{"id":"W4389302953","doi":"10.32920/24724932.v1","title":"Governors and Electoral Hazard in the Allocation of US Federal Disaster Aid","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"University of Toronto; Colorado State University","keywords":"Governor; Welfare; Moral hazard; Hazard; Hazard model; Public economics; Politics; Economics; Public administration; Political science; Business; Actuarial science; Microeconomics; Incentive; Law; Engineering; Market economy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002978088,0.00008472293,0.0002772934,0.0005610909,0.0006998291,0.00143591,0.0003022639,0.0004521926,0.005889237],"category_scores_gemma":[0.01169459,0.0001565471,0.0002183153,0.0006839487,0.0007462846,0.00046329,0.0007173783,0.0007223895,0.0006526016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009034347,"about_ca_system_score_gemma":0.0006628867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01817242,"about_ca_topic_score_gemma":0.03285166,"domain_scores_codex":[0.9987569,0.0006177041,0.00005102337,0.0001379961,0.0001004752,0.0003358348],"domain_scores_gemma":[0.9894881,0.004781453,0.003468739,0.0005343683,0.0005033535,0.001223986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002810487,0.0002012398,0.9820795,0.00001012185,0.0000480222,0.00006290428,0.0008229087,0.003916782,0.0001942656,0.00358619,0.001136894,0.007660074],"study_design_scores_gemma":[0.00005698176,0.0001811469,0.9735273,0.00001402235,0.00003509972,0.00005379968,0.003439396,0.01725971,0.0004482692,0.002682448,0.002285789,0.00001605653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977903,0.00003158076,0.0002742177,0.0002341499,0.000003616271,0.000007899793,0.0000804716,0.000004211856,0.001573584],"genre_scores_gemma":[0.999015,0.0000183845,0.00005624225,0.00002116701,0.000004615553,0.000003343497,0.0000697754,0.000001915466,0.0008095505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01817242,"threshold_uncertainty_score":0.03613329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05906031202396163,"score_gpt":0.2441614793333611,"score_spread":0.1851011673093995,"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."}}