421,0.0004405807,0.0005888372,0.02225362,0.00005567175],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673154,0.002318284,0.0002494666,0.003391522,0.00003857892,0.0001392682,0.002931959,0.00001764717,0.0235978],"genre_scores_gemma":[0.9865807,0.001896948,0.0002510735,0.0006712222,0.00002584279,0.00003111379,0.002144589,0.00001329712,0.008385102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08878383,"threshold_uncertainty_score":0.6441748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03793185123713397,"score_gpt":0.2781584520528567,"score_spread":0.2402266008157228,"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."}}