{"id":"W4360621050","doi":"10.1093/oso/9780192862341.003.0004","title":"The Interconnections between Tax Crime, Organized Crime, and Corruption","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Money laundering; Language change; Organised crime; Collusion; Business; Enforcement; Law enforcement; Government (linguistics); Law and economics; Tax evasion; Political science; Public economics; Economics; Law; Finance; Industrial organization","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003918712,0.0001417963,0.0001448544,0.0009197833,0.001078331,0.002989333,0.0001975957,0.0003369882,0.003402509],"category_scores_gemma":[0.0007996731,0.00008131544,0.0001126964,0.001609295,0.005163572,0.001382757,0.001015913,0.000961358,0.0002329543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001726157,"about_ca_system_score_gemma":0.001391998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004244782,"about_ca_topic_score_gemma":0.006115473,"domain_scores_codex":[0.9994705,0.0003190993,0.000009157736,0.00002828388,0.000113022,0.00005982002],"domain_scores_gemma":[0.9994171,0.0003609686,0.00007833351,0.00002917333,0.00007389773,0.00004068096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005740043,0.00001606299,0.001815141,0.0000845168,0.000004816648,0.0001087959,0.007381536,0.0004231468,0.00005613279,0.9591433,0.01278676,0.01817405],"study_design_scores_gemma":[0.000007494569,0.00003157297,0.01898325,0.001431407,0.00001435237,0.0006622825,0.03481948,0.002212139,0.0003604445,0.3880257,0.5534248,0.00002694644],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07434759,0.03069717,0.003960527,0.01439274,0.0003929539,0.00004799057,0.000120167,0.00003345116,0.8760074],"genre_scores_gemma":[0.8947964,0.02794414,0.001821799,0.001533013,0.0002918937,0.00007235164,0.0001219879,0.00003807736,0.07338036],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.004244782,"threshold_uncertainty_score":0.01252413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06812515271228275,"score_gpt":0.3059963837421468,"score_spread":0.2378712310298641,"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."}}