{"id":"W4387523452","doi":"10.2308/bria-2022-040","title":"In All Fairness: A Meta-Analysis of the Tax Fairness–Tax Compliance Literature","year":2023,"lang":"en","type":"article","venue":"Behavioral Research in Accounting","topic":"Taxation and Compliance Studies","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; York University; Wilfrid Laurier University","funders":"","keywords":"Compliance (psychology); Distributive justice; Procedural justice; Equity (law); Business; Interpersonal communication; Perspective (graphical); Public economics; Economic Justice; Economics; Psychology; Social psychology; Microeconomics; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.002965517,0.0001591774,0.0008626857,0.001647245,0.0001465582,0.0001746407,0.000714888,0.0001023686,0.0003007831],"category_scores_gemma":[0.0003047787,0.0001347696,0.0004832617,0.009599004,0.0001544837,0.0004228424,0.0004296927,0.0005843285,0.0001901964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001390361,"about_ca_system_score_gemma":0.00002853671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002939092,"about_ca_topic_score_gemma":0.003371798,"domain_scores_codex":[0.9977211,0.0001069725,0.000803277,0.0005099229,0.0002618454,0.0005969006],"domain_scores_gemma":[0.9986811,0.0001700625,0.0003630322,0.0005589864,0.0001896645,0.00003720867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002190933,0.000260521,0.9597344,0.0001138972,0.00212688,0.00003560501,0.003142764,0.0008258003,0.0001235478,0.03053454,0.002610123,0.0004699548],"study_design_scores_gemma":[0.0003855058,0.00002221902,0.9693761,0.00006208111,0.0006465167,6.584885e-7,0.001284589,0.002897264,0.00005327008,0.01446003,0.01053355,0.0002782488],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986217,0.003886337,0.00003738095,0.004965581,0.0002339196,0.0005886424,0.0004824605,0.00003562432,0.003553065],"genre_scores_gemma":[0.9969454,0.0001411204,0.00009092718,0.0001065983,0.00002774143,0.0002308429,0.00001786982,0.0000168386,0.002422603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01607451,"threshold_uncertainty_score":0.5495743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5708730756156174,"score_gpt":0.4622197642620122,"score_spread":0.1086533113536052,"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."}}