{"id":"W3122824413","doi":"10.17848/1075-8445.27(4)-2","title":"Impacts of the COVID-19 Pandemic and the CARES Act on Earnings and Inequality","year":2020,"lang":"en","type":"article","venue":"Employment Research","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"University of Illinois at Urbana-Champaign; York University; W.E. Upjohn Institute for Employment Research","keywords":"Earnings; Unemployment; Pandemic; Economics; Inequality; Coronavirus disease 2019 (COVID-19); Labour economics; Demographic economics; Payment; Population; Panel data; Distribution (mathematics); Economic inequality; Economic growth; Medicine; Finance","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":[0.0008768887,0.000148006,0.0001533748,0.0004954937,0.0003592214,0.0007963216,0.000296922,0.0003595731,0.001915368],"category_scores_gemma":[0.004383323,0.00008597941,0.0002904484,0.0007358894,0.0003543705,0.0003708691,0.0008727929,0.0007595627,0.0001844088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001307781,"about_ca_system_score_gemma":0.0007612159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08151107,"about_ca_topic_score_gemma":0.09514974,"domain_scores_codex":[0.9992548,0.0002594151,0.00002709807,0.00004787612,0.0001478635,0.0002629985],"domain_scores_gemma":[0.9981728,0.0005310805,0.0008386731,0.0000683939,0.0001762238,0.0002129043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002197869,0.0001593742,0.9669358,0.00002629081,0.00009426648,0.0002484003,0.0002472078,0.008279311,0.0001981096,0.004084998,0.005264498,0.01424192],"study_design_scores_gemma":[0.000009316172,0.00007885241,0.989398,0.00003872587,0.00002245684,0.00003991661,0.0005949337,0.006888996,0.0001263072,0.0007500533,0.002044048,0.000008481961],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986115,0.0002480175,0.0003658097,0.00232757,0.00004511483,0.00002573092,0.00382559,0.000009055982,0.007038102],"genre_scores_gemma":[0.9982299,0.0001238,0.00009620787,0.0001559457,0.00002808754,0.00001253227,0.0008936373,0.000001720598,0.0004581095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08151107,"threshold_uncertainty_score":0.1620733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3786181147016197,"score_gpt":0.5460538319285441,"score_spread":0.1674357172269244,"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."}}