{"id":"W2092231391","doi":"10.1108/09513550010338755","title":"Facts, myths and monsters: understanding the principles of good governance","year":2000,"lang":"en","type":"article","venue":"International Journal of Public Sector Management","topic":"Healthcare Quality and Management","field":"Health Professions","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Corporate governance; Restructuring; Excellence; Project governance; Monster; Business; Public relations; Health care; Public sector; Function (biology); Public administration; Political science; Law; Finance","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":[0.02429201,0.0007836695,0.0007904442,0.002815757,0.01228303,0.02215475,0.002864706,0.007929944,0.002251592],"category_scores_gemma":[0.02458002,0.0005823916,0.0005346182,0.002802085,0.1331594,0.02865951,0.007926389,0.0208165,0.0004494992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02287121,"about_ca_system_score_gemma":0.02434135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08216272,"about_ca_topic_score_gemma":0.07133242,"domain_scores_codex":[0.9824427,0.01028831,0.0005378841,0.001204143,0.003317173,0.002209626],"domain_scores_gemma":[0.9804356,0.01294059,0.001931216,0.00142468,0.001710356,0.001557589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000004282523,0.000005248117,0.0002443547,0.00002996221,0.000004319426,0.00005053974,0.01210104,0.0001752808,0.00001586268,0.9751292,0.008582454,0.00365747],"study_design_scores_gemma":[0.000007629998,0.000007523284,0.0003669003,0.000231556,0.000003644826,0.00003542941,0.011627,0.0002202351,0.00003112109,0.918448,0.06900679,0.00001404271],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01458504,0.01653295,0.01616208,0.8320012,0.002151062,0.00005252878,0.00008653373,0.00006091289,0.1183677],"genre_scores_gemma":[0.8841305,0.01638957,0.00907112,0.0738496,0.002595914,0.0002105427,0.0001155032,0.00008806111,0.01354925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08216272,"threshold_uncertainty_score":0.165943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2369769560245352,"score_gpt":0.4205139158342987,"score_spread":0.1835369598097635,"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."}}