{"id":"W4410179633","doi":"10.1108/aaaj-05-2024-7072","title":"Corruption networks and anti-corruption mechanisms: the case of Kenya","year":2025,"lang":"en","type":"article","venue":"Accounting auditing & accountability journal/Accounting, auditing & accountability journal","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Language change; Business; Accounting; Political science; Financial system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","metaepi_narrow"],"category_scores_codex":[0.0480723,0.001340677,0.001965012,0.001282422,0.01213587,0.005597478,0.002240962,0.00102541,0.001768059],"category_scores_gemma":[0.01270964,0.001234483,0.001024987,0.002414226,0.002017447,0.005485854,0.001017075,0.004909011,0.00006103488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003457483,"about_ca_system_score_gemma":0.002600419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005077459,"about_ca_topic_score_gemma":0.005413232,"domain_scores_codex":[0.9859575,0.001948719,0.005474078,0.001790045,0.001977859,0.002851811],"domain_scores_gemma":[0.9807808,0.004449969,0.008016068,0.001492784,0.004640344,0.0006200045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004859483,0.001236641,0.6509095,0.0009086001,0.001081596,0.0003470966,0.02389785,0.006044297,0.001663179,0.007514639,0.005715251,0.3001955],"study_design_scores_gemma":[0.009658926,0.0003930315,0.4737516,0.006559186,0.002773633,0.02232175,0.306707,0.03046646,0.0003969329,0.0381355,0.1022041,0.00663184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609565,0.001146218,0.01995104,0.0040683,0.008004552,0.001389864,0.00004389759,0.0003837127,0.004055962],"genre_scores_gemma":[0.9900876,0.001660418,0.002080266,0.001844338,0.003791243,0.0000675,0.00002370043,0.0001418665,0.0003030179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2935636,"threshold_uncertainty_score":0.9999344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01729073164170886,"score_gpt":0.3005229416252054,"score_spread":0.2832322099834966,"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."}}