{"id":"W2246127399","doi":"10.1016/j.jet.2006.03.002","title":"Optimal Dynamic Risk Sharing When Enforcement is a Decision Variable","year":2003,"lang":"en","type":"article","venue":"Journal of Economic Theory","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"University of Minnesota; National Science Foundation","keywords":"Enforcement; Incentive; Corporate governance; Ex-ante; Punishment (psychology); Business; Microeconomics; Variable (mathematics); Optimal decision; Economics; Computer science; Finance; Decision tree; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005229323,0.001148374,0.003081223,0.001062424,0.000768398,0.003535238,0.00196838,0.003983745,0.009097769],"category_scores_gemma":[0.01963862,0.001337293,0.0009242521,0.000949213,0.002730311,0.005844877,0.00248565,0.002667269,0.0004962112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001931901,"about_ca_system_score_gemma":0.002443503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001848057,"about_ca_topic_score_gemma":0.00107657,"domain_scores_codex":[0.9975244,0.000925969,0.0001312337,0.0004549958,0.0002148837,0.0007484458],"domain_scores_gemma":[0.9839407,0.01150838,0.00197463,0.001073009,0.0005347294,0.0009684841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009515927,0.0006176406,0.002342905,0.0002180464,0.0002391231,0.0004561933,0.0002367499,0.5203083,0.003340618,0.4396921,0.003229313,0.02836744],"study_design_scores_gemma":[0.0002653126,0.0002305129,0.00110743,0.00004692035,0.0001029671,0.0001038674,0.0002207397,0.5714786,0.0008354822,0.4244564,0.001093715,0.00005791547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6643834,0.0005760348,0.2880468,0.007093811,0.0002461396,0.0002857947,0.0005359857,0.0003127319,0.03851926],"genre_scores_gemma":[0.9857134,0.0001323829,0.008123062,0.0001496071,0.00006339842,0.00006770864,0.00004073177,0.00002566851,0.005684087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009097769,"threshold_uncertainty_score":0.03043503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007262281386492179,"score_gpt":0.2129185206577247,"score_spread":0.2056562392712326,"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."}}