{"id":"W2137334353","doi":"10.1287/mnsc.2014.2124","title":"Discretionary Sanctions and Rewards in the Repeated Inspection Game","year":2015,"lang":"en","type":"article","venue":"Management Science","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; York University; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Universiteit van Amsterdam; Royal Economic Society; Leverhulme Trust","keywords":"Sanctions; Discretion; Earnings; Microeconomics; Economics; Behavioral economics; Business; Political science; Law; Accounting","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":[0.005411543,0.0008273374,0.001133808,0.000497418,0.0006356239,0.001741896,0.00142833,0.002044023,0.00621595],"category_scores_gemma":[0.02949219,0.0004260442,0.0005562177,0.0003529911,0.001682653,0.001984156,0.00125922,0.001997033,0.0003427178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001811114,"about_ca_system_score_gemma":0.001297409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00238837,"about_ca_topic_score_gemma":0.003688534,"domain_scores_codex":[0.9948702,0.003119172,0.0002196502,0.000455663,0.0007549191,0.0005804949],"domain_scores_gemma":[0.9542866,0.03172768,0.008113691,0.003376189,0.0005967109,0.001899157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01869443,0.02324579,0.0942471,0.001244429,0.001117075,0.001845689,0.004096223,0.2778354,0.1030077,0.3320277,0.007174991,0.1354634],"study_design_scores_gemma":[0.003633386,0.01116091,0.09042969,0.0001862275,0.0004378566,0.0005800409,0.001370614,0.6062454,0.01295361,0.2665689,0.00602694,0.0004063814],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808614,0.00008264415,0.009657939,0.0004067325,0.00002419116,0.0001177674,0.00006680515,0.0000406082,0.008741817],"genre_scores_gemma":[0.9959131,0.00003647415,0.002677978,0.00008966511,0.000008253491,0.00007331505,0.00001786875,0.00000714295,0.001176171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00621595,"threshold_uncertainty_score":0.02861935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0584064833595772,"score_gpt":0.3596950911005722,"score_spread":0.301288607740995,"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."}}