{"id":"W1843663959","doi":"","title":"Ownership versus Management Effects on Performance in Family and Founder Companies: A Bayesian Analysis","year":2010,"lang":"en","type":"preprint","venue":"Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)","topic":"Family Business Performance and Succession","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; University of Alberta","funders":"","keywords":"Multicollinearity; Bayesian probability; Agency (philosophy); Principal–agent problem; Economics; Sociology; Management; Computer science; Regression analysis; Corporate governance; Social science; Statistics; Mathematics; Artificial intelligence","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":[0.02550176,0.0005408734,0.001664168,0.002427326,0.0007765042,0.002038811,0.001226411,0.001521032,0.01033467],"category_scores_gemma":[0.06913704,0.0003452305,0.002175126,0.001419112,0.001910779,0.001928871,0.002090669,0.001535628,0.0007007275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009054314,"about_ca_system_score_gemma":0.000958737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01471324,"about_ca_topic_score_gemma":0.006208246,"domain_scores_codex":[0.9924326,0.004806523,0.000263183,0.0007939803,0.0009100716,0.0007936889],"domain_scores_gemma":[0.8842543,0.09791119,0.008735882,0.00405169,0.002194204,0.002852672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002807189,0.0009540595,0.8585399,0.0001681927,0.001759872,0.0006957233,0.003568873,0.01541316,0.001552501,0.03384098,0.002003597,0.07869588],"study_design_scores_gemma":[0.0002432664,0.001402999,0.7959518,0.0001729179,0.001913825,0.0006415514,0.001814034,0.1464375,0.001197466,0.04658163,0.003498761,0.0001443493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784168,0.0007628566,0.01653072,0.0005508044,0.00001610037,0.00008803755,0.0003347856,0.00005002131,0.003249893],"genre_scores_gemma":[0.995682,0.0002640364,0.001856642,0.00005562507,0.00003520647,0.00003691158,0.0002199481,0.00001501438,0.001834545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02550176,"threshold_uncertainty_score":0.1348678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02170710259212221,"score_gpt":0.2153924992755552,"score_spread":0.193685396683433,"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."}}