{"id":"W3082334103","doi":"10.17848/wp20-332","title":"Impacts of the Covid-19 Pandemic and the CARES Act on Earnings and Inequality","year":2020,"lang":"en","type":"report","venue":"","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada; W.E. Upjohn Institute for Employment Research","keywords":"Earnings; Unemployment; Pandemic; Economics; Inequality; Labour economics; Coronavirus disease 2019 (COVID-19); Demographic economics; Population; Payment; Panel data; Distribution (mathematics); Economic growth; Finance; Medicine","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":[0.0007801106,0.0001780102,0.000131258,0.000533779,0.000258973,0.000658981,0.0002731661,0.0002979988,0.002298238],"category_scores_gemma":[0.003341617,0.00008044945,0.0002941015,0.000738278,0.0001959329,0.0003079333,0.0007471719,0.0005918152,0.0002776659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169892,"about_ca_system_score_gemma":0.001022293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1443896,"about_ca_topic_score_gemma":0.1581647,"domain_scores_codex":[0.9994532,0.0001565911,0.00001864652,0.00003166038,0.0001611059,0.0001787433],"domain_scores_gemma":[0.9987665,0.0003333024,0.0004685762,0.00004272989,0.0002200754,0.0001687709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002240331,0.0001642203,0.9296454,0.00006791266,0.000093225,0.0002785421,0.0002257465,0.007108579,0.0002113278,0.004321028,0.0285337,0.02912633],"study_design_scores_gemma":[0.00001290374,0.00007166225,0.9848471,0.00007944128,0.0000281684,0.00005361694,0.0005664176,0.005604033,0.0002008285,0.0004887307,0.008036967,0.00001025622],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9184974,0.0009185814,0.0007968115,0.006783524,0.0001971414,0.0001191379,0.04493013,0.00004130499,0.02771592],"genre_scores_gemma":[0.982848,0.0007194273,0.0003632671,0.0005954964,0.0001165025,0.0000767575,0.01199668,0.000008893523,0.003274927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1443896,"threshold_uncertainty_score":0.2870982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2354685972499457,"score_gpt":0.4966265272720031,"score_spread":0.2611579300220573,"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."}}