{"id":"W1991484848","doi":"10.3386/w12490","title":"How Corruption Hits People When They Are Down","year":2006,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Language change; Business; Computer security; Advertising; Computer science; Art; Literature","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":[0.0009302045,0.0002030878,0.0003595855,0.000954498,0.001609801,0.003280324,0.0002065014,0.0007982425,0.0129586],"category_scores_gemma":[0.01059613,0.0002055459,0.0003270781,0.001319341,0.001128165,0.002600078,0.001674603,0.001382285,0.002184663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008101024,"about_ca_system_score_gemma":0.0004393258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006790691,"about_ca_topic_score_gemma":0.01022649,"domain_scores_codex":[0.9981014,0.0009521224,0.00007928906,0.000157282,0.0001973193,0.000512721],"domain_scores_gemma":[0.9934076,0.000989431,0.003641171,0.0004331331,0.0008067219,0.0007219089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001851212,0.0001168297,0.8439521,0.0001838874,0.0002164939,0.0006307368,0.02945932,0.00021303,0.0003002686,0.01040432,0.04232425,0.07201366],"study_design_scores_gemma":[0.00002248982,0.00020802,0.8672558,0.0005298476,0.0001352104,0.001157708,0.06060753,0.0005376197,0.0003496273,0.008040057,0.06110156,0.00005452245],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9057553,0.005036825,0.0009051244,0.02802795,0.0003207805,0.00003637018,0.0012572,0.00004540432,0.05861509],"genre_scores_gemma":[0.9928832,0.001448691,0.0001061773,0.001602611,0.00008745632,0.00001248512,0.000213049,0.00001327167,0.003633087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0129586,"threshold_uncertainty_score":0.04335082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3747762841863398,"score_gpt":0.5041634109485262,"score_spread":0.1293871267621864,"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."}}