{"id":"W2083299902","doi":"10.1509/jppm.25.1.117","title":"Dishonesty in Everyday Life and Its Policy Implications","year":2006,"lang":"en","type":"article","venue":"Journal of Public Policy & Marketing","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Dishonesty; Honesty; Value (mathematics); Everyday life; Psychology; Social psychology; Economics; Political science; Computer science; Law","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":[0.003099278,0.0001084267,0.0002401523,0.0005549372,0.0003781626,0.0001896517,0.0002509936,0.00006972296,0.00002730461],"category_scores_gemma":[0.004111488,0.0001077341,0.00007718446,0.0006131803,0.0001580545,0.0007169522,0.0001218179,0.0001825857,0.000003649212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000649697,"about_ca_system_score_gemma":0.001095874,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008701243,"about_ca_topic_score_gemma":0.002170802,"domain_scores_codex":[0.9983008,0.0003662767,0.0005703226,0.0001322962,0.00018417,0.0004461613],"domain_scores_gemma":[0.9987431,0.0003371158,0.0004375986,0.00008258132,0.000164512,0.0002351393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002204749,0.0001992762,0.8686736,0.00001282033,0.00002543067,0.000005877681,0.003334111,0.0000062899,0.002385441,0.1126989,0.002439579,0.01019662],"study_design_scores_gemma":[0.0005038971,0.00002850896,0.9760059,0.00003493684,0.000008148578,0.00002312232,0.003884846,0.00001036194,0.00004308872,0.004182231,0.01508732,0.0001876978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9070023,0.00100239,0.000001977809,0.0551712,0.00007804648,0.00009743822,0.000006565742,0.00001377929,0.03662631],"genre_scores_gemma":[0.9972906,0.0005045336,0.0001251949,0.0003587002,0.001392892,0.000007057613,6.561613e-7,0.00001180768,0.0003086255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1085167,"threshold_uncertainty_score":0.9978999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04477179422298604,"score_gpt":0.3649536144742226,"score_spread":0.3201818202512365,"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."}}