{"id":"W4403971205","doi":"10.1016/j.jmoneco.2024.103699","title":"How to fund unemployment insurance with informality and false claims: Evidence from Senegal","year":2024,"lang":"en","type":"article","venue":"Journal of Monetary Economics","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Unemployment; Economics; Actuarial science; Macroeconomics","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":[0.008523146,0.0003917603,0.0003349373,0.001143053,0.001665569,0.003665901,0.001447797,0.001824726,0.005090437],"category_scores_gemma":[0.03889168,0.0003720228,0.0004710673,0.001036381,0.002456765,0.002571149,0.002703406,0.001612091,0.00051962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002138492,"about_ca_system_score_gemma":0.004615521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04057546,"about_ca_topic_score_gemma":0.05634856,"domain_scores_codex":[0.9945808,0.002958473,0.000266788,0.0002190204,0.0006968849,0.001277952],"domain_scores_gemma":[0.9508014,0.02814079,0.01153535,0.003205191,0.003158347,0.00315885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005730116,0.002056799,0.8031903,0.0006471768,0.0009748793,0.002801002,0.01266084,0.00390198,0.001764283,0.02929272,0.009192195,0.1277878],"study_design_scores_gemma":[0.001812228,0.002720219,0.8629872,0.001778566,0.001927517,0.002223699,0.05092909,0.009115733,0.0032195,0.01890669,0.04419594,0.000183504],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852903,0.001293814,0.0002549139,0.003620596,0.00003005103,0.00004475472,0.0001721917,0.00001216452,0.009281291],"genre_scores_gemma":[0.9988353,0.0002618607,0.00010793,0.0001838636,0.00001066083,0.00001145425,0.00003407361,0.000002556345,0.0005522062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04057546,"threshold_uncertainty_score":0.08067858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03457100163211479,"score_gpt":0.2755008630749236,"score_spread":0.2409298614428088,"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."}}